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Third-stage larvae ( L3 ) of the canine hookworm , Ancylostoma caninum , undergo arrested development preceding transmission to a host . Many of the mRNAs up-regulated at this stage are likely to encode proteins that facilitate the transition from a free-living to a parasitic larva . The initial phase of mammalian host invasion by A . caninum L3 ( herein termed “activation” ) can be mimicked in vitro by culturing L3 in serum-containing medium . The mRNAs differentially transcribed between activated and non-activated L3 were identified by suppression subtractive hybridisation ( SSH ) . The analysis of these mRNAs on a custom oligonucleotide microarray printed with the SSH expressed sequence tags ( ESTs ) and publicly available A . caninum ESTs ( non-subtracted ) yielded 602 differentially expressed mRNAs , of which the most highly represented sequences encoded members of the pathogenesis-related protein ( PRP ) superfamily and proteases . Comparison of these A . caninum mRNAs with those of Caenorhabditis elegans larvae exiting from developmental ( dauer ) arrest demonstrated unexpectedly large differences in gene ontology profiles . C . elegans dauer exiting L3 up-regulated expression of mostly intracellular molecules involved in growth and development . Such mRNAs are virtually absent from activated hookworm larvae , and instead are over-represented by mRNAs encoding extracellular proteins with putative roles in host-parasite interactions . Although this should not invalidate C . elegans dauer exit as a model for hookworm activation , it highlights the limitations of this free-living nematode as a model organism for the transition of nematode larvae from a free-living to a parasitic state .
Parasitic nematodes are of considerable medical , veterinary and agricultural importance . For example , it is estimated that the morbidity attributable to hookworms , Trichuris and Ascaris , the three most prevalent parasitic nematodes in humans globally , could be as high as 39 disability adjusted life years ( DALY ) [1] . This assessment takes into account the long-term impact of infection on cognitive and physical development and the overall health of the host . World-wide , ∼1 . 3 billion people are infected with at least one of these geohelminths [2] . The prevalence of the human hookworms , Ancylostoma duodenale and Necator americanus , alone approaches 740 million , with the foci predominantly within Asia , sub-Saharan Africa , and Latin America [3] . Facultative developmental arrest in the free-living nematode , Caenorhabditis elegans , can occur transiently in the first larval stage ( L1 ) as well as for prolonged periods at the L3 stage . Developmental arrest ( often referred to as the dauer stage ) in the L3 is triggered in response to conditions , such as crowding , scarcity of food and elevated temperature [4] . When the environment improves , worms exit the arrest to resume development . However , under permissive conditions , arrest is bypassed and adult and reproductive development is favoured . For many parasitic nematodes , arrest at the L3 facilitates survival in the environment . The exit from arrest marks the return to growth and development as well as the transmission of the parasite to its host . Larvae invade a suitable host and undergo a migration through particular tissues to then establish in a target organ and complete the life cycle or arrest in specific tissues . The infective L3 of many parasitic nematodes produce mRNAs which are thought to relate to invasion , migration , and/or survival [5]–[10] . Therefore , the characterization of mRNAs transcribed in the L3 during its transition from the free-living to the parasitic stage may aid in the identification of genes associated with these processes . An attractive parasite model in which to experimentally study this transition is the dog hookworm , Ancylostoma caninum , for which an in vitro serum-stimulation assay exists [11] . Several molecular aspects associated with serum stimulation have been investigated previously in A . caninum . Some researchers have focused on the release of activation-associated proteins; these molecules include the pathogenesis related protein ( PRP ) superfamily members Ac-ASP-1 [12] and Ac-ASP-2 [13] , and the metalloprotease Ac-MTP-1 [14] , all of which represent the most abundant excreted/secreted proteins released by serum-stimulated ( activated ) L3 . Other workers have studied activation-associated genes of hookworms using a transcriptomic approach . For instance , Mitreva et al . [8] generated expressed sequence tags ( ESTs ) for A . caninum ( serum stimulated , unstimulated and tissue-arrested L3 ) and A . ceylanicum ( unstimulated L3 and adults ) , being the first systematic study of genes associated with the host invasion process . However , this study had some limitations in that ( 1 ) comparative analyses made between larval stages were qualitative rather than quantitative; ( 2 ) some of the observed differences in the abundance of ESTs between activated and non-activated A . caninum L3 seemed to be attributable to differences in the procedures employed for the construction of the cDNA libraries from these life-cycle stages; and ( 3 ) the study included a relatively small number of randomly generated sequences available at the time for A . caninum ( n = 3840 ) and A . ceylanicum ( n = 3149 ) . Moser et al . [7] addressed the first two points by conducting a quantitative microarray analysis of A . caninum genes associated with the transition to parasitism , focusing on decreased transcription after serum stimulation ( i . e . , those mRNAs which are “switched off” or reduced in transcription upon host entry ) . However , this study was also limited to known ESTs available in the public databases . To infer the mRNAs involved in the infective process of A . caninum , we conducted herein a quantitative study of all known A . caninum sequences as well as newly identified genes discovered through suppressive-subtractive hybridisation ( SSH ) of activated versus non-activated L3 of A . caninum . The method of SSH was employed to selectively enrich differentially transcribed genes [15] . In summary , 242 potentially up-regulated and 109 potentially down-regulated mRNAs were identified by SSH . There were many mRNAs that were differentially expressed but not identified by SSH , although this might be a function of the number of clones randomly sequenced from our subtracted libraries . The final repertoire of activation-associated genes consisted of 240 up-regulated and 362 down-regulated mRNAs . Among these nearly 600 activation-associated genes were numerous ( often substantially up-regulated ) mRNAs encoding PRPs and three of the major catalytic classes of proteases ( metallo- , cysteine , and aspartic ) . Several mRNAs encoding novel secreted proteins without any known homologues were also identified . These mRNAs , if demonstrated to be integral to the parasitic process , could represent a new generation of potential vaccine antigens and drug targets against hookworms .
A . caninum L3 were isolated from the faeces of stray dogs in the greater Brisbane area and surrounding towns in Queensland , Australia , using a standard charcoal coproculture method . Cultures were incubated at ∼23°C in a humidified chamber for one week , after which L3 were concentrated using a modified Baermann technique and purified through a nylon filter ( 20 µm ) . Larvae were stored for up to four weeks in 50 mM Na2HPO4 , 22 mM KH2 PO4 , 70 mM NaCl , pH 6 . 8 [16] in 12 . 5 cm2 vented tissue culture flasks in the dark at room temperature until use . In total , four separate groups of L3 representing four separate infections from different geographical locations were obtained . The first group was used for SSH and time course studies , whereas the others were employed as biological replicates in microarray validation and real-time PCR analyses ( Figure 1 ) . The specific identity of the parasite material was confirmed by PCR amplification of the first and second internal transcribed spacers ( ITS-1 and ITS-2 ) of nuclear ribosomal DNA ( as described by [17] ) and automated sequencing ( using BigDye chemistry , ABI ) . The sequences determined were required to be identical to those with GenBank accession numbers Y19181 ( ITS-1 ) and AJ001591 ( ITS-2 ) . Prior to in vitro activation ( serum-stimulation ) , ensheathed L3 were incubated in 1% HCl for 30 min at ∼23°C and then resuspended in RPMI-C ( RPMI-1640 tissue culture medium supplemented with 25 mM HEPES ( pH 7 . 0 ) , 100 IU/ml of penicillin , 100 µg/ml of streptomycin , and 40 µg/ml of gentamycin ) [12] . To each well of a 24-well tissue culture plate , 5 , 000 L3 were added . For the SSH , a total of 40 , 000 L3 were activated in 15% serum and 25 mM S-methylglutathione in RPMI-C , whereas 25 , 000 L3 were incubated in RPMI-C alone ( non-activated control ) . Five thousand L3 were sampled at each of four time points during the activation ( 1 , 6 , 13 , and 24 h ) , in order to perform a time-course analysis of transcripts using real-time PCR ( described in “Validation of transcription via real-time PCR” ) . The same number of non-activated control L3 were separately prepared for this analysis , leaving 20 , 000 activated and 20 , 000 non-activated worms for SSH . For the microarray analysis , activated and non-activated L3 ( 50 , 000 of each ) were prepared from each of two separate populations of A . caninum . Also , activated and non-activated L3 ( 5 , 000 of each ) were prepared for real-time PCR . For the in vitro activation , L3 were incubated overnight at 37°C in 5% CO2; pharyngeal pumping in activated L3 was verified by feeding ∼100 of them with FITC-BSA ( 10 mg/ml ) for 3 h and fluorescence was detected using a Leica DM IRB inverted microscope with a Leica DC 500 high-resolution digital camera [11] . Activated and non-activated L3 were each washed twice in phosphate-buffered saline ( PBS , pH 7 . 4; 23°C ) and immediately frozen at −80°C . For RNA isolation , larvae were resuspended in 100 µl of Trizol reagent and homogenized in a 1 . 5 ml tube using an RNase-free , disposable , in-tube pestle and subjected to three rapid ( 1 min ) freeze/thaw cycles . Trizol was added to a final volume of 500 µl , before snap freezing in liquid nitrogen . These samples were stored for ≤1 month at −80°C before RNA was isolated . Frozen samples of L3 in Trizol were brought to 4°C and centrifuged ( 16 , 000×g at the same temperature ) for 10 min to remove insoluble debris and residual genomic DNA . RNA was then extracted with chloroform , precipitated with isopropanol , washed with absolute ethanol and resuspended in 50 µl of RNAse-free water . Each RNA sample was treated with 2 U of DNase I ( Promega ) prior to heat denaturation of the enzyme ( 75°C for 5 min ) and frozen immediately at −80°C . The integrity of RNA was verified to have an RNA Integrity Number >8 . 0 using an Agilent 2100 Bioanalyzer and RNA 6000 LabChip Kit ( Agilent Technologies ) . RNA used for microarray analysis was stored as an ethanol precipitate in 75% ethanol at −80°C . First strand cDNA was synthesized from 1 µg of total RNA using the SuperSmart cDNA synthesis kit ( Clontech ) , according to the manufacturer's protocol . Subsequently , double stranded cDNA was produced through 17 rounds of PCR amplification and purified by phenol:chloroform:isoamyl alcohol ( 25:24:1 ) extraction , followed by sodium acetate precipitation . SSH was carried out using the PCR Select cDNA subtraction kit ( Clontech ) according to the manufacturer's protocol . Briefly , cDNA from activated or non-activated A . caninum L3 was digested with the endonuclease Rsa I and ligated to adapters , yielding tester cDNAs for each treatment . Activated tester cDNA was denatured and allowed to re-hybridize in an excess of non-activated “driver” cDNA . This hybridization was termed the forward subtraction and enriched for cDNAs with a higher abundance in activated worms . A reverse subtraction was also performed which enriched for cDNAs which were more abundant in the non-activated worms . Also , an unsubtracted control was prepared according to the standard protocol . Hybridized cDNAs were amplified via two rounds of PCR ( according to the recommended protocol ) , purified by spin-column ( QIAGEN ) and then cloned into the plasmid vector pGEM-T ( Promega ) . Chemically competent Escherichia coli ( TOP 10 ) were transformed and grown for 8 h at 37°C in Luria Bertani medium ( LB ) with 100 µg/ml ampicillin . Stocks were stored in glycerol ( 20% ) at –80°C . Immediately prior to sequencing , 50 µl of LB ( 22°C ) was added to each E . coli stock and grown overnight on LB agar plates containing 100 µg/ml of ampicillin . Recombinant colonies were isolated by blue/white selection and then arrayed on a grided LB plate containing 100 µg/ml of ampicillin . Inserts amplified using the TempliPhi DNA Sequencing Template Amplification kit ( GE Healthcare Life Sciences ) were sequenced unidirectionally using the T7 vector primer in an ABI 3730X1 DNA analyser . The chromatograms for all raw ESTs were inspected and processed to remove poor quality sequence , with subsequent removal of contaminating vector sequences using BioEdit software v . 7 . 0 . 1 . Following this pre-processing , ESTs were organized into contigs and clusters through an iterative approach using the Cap contig assembly facility in BioEdit under strict conditions , requiring at least a 100 bp overlap and 95% identity among sequences . The resultant contigs and singletons were named according to a simple convention . A “C” in the sequence name identifies sequences composed of multiple ESTs while singletons are indicated with an “S” . Sequences from the forward-subtracted library have four digit identifiers , whereas those from the reverse-subtracted library have three digits . For example , Ac_SSH_C_0056 indicates that the SSH sequence 0056 is composed of multiple ESTs from the forward subtracted library . SSH sequences were compared with existing sequences in GenBank and Wormbase ( www . wormbase . org ) via BLASTx through NCBI ( www . ncbi . nlm . nih . gov/BLAST/ ) and WU-BLAST ( www . ebi . ac . uk/blast2 ) . Alignments were considered statistically significant if an E- or P-value was ≤1×10−5 . Neural networks and hidden Markov models were used to predict signal peptides and transmembrane domains by way of the SignalP 3 . 0 ( www . cbs . dtu . dk/services/SignalP/ ) and TMPred ( www . ch . embnet . org/software/TMPRED_form . html ) interfaces , respectively . Conserved protein motifs of activation-associated ORFs were identified using the InterProScan website ( www . ebi . ac . uk/InterProScan ) . Potential proteases were classified using the MEROPS protease database ( http://merops . sanger . ac . uk/index . htm ) . Contigs were also mapped to gene ontology ( GO ) terms based on sequence similarity using the BLAST2GO platform ( www . blast2go . de ) which compares all contigs with sequences available in several databases , including Wormbase and Uniprot [18] . Only BLASTx hits with a maximum E-value ≤1×10−10 and a minimum of 50% similarity ( default software settings ) were selected for annotation . A modified one-tailed Fisher exact test based on a hypergeometric distribution was employed in the identification of GO terms for differentially transcribed genes , which were significantly over-represented [19] . This assessment was made relative to the total number of A . caninum genes which had been GO-annotated . Setting the “false discovery” rate limit to 0 . 5 aided in controlling for multiple testing errors [18] . Sequence data for 9 , 618 A . caninum ESTs were obtained from the Washington University Genomics Department via the NCBI sequence database ( http://www . ncbi . nlm . nih . gov/Genbank/index . html ) . Chromatograms were pre-processed with the Phred software [20] , [21] and organized into contigs and clusters with the Cap3 contig assembly program [22] , employing a minimum sequence overlap length of 30 bases and an identity threshold of 95% . Contigs ( n = 1311 ) were assembled from the ESTs and are hereafter designated with “Contig” , followed by a number between 1 and 1311 . The remaining singletons were filtered by BLAST E-values ( <0 . 001 ) to remove potentially spurious sequences and are henceforth referred to by their GenBank accession number . In total , 2 , 889 individual sequences were identified from the total EST dataset for A . caninum . Sequences representing individual clusters assembled from the sequence data from the forward and reverse subtracted cDNAs as well as the publicly available repository were combined . The combined dataset ( a total of 3 , 100 representative sequences ) were submitted for the design of 60-mer oligonucleotides using eArray ( Agilent ) . A total of 9 , 288 oligonucleotides ( 3 per target ) were proposed for 3 , 096 contigs . Of these oligonucleotides , 3 , 443 possessed a non-self perfect match , resulting in 5 , 845 representing 1 , 967 genes suitable for microarray analysis . These 5 , 845 oligonucleotide probe sequences were electronically submitted using eArray for ink-jet in-situ synthesis onto glass slides by Agilent Technologies . To generate cRNA , 200 ng of total RNA extracted from each activated and non-activated L3 population of A . caninum was reverse transcribed and simultaneously labelled with Cy3 or Cy5 ( Agilent ) . Immediately prior to hybridisation , 500 ng of labelled cRNAs from each of activated and non-activated worms were quantified using a NanoDrop ND-1000 UV-VIS spectrophotometer ( NanoDrop ) , assessed for size distribution and Cy5-dye incorporation using an Agilent 2100 Bioanalyzer and RNA 6000 LabChip Kit ( Agilent ) , mixed together and fragmented . The cRNA from the combined treatments for each population was hybridised to the array in duplicate , with the second hybridisation representing a dye swap to control for any bias in signal intensity between the two dyes . Hybridisations and washes were conducted as per Agilent's Two-colour Gene Expression Hybridisation protocol version 5 . 0 . 1 . Briefly , 250 µl of hybridisation solution was applied and the microarrays were hybridised for 17 hours at 65°C , 10 rpm . Slides were then washed for 1 minute in Wash Buffer 1 ( RT ) , 1 minute in Wash Buffer 2 ( 37°C ) , 1 minute in Acetonitrile ( RT ) and 30s in Stabilisation and Drying Solution ( RT ) . Slides were scanned using a DNA Microarray Scanner ( Agilent ) . Scanning and feature extraction were performed using Feature Extraction software version 9 . 1 ( extraction protocol GE2-v4_91; Agilent ) . During extraction , signal intensities were Linear and Lowess-normalized , dye-corrected , and adjusted for local background . Data handling and analysis were carried out using the program SAS v . 8 . 0 ( SAS Institute ) . Processed signal intensities for each probe were averaged across genes , replicates and populations for comparison between treatments by a two-sided t-test with a Type I error rate of 0 . 01 . Only signals differing by at least 1 . 5 fold ( P≤0 . 01 ) for each population were considered to represent molecules differentially transcribed in A . caninum as a consequence of serum stimulation in vitro . The effects of dye and probe on the mean signal were assessed graphically . Fold changes in hybridisation were expressed as log2-transformed ratios . The absolute log2 ratios within each level-three GO category were averaged and divided by the mean absolute log2 ratio of all spots on the chip to derive an expression quotient ( EQ ) . The EQ provides an indication of the degree of differential expression associated with a specific GO term . Reverse transcription real-time PCR was used for the validation of microarray data and for studying levels of transcription in L3 at different time points during the course of serum stimulation in vitro . Ten target sequences were chosen at random and seven others were selected to represent contigs with high , medium and low levels of hybridisation in the microarray . The sequences of all of the primers used in the real-time PCR are listed in Table S2 . The single-stranded cDNA template was quantified spectrophotometrically and diluted to an appropriate concentration ( 2 ng/µl ) . Two ng of cDNA from each activated and non-activated A . caninum L3 population were subjected to PCR in the presence of 100 nM of the forward and reverse primers in 1× Platinum SYBR Green qPCR SuperMix-UDG ( Invitrogen ) . All experiments were repeated three times with two replicates in each using a Rotor-Gene 6000 Series 2-Plex real-time PCR thermal cycler ( Corbett Life Science ) employing the following cycling parameters: 50°C for 2 min , 95°C for 2 min , and 40 cycles of 95°C for 15 sec and 60°C for 30 sec . A melt curve analysis was performed from 60°C to 95°C in 1°C intervals to demonstrate the specificity of each amplicon and to identify the formation of primer dimers . Amplicons were also inspected on a 1 . 2% agarose gel and subjected to automated sequencing to prove their identity . Fold changes in transcripts between activated and non-activated L3 were normalized to the 60S acidic ribosomal protein gene ( accession number BF250585 ) [23] according to an established method [24] , [25] . The standard error of the log2 ratios was calculated from the error of the crossing points and observed reaction efficiencies propagated through the calculation of the ratio . Non-parametric statistical inference testing of log2-transformed ratios was performed using a pairwise fixed reallocation randomisation approach with 10 , 000 simulations which calculated the probability of observing ratios of randomly assigned control and treatment pairs greater than or equal to the treatment effect observed .
Approximately 120 , 000 activated and 120 , 000 non-activated L3 of A . caninum were prepared for RNA extraction . As evidenced by the ingestion of FITC-BSA , >95% of all activated L3 resumed feeding , whereas <4% of the non-activated L3 fed ( Figure 2 ) . L3 that failed to feed in the presence of the serum stimulus or those that fed in the absence of the stimulus could not be separated from each other . The RNAs from activated and non-activated L3 were extracted , processed , subjected to forward and reverse SSH and cloned into a plasmid vector . A total of 958 sequencing reactions from the forward library and 171 from the reverse library yielded high quality ESTs . The sequences were deposited in GenBank ( accession numbers ES671894–ES672870 ) and dbEST ( accession numbers 46880363 – 46881339 ) databases . Clustering of these SSH ESTs yielded totals of 242 forward subtracted and 109 reverse-subtracted contigs ( Table 1 ) . Approximately half of all forward subtracted sequences were represented by a single EST , although this figure was ∼80% for reverse subtracted sequences . The minimum and maximum lengths of the ESTs were 100 bp and 1500 bp , respectively , with the forward subtracted contigs being slightly larger ( 571 bp ) than those from the reverse subtracted contigs ( 499 bp ) . Contigs assembled from the publicly available ESTs for A . caninum had a similar size distribution compared with those assembled from the subtracted ESTs . From the SSH-derived ESTs , almost 30% of all contigs from both libraries lacked significant sequence similarity to any of the ESTs generated previously for this species [8] . Furthermore , 64–70% of the ESTs from the forward and reverse subtracted libraries respectively did not exhibit significant similarity ( at both the nucleotide and protein levels ) to sequences within the databases queried ( GenBank , EMBL and WormBase ) ( Table 2 ) . Most mRNAs identified by SSH ( 63 . 8% ) had a predicted ORF of >50 amino acids . Of these , 19% from the forward subtracted contigs had ORFs with a predicted signal sequence as compared with 6% from the reverse subtracted contigs . The differential hybridisation of forward and reverse subtracted contigs identified by SSH was verified using a custom designed oligonucleotide microarray . In order to assess the sensitivity and specificity of SSH , we clustered the entire A . caninum EST dataset ( 9 , 618 ESTs ) and submitted the union of the public ESTs and the SSH contigs for oligonucleotide design . Slides were hybridised with cRNA derived from two separate populations of hookworms ( Groups III and IV; Figure 1 ) . The number of L3 obtained from Group III was sufficient to produce two separate pools , serving as a technical replicate for RNA extraction . In total , eight separate hybridisations were performed , one for each of the three RNA samples , plus a dye swap as well as two self-hybridisations , in which Cy3 and Cy5 probes generated from the same RNA stock were used together to hybridise to the slide . For the two populations of A . caninum L3 used , the response to serum stimulation was very similar , as can be seen from the Magnitude ( M ) versus Amplitude ( A ) plots generated for each population ( Figure 3 ) . The three different oligonucleotides designed for each target yielded consistent log2 ratios among the 50 A . caninum control genes ( data not shown ) . Similar log2 ratios were also observed between arrays and dye-swaps ( Figure S1 ) . Furthermore , real-time PCR analysis , performed on 17 randomly chosen SSH-derived sequences , demonstrated the validity of the microarray data . However , the microarray consistently under-estimated the log2 ratio for highly abundant mRNAs , most likely attributable to probe saturation at both the 100% and 50% scans ( data not shown ) . The data discussed in this publication have been deposited in NCBIs Gene Expression Omnibus ( http://www . ncbi . nlm . nih . gov/geo/ ) and are accessible through GEO Series accession number GSE8155 In total , 602 mRNAs were associated with log2 transcription ratios significantly greater than zero ( P≤0 . 01 ) . A total of 103 mRNAs new to A . caninum ( not in the public databases prior to this study ) were identified by SSH , of which 79 had microarray data available . More than 60% of these mRNAs exhibited no significant similarity to any sequences other than A . caninum nor did they have any homologues/orthologues in the publicly available sequences for the congeneric hookworm , A . ceylanicum , or other strongylid nematodes . Sixty-three percent of unique genes , which were up-regulated upon serum stimulation , possessed a signal sequence , in comparison with 33% for down-regulated mRNAs ( Table 3 ) . The ten most abundant mRNAs in activated and non-activated L3 are listed in Table 4 . Cytochrome c oxidase large subunit of nuclear ribosomal RNA and two novel mRNAs were amongst the most highly expressed mRNAs in both activated and non-activated larvae , with all but the two novel mRNAs being slightly , albeit significantly ( P≤0 . 01 ) up-regulated upon stimulation . One of the most abundant mRNAs in non-activated larvae was Ac-mtp-1 , encoding a metalloprotease involved in skin penetration [26] , and this was the only molecule to also exhibit dramatic differential transcription upon stimulation ( Table 4 ) . The types of proteins encoded by mRNAs that were up-regulated upon serum stimulation are very different from those that were down regulated ( Tables 5 and 6 ) . Among the 30 most highly up-regulated mRNAs , 17 encoded members of the PRP superfamily [27] . In addition >30% of these mRNAs were predicted to encode secreted proteins . In contrast , most mRNAs that were highly down regulated upon serum stimulation did not possess signal sequences and represented a more diverse group of molecules , including two heat-shock proteins , three PRPs , several novel sequences and a cytochrome P450 . Thirteen mRNAs encoding proteases representing all four mechanistic classes , as determined from the MEROPS database [28] , were also differentially expressed following serum stimulation ( Table 7 ) . In general , the most abundantly represented group of mRNAs associated with activation was the PRPs . Sixty-one different PRP transcripts were identified among the publicly available ESTs and the SSH dataset herein . Thirty-two of these PRPs were associated with activation , 21 of which shared greater than 50% amino acid identity with at least one of the other activation-associated PRPs . All but three of the activation-associated PRPs , Ac-asp-2 ( AW626807 ) , an mRNA similar to Ac-asp-1 ( SSH Contig 017 ) , and un-clustered A . caninum EST ( BQ667555 ) , were up-regulated upon serum stimulation . Selected mRNAs were examined at different time points throughout the course of serum stimulation ( Table 8 ) . Four mRNA's were up-regulated and 4 were down-regulated within 1 hour of stimulation , then a further 80 responded to stimulation after 6–13 hours . The mRNAs that were rapidly up- or down-regulated following activation included the heat shock protein gene , hsp 12 . 6 , the cysteine protease Ac-cp1 , a metalloprotease and an mRNA similar to the Onchocerca related antigen ( ora-1 ) from C . elegans . Several PRPs , as well as the metalloprotease Ac-mtp-1 and a neuropeptide-like protein exhibited obvious differential transcription after at most 6 h . Interestingly , Ac_SSH_0042_A , one of the most highly up-regulated activation-associated PRPs , did not appear to increase in transcription until after 13 h of incubation . All activation-associated mRNAs were annotated with GO terms based on sequence similarity using the Blast2GO platform , and 3-level summaries were prepared for each aspect of GO , molecular function , biological process and cellular component ( Figure 4 ) . It is important to note that these classifications provide an estimation only of gene function , because the sequence data used are mRNAs , and often only partial sequences . Nonetheless , we identified a number of gene families that were highly upregulated in activated L3s . The GO category for catalytic activity was significantly over-represented in the mRNAs which were up-regulated upon serum stimulation . Inspection of higher-level terms in the GO tree showed that this significance was likely accounted for by the many proteases and other hydrolytic enzymes which were up-regulated during serum stimulation ( Table 7 ) . Based on the frequency of proteases encoded by the current gene/cDNA entries ( n = 48 ) for A . caninum in the NCBI databases , only three such molecules would be expected among the 66 annotated , up-regulated mRNAs . Instead , a total of seven were observed . Additionally , three of the 13 genes predicted to encode metallopeptidases were up-regulated in activated L3 . The importance of proteases in activation seems evident from Figure 4 , which shows that a majority of the up-regulated genes encode ‘protein catabolism’ functions , a sub-category of the ‘biological process’ GO category . The GO data were also analysed in the context of mRNA expression data [29] . This analysis focused on the degree to which mRNA expression within specified GO categories was greater than the global array average ( Table 9 ) . The absolute log2 ratios of genes associated with defence and the response to external stimuli were 2 . 4 to 2 . 9 times greater than the average . The log2 ratio of genes encoding proteins with a predicted extracellular localization was greater than three times the average , with this trend being reflected primarily by the PRPs and proteases . Interestingly , mRNAs associated with carbohydrate binding were more highly represented than average ( EQ = 2 . 7 ) . The largest group of annotated genes was associated with catalytic activity . Collectively , these genes had log2 ratios , which were 1 . 3 times greater than the average . However , hydrolases and lyases were largely responsible for the trend . Hydrolases ( n = 93 ) and lyases ( n = 14 ) were generally up-regulated 1 . 5 to 1 . 7 times more than the average , which was considerable given the size of those GO categories . The GO classifications can be useful for functional comparisons among species . A comparison was made between activated L3 in A . caninum and C . elegans larvae exiting from dauer . The 3-level charts ( Figure 5 ) display the distribution of GO terms specific to the category of biological process for the 30–36% of hookworm ESTs where a GO function could be assigned . While the “post-stimulation” transcriptome of both organisms was dominated by genes associated with cellular and physiological processes , it was evident that dauer exit in C . elegans was associated with a substantial increase in the proportion of genes involved in growth , development and reproduction . By comparison , serum stimulation in A . caninum did not result in an increased representation of these mRNAs . Interestingly , even the pool of annotated sequences from C . elegans dauer larvae included ( 15% ) of mRNAs associated with development . This was not the case for the ensheathed , non-activated L3 of A . caninum .
High-level GO summaries demonstrated that a large proportion ( 12% ) of differentially expressed mRNAs appear to be involved in extracellular localization , of which the majority ( 27 ) encode a group of proteins belonging to the PRP superfamily . The greater than average transcription of genes encoding PRPs highlights their importance in the transition of A . caninum from a free-living to a parasitic larva . Although the functions of these molecules are largely unknown , the identification of eight A . caninum PRP superfamily members from the excretory/secretory products of larvae [13] , [30] and adults [31]–[33] suggests involvement in host-parasite interactions . Consistent with this hypothesis is the observation that the N . americanus orthologue of Ac-ASP-2 , a major vaccine antigen from N . americanus [34] , possesses a crystal structure similar to a chemokine , suggesting that it may serve as an extracellular ligand for an unknown host receptor involved in inflammation [35] . Furthermore , Ac-NIF ( neutrophil inhibitory factor ) [33] and Ac-HPI ( platelet inhibitor ) [32] , the only two A . caninum PRPs for which in vivo functions have been proposed , both exhibit in vitro activities in the mediation of the inflammatory response . All eight of the A . caninum PRPs characterized to date are secreted proteins . Similarly , the presence of predicted signal peptides in most of the activation-associated PRPs suggests that they too are secreted . Although most of the mRNAs encoding extracellular proteins were PRPs , others encoded proteases . The importance of the activation-associated proteases was evident in the high-level GO summary of differentially expressed mRNAs ( Table 9 ) . In broad terms , catalytic activity was over-represented in mRNAs from activated L3 , with proteases largely reflecting this trend . The activation-associated proteases represented four of the major catalytic families , namely the metallo- , aspartic , cysteine and serine proteases . These proteases may serve roles in host tissue degradation , digestion and/or development . For example , the activation associated mRNA Ac_SSH_C_0180 is a likely homologue of Parelaphostrongylus tenuis cpl-1 , which encodes a cysteine protease implicated in the digestion of host tissue during the escape of the L3 from the intermediate snail host [36] . While many mRNAs encoding proteases were upregulated upon activation , a few such as those encoding the astacin-like metalloprotease , Ac-MTP-1 , were down-regulated . MTP-1 is thought to play a critical role in skin penetration in vivo [26] , thus supporting its candidacy as a vaccine antigen [37] . A similar scenario exists in larval schistosomes , where the major protease involved in tissue penetration is pre-synthesized and its mRNA is down-regulated before the cercarial stage infects the mammalian host ( reviewed in [38] ) . Proteases also serve roles in nematode development . For example , O . volvulus cathepsin Z ( Ov-cpz-1 ) is expressed in the cuticle of O . volvulus and is essential for the moult of the L3 to L4 stage [39] . Evidence suggests that the cpz-1 orthologue in C . elegans is also necessary for normal moulting and development [40] . The activation-associated A . caninum mRNA , BQ125325 , is cathepsin Z-like and could therefore fulfil a similar role in the moult of hookworm L3 to L4 . In addition to moulting , the beginning of the exit from dauer in C . elegans involves a major neurological restructuring [41] . The aspartyl protease Ce-ASP-2 plays an important role in neurodegeneration in this species [42] , and the association of a likely hookworm orthologue ( Ac_SSH_C_0068 ) with serum stimulation may also indicate a role in neurological development . Lastly , other activation-associated proteases may be involved in the digestion of host proteins for nourishment . Ac_SSH_C_0046 is 60% identical to H . contortus pepsinogen ( CAA96571 ) and necepsin I ( also referred to as Na-APR-2 ) from N . americanus ( CAC00542 . 1 ) [43] . The pepsinogen of H . contortus is expressed in the gut of the adult stage , and mRNAs have been detected in the L4 and adult stages but not in the L3 [44] . Furthermore , its ability to degrade haemoglobin indicates that it could be involved in feeding [44] . The N . americanus aspartyl proteases Na-APR-2 , Na-APR-1 and the A . caninum orthologue , Ac-APR-1 , are all expressed in the gut of the adult stage where they digest haemoglobin [45] . Mitreva et al . [8] observed that nearly 80% of the A . caninum clusters that were publicly available ( before our study here ) shared some degree of significant sequence similarity with C . elegans sequences . Moser et al . [7] compared the “serum-stimulated expression data” from many of these clusters to the 1 , 984 mRNAs associated with dauer exit in C . elegans . This was done on a gene-by-gene basis , and it was observed that cytochrome P450 , two neuropeptides , phospholipase and alcohol dehydrogenase were enriched in the dauer form of C . elegans and in non-activated L3 of A . caninum [7] . Conversely , these authors identified mRNAs representing cytochrome c oxidases , an arginine kinase , a heat shock protein , a glycerol hydrolase and glyceraldehyde 3-phosphate dehydrogenase , which were up-regulated in both nematode species following stimulation . Our findings are in accordance with these reports . Neither our study nor that of Moser et al . [7] identified major similarities between the “activated” states of C . elegans and A . caninum . This was attributed to the fact that many of the C . elegans genes which were up-regulated were under-represented in the A . caninum dataset [7] . However , even after enriching for mRNAs that are differentially expressed between free-living and activated L3 , the lack of similarity between recovered dauers and activated hookworm L3 persisted . In lieu of a gene-by-gene approach , we used species-independent GOs to assess the similarity of the relevant A . caninum and C . elegans transcriptomes . This analysis made use of the microarray data generated by [46] . This comparison demonstrated that GO annotations specific to growth , development and reproduction were highly represented in the recovered dauers of C . elegans ( Figure 5 ) . This was not the case in A . caninum and is consistent with the observation that serum-stimulation does not invoke moulting of the L3 stage [47] . Conversely , mRNAs from C . elegans dauers or larvae recovered 12 h after beginning of the exit from dauer did not exhibit the significant over-representation of extracellular products as was observed for A . caninum . This finding supports the hypothesis that many of the highly up-regulated mRNAs encoding putatively secreted products are involved in parasitism . Another major difference between “activation” in C . elegans and A . caninum is the down-regulation of several mRNAs encoding genes involved in G-protein coupled signal transduction during dauer exit in C . elegans . Such a down-regulation was not observed for A . caninum in the present study or that of [7] . As opposed to the PRPs of activated A . caninum L3 , the predominant transcripts in C . elegans 12 h after beginning the exit from dauer included a plethora of collagens , many of which were up-regulated ≥32-fold [46] . Even after enrichment for activation-associated mRNAs , only three potential collagens were identified from A . caninum and only one of these ( cuticulin ) was significantly up-regulated . Based on this information , the activation of A . caninum larvae and the exit from dauer involve considerably different mRNAs . However , the mechanisms by which these mRNAs are regulated may be similar . Ce-hsp-12 . 6 is a well-known direct target of the fork head transcription factor ( designated DAF-16 ) in C . elegans [48] . Transcripts for this gene are down regulated during dauer exit . Interestingly , it was observed that the A . caninum orthologue of hsp-12 . 6 ( contig 313 from the publicly available ESTs ) was also significantly down-regulated during serum stimulation . Assuming that the transcription of this gene is also under the direct regulation of a DAF-16 homologue , the earliest transcriptional events in the transition of A . caninum L3 to parasitism may also be regulated by DAF-16 . Real-time PCR conducted on several activation-associated mRNAs at various time points throughout the serum-activation process showed that the levels of many of these mRNAs changed rapidly , as half of those assessed achieved log2 ratios of noticeably more than zero in less than 1 h . The hsp-12 . 6 transcript was represented in this group of “early responder” molecules . Other mRNAs with similar expression profiles may also be directly regulated by DAF-16 . Interestingly , one of the most highly up-regulated PRP mRNAs did not increase substantially in transcription until 13 h after serum-stimulation , which suggests that it may be under the indirect control of DAF-16 . The SSH enrichment of activation-associated mRNAs identified 17 sequences which were up-regulated ≥4-fold and appeared to be unique to parasitic nematodes ( Table S1 ) . For example , the EST Ac_SSH_C_0056 was similar in sequence to an uncharacterised gene , ora-1 , from C . elegans which is related to an O . volvulus antigen ( Ov39 ) and is thought to play a role in the ocular pathogenesis caused by this parasite [49] . The mRNA representing Ac_SSH_S_0199 was up-regulated nearly 9-fold with the EST showing sequence similarity to the genes Hc-nim-1 and Hc-nim-2 from H . contortus . The mRNAs encoding these genes are abundant in adult H . contortus and represent almost 10% of total mRNA [50] . Hc-NIM-1 is expressed in the hypodermis of the pharyngeal region of the adult worm [50] . Lastly , SSH contigs 0099 and 0032 were among the most highly up-regulated mRNAs in activated L3 of A . caninum , with log ratios of ∼4 . 7 and 5 . 9 , respectively . Both were predicted to possess a signal peptide and appeared to be specific to A . caninum . Their apparent novelty and stage specificity suggest that they are parasite-specific molecules which might be involved in interactions with host tissues . Functional characterization of these and other novel activation-associated mRNAs may provide insights into the roles that such molecules play in the transition to parasitism . Furthermore , this information may warrant investigating their potential as targets for novel therapeutics . Having identified a suite of mRNAs associated with serum stimulation , future efforts should be focused on gaining an understanding of the biological function/s of selected members of these parasitism-associated genes . Of particular interest is the large group of PRPs that are up-regulated upon serum stimulation . In combination with their considerable stage specificity and diversity , many of these PRPs may have evolved to perform several coordinated yet distinct functions involved in the parasitic process . Given that PRP-like proteins occur in a wide range of taxa , delineating their function could potentially provide a deeper insight into their roles in parasitism as well as their broader biological significance . It is also of interest that the two most efficacious hookworm vaccine antigens , ASP-2 and APR-1 , are members of the two most represented families/groups of proteins associated with this transition to parasitism , PRPs and proteases . We believe that this bodes well for the pursuit of these new molecules identified by SSH as targets for novel vaccines and drugs . The near absence of mRNAs associated with reproduction , growth and development among activated hookworm L3 probably reflects their ability to further arrest in tissues of non-permissive hosts or in the external environment when conditions for transmission are unfavourable . Although this should not invalidate C . elegans dauer exit as a model for hookworm activation , it highlights the limitations of this free-living nematode as a model organism for the transition of nematode larvae from a free-living to a parasitic state .
|
Hookworms are soil-transmitted nematodes that parasitize hundreds of millions of people in developing countries . Here we describe the genes expressed when hookworm larvae make the transition from a developmentally arrested free-living form to a tissue-penetrating parasitic stage . Ancylostoma caninum can be “tricked” into thinking it has penetrated host skin by incubating free-living larvae in host serum – this is called “activation” . To comprehensively identify genes involved in activation , we used suppressive subtractive hybridization to clone genes that were up- or down-regulated in activated larvae , with a particular focus on up-regulated genes . The subtracted genes , as well as randomly sequenced ( non-subtracted ) genes from public databases were then printed on a microarray to further explore differential expression . We compared predicted gene functions between activated hookworms and the free-living nematode , Caenorhabditis elegans , exiting developmental arrest ( dauer ) , and found enormous differences in the types of genes expressed . Genes encoding secreted proteins involved in parasitism were over-represented in activated hookworms whereas genes involved in growth and development dominated in C . elegans exiting dauer . Our data implies that C . elegans dauer exit is not a reliable model for exit from developmental arrest of hookworm larvae . Many of these genes likely play critical roles in host-parasite interactions , and are therefore worthy of pursuit for vaccine and drug development .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/helminth",
"infections"
] |
2008
|
Transcriptional Changes in the Hookworm, Ancylostoma caninum, during the Transition from a Free-Living to a Parasitic Larva
|
The fast development of software and hardware is notably helping in closing the gap between macroscopic and microscopic data . Using a novel theoretical strategy combining molecular dynamics simulations , conformational clustering , ab-initio quantum mechanics and electronic coupling calculations , we show how computational methodologies are mature enough to provide accurate atomistic details into the mechanism of electron transfer ( ET ) processes in complex protein systems , known to be a significant challenge . We performed a quantitative study of the ET between Cytochrome c Peroxidase and its redox partner Cytochrome c . Our results confirm the ET mechanism as hole transfer ( HT ) through residues Ala194 , Ala193 , Gly192 and Trp191 of CcP . Furthermore , our findings indicate the fine evolution of the enzyme to approach an elevated turnover rate of 5 . 47×106 s−1 for the ET between Cytc and CcP through establishment of a localized bridge state in Trp191 .
Electron transfer ( ET ) is a fundamental reaction in biochemistry [1] , [2] . Its comprehensive elucidation is crucial for the understanding of biological function and the design of synthetic energy transduction systems . In this matter , the question of how intermediary medium controls the electron transfer process between two redox proteins remains an intriguing and challenging problem in biophysics and biochemistry [3]–[7] . In general , ET can be considered as a transition between two electronic states , donor ( D ) and acceptor ( A ) . Following Marcus theory , the ET rate is determined by the electronic coupling between D and A ( VDA ) , the reaction free energy ( ΔG ) and the reorganization energy ( λ ) needed to adopt the system from one state to the other: ( 1 ) Besides direct and bridge-mediated superexchange between donor and acceptor , ET can also occur through incoherent hopping including transiently populated electronic states localized on a bridge [8] . There have been many investigations on ET in enzymes [9]–[13] , with several of them on ruthenium-modified proteins [14]–[28] . In terms of the theoretical study of ET in protein , the Pathways method developed by Beratan et al . has made considerable impact in the 90's [1] , [29] , while it got replaced by the combined QM-MD approach [30]–[33] , being employed in this study . Of special interest is the ET in the Cytochrome c Peroxidase/Cytochrome c ( CcP/Cytc ) complex [9] , [34]–[39] . In its catalytic cycle , CcP undergoes a two-electron oxidation by peroxide forming an oxo-ferryl intermediate called compound I ( CpdI ) , which is then reduced by two distinct Cytc to firstly CpdII and finally the ferric resting state again ( see Figure 1 ) . The measurement of the pure ET rate ( not including the complex formation ) still bears difficulties due to instrumental dead-times . It was estimated to be greater than 2000 s−1 measured by stopped flow experiments on the ground state ET in the covalently linked complex , or rather 5 . 0×104 s−1 measured by flash photolysis methods using Ru-porphyrin photo-excited states of the noncovalent complex [38] , [40] . Pelletier and Kraut proposed a σ-bond tunneling pathway from Cytc to Trp191 following the residues Ala194 , Ala193 and Gly192 of CcP ( shown in red in Figure 2 ) , which is supported by several other studies [34] , [36] , [41] , [42] . Furthermore , it is widely accepted that CpdI oxidizes Trp191 generating the radical intermediated Trp191+ , which then is reduced by Cytc [43]–[48] . Consequently , the ET mechanism can be considered as hole transfer ( HT ) . Understanding the ET mechanism at an atomic detailed level is a crucial step towards rational enzyme engineering . In this paper we demonstrate how the evolution of computational methodologies allows today for a comprehensive study on complex protein-protein ET . Using a new theoretical strategy combining conformational sampling , a recently developed ET pathway search ( QM/MM e-Pathway ) [49] , [50] and robust ab-initio quantum mechanics electronic coupling calculations , we perform a comprehensive case study of the ground state ET between CcP and its redox partner Cytc . In addition to the identification of the ET mechanism and pathway , this study provides a computational assessment of the ET rate constant . Our analysis confirms the underlying ET mechanism to be sequential hopping , with the Trp191 radical cation as an intermediate state . This finding provides a select example of enzyme evolution by means of breaking down slow processes into several faster ones , together with a fine-tuning of the ΔG and λ differences , thereby gaining total turnover rate .
Molecular dynamics techniques have experienced a significant advancement in the recent years . Both the development of better algorithms together with the availability of a larger number of processors make it easy to run tens of nanoseconds in few days on a small local cluster ( 16–32 processors ) . Furthermore , hundreds of nanoseconds or even microseconds are becoming a possibility with the usage of GPU clusters or specialized purpose machines [51] , [52] . These long MD runs have also provided the necessary phase space exploration to further optimize the force fields [53] . For CcP/Cytc , the existence of a “rigid” engineered covalent cross-link protein-protein complex [38] , with very similar activity and structure to the non-covalent ( wild type ) complex , points to the existence of a main ET conformation . Thus , a relatively short MD around the initial crystal should provide representative conformations . Nevertheless , we run a 30 ns MD trajectory that confirmed the stability of the protein-protein complex . Additionally the ET rate results ( see below ) confirm the properness of the conformational sampling . Starting from the Pelletier and Kraut crystal structure [34] we performed 30 ns of molecular dynamics ( MD ) on the complex and extracted 10 snapshots within the first 2 ns ( based on clustering of the ET region RMSD ) for local sampling and 3 more snapshots at time steps 10 ns , 20 ns and 30 ns for nonlocal sampling . The RMSD for the heme groups as well as the superposition of all 14 conformations ( crystal structure plus 13 snapshots from MD ) is given in Figure S1 and S2 in Text S1 . The overall results indicate clearly the stability of the complex and the lack of large fluctuations in the donor , acceptor and interphase region . Following the conformational sampling , we identified the potentially important residues for the ET in each of the 14 snapshots . By using mixed quantum mechanics and molecular mechanics ( QM/MM ) techniques , it is now possible to track the electron pathway for complex biological systems . To this purpose , we developed the QM/MM e-Pathway , an iterative procedure capable of tracking the residues ( molecular orbitals ) with highest electron affinity in the transfer region ( see Figure 3 and methods section ) . In detail , the examined residues are Ala176 , Leu177 , Trp191 , Gly192 , Ala193 , Ala194 , Asn195 and Asn196 of CcP as well as Ala81 and Phe82 of Cytc , spanning the protein space between the donor and acceptor . The logo plot , given in Figure 4 , summarizes the QM/MM e-Pathway calculations on all 14 snapshots , where the size of a digit d for residue r indicates the relative frequency of residue r being identified as hole acceptor at step d of the iterative approach . The total occurrence of a specific residue can deviate from 1 . 0 because multiple residues were sometimes identified within a single QM/MM e-Pathway step and we also stopped the search after 7 steps . The results clearly indicate that Trp191 is the first hole acceptor in 10 of the 14 conformations . Thus , from the QM/MM e-Pathway analysis , one can obtain qualitative mechanistic information . In this case , for example , it indicates the possibility of having Trp191 as the localized bridge state in a two-step , sequential hopping ET mechanism . We denote a set of residues as the ET pathway for a specific snapshot , once a connecting chain of residues between the donor and acceptor is found through the stepwise application of the QM/MM e-Pathway approach ( see supporting information ) . Our calculations result in 2 distinct ET pathways for the CcP/Cytc system . The first pathway path1 consists of residues Trp191 , Gly192 , Ala193 and Ala194 of CcP , and is assigned to 10 of the 14 conformations . The second pathway path2 consists of residues Ala176 , Leu177 , Ala194 and Asn195 of CcP , and Phe82 and Ala81 of Cytc , and is assigned to 4 of the 14 conformations . Comparison of our results with published data shows that path1 is identical to the ET pathway proposed by Pelletier and Kraut and confirmed by several studies [1] , [34] , [42] . There is less evidence for path2 to be involved in the ET between Cytc and CcP , yet it was proposed by Siddarth [54] . The QM/MM e-Pathway approach only identifies important residues in the ET region in a qualitative manner . Therefore , we computed the ET rate for each possible pathway and mechanism in order to get a quantitative measure . As mentioned above , based on the QM/MM e-Pathway analysis we also investigated the hole localization on Trp191 and its role in the ET process . Thus , the following text is split into two parts: 1 ) single-step HT between Cytc and CcP and 2 ) sequential hopping HT with Trp191 as localized bridge . Our results are in agreement with experiments in both the ET mechanism as well as the ET rate constant . From the literature it is known that CpdI oxidizes Trp191 generating the radical intermediated Trp191+ , which then is reduced by Cytc [43]–[48] . Comparing our computed ET rates for the single- and two-step HT processes , it is clear that the electron hole is transferred between Cytc and CcP by sequential hopping with the intermediate state being Trp191+ . Interestingly , when comparing the couplings and rates for the two-step and one-step processes , we observe a ∼60× larger rate constant for the two-step mechanism despite of only ∼6× larger electronic coupling . The reason for this is the relation between ΔG° , λ and kET depicted in the Marcus equation , with kET being maximal when λ = −ΔG° . The direct HT from Cytc to CcP has λ - ( −ΔG° ) = 0 . 46 eV , whereas the rate-limiting HT between Trp191 and Cytc of the two-step process has λ - ( −ΔG° ) = 0 . 33 eV only , thus enabling higher rate constant at similar electronic coupling . These findings indicate the fine evolution of the enzyme to approach an increased turnover rate for the ET between CcP and Cytc through establishment of the localizable bridge state Trp191+ . We computed the rate of the ground state ET transfer between Cytc and CcP to be 5 . 47×106 s−1 . This result is in agreement with experimental ET rates to be greater than 2000 s−1 , measured using stopped-flow methods on the ground state ET [38] . Although our results furthermore agree with ET rates measured to be greater than 5 . 0×106 s−1 by flash photolysis on photo-exited ruthenium-modified Cytc [40] , these values should not be compared directly due to the different kind of ET states involved . As indicated by the coherent numbers in Table 1 ( or by the individual values for the different snapshots in the supporting information ) , the coupling and reorganization energies for the different snapshots are quite consistent . Taking into account the computed rate constant , in good agreement with the experimental values , the low fluctuations in VDA and λ , together with the small conformational changes along the MD , indicates a nongated ET mechanism . In terms of the reorganization energy , we are aware of the simplicity of our model and the importance of including protein electronic polarization into the calculations . Nevertheless , custom fit MD templates for both states RO and OR based on QM/MM optimization of the hemes plus ligated residues , as well as the rigidity of the interface and the fact that donor and acceptor are completely buried into protein and not accessible to solvent , lets us safely estimate correct reorganization energies as well as ΔG° through ΔE , as done in this study . However , the application of stated methodology to other ET systems might make specific adaptions necessary , such as more sampling or polarizable force fields to estimate λ and ΔG° . In summary , we have performed a comprehensive mechanistic case study on the ET process in the CcP/Cytc complex . It shows that the maturity of computational techniques and a novel protocol combining conformational sampling , ET pathway mapping and calculation of the key ET parameters ( ΔG° , V and λ ) , allows a detailed description of the underlying ET mechanism including the estimation of absolute rates of all relevant ET steps for this well-known system . Currently , there are efforts under way testing the approach in further systems in order to validate its general applicability . For the CcP/Cytc complex , our approach has confirmed a two-step nongated mechanism with residues Ala194 , Ala193 , Gly192 and Trp191 of CcP acting as the main ET pathway , with Trp191 serving as the transient hole acceptor at the first stage of the ET process . Most importantly , in the rate-limiting step of the two-step HT process , λ is found to be better matching -ΔG° than in the single-step HT , resulting in a much higher rate despite similar electronic coupling . This finding provides a select example of enzyme evolution by means of breaking down slow processes into several faster ones , thereby gaining total turnover rate .
All QM/MM calculations were performed with Schrodinger's QSite program [59] . The spin-unrestricted DFT method with the M06 functional [60] was applied for the QM/MM geometry optimization as well as for the analysis of ET mechanisms by using the QM/MM e-Pathway approach ( see supporting information and references ) [49] , [50] . All setups included the 6–31G* basis set for main-group elements and the lacvp pseudo-potential for Fe . The DFT methodology does not include the dispersion corrections , which could slightly affect the geometries , However these corrections do not change the electron interaction in the system and therefore have no direct impact on the electronic coupling . For our calculations , we chose the structure of the native CcP/Cytc complex derived by Pelletier and Kraut [34] . Protocols of the protein preparation , MD simulation and QM/MM energy minimization are given in the supporting information . In brief , the data of QM/MM calculations on both hemes in their reduced states were used to construct the diabatic states and derive the electronic coupling ( see below ) . The resulting conformation is referred to as the crystal complex of CpdII/CytcRED since the proteins did not undergo conformational changes throughout the equilibration process . We performed 30 ns of molecular dynamics ( MD ) on the complex , applying GROMACS [61] together with the OPLS force field . Snapshots were extracted every 1 ps within the first 2 ns and furthermore at time steps 10 ns , 20 ns and 30 ns . Based on the RMSD of the ET region , we clustered all 2000 snapshots from the 2 ns trajectory by using the k-medoids algorithm [62] and chose the 10 resulting clustering modes as representatives . In particular , the selected conformations were taken at time steps 0 , 162 , 432 , 990 , 1083 , 1356 , 1527 , 1764 , 1814 and 1884 . Together with the crystal complex and snapshots at 10 , 20 and 30 ns , our study included 14 conformations . ET pathways are identified through the recently developed QM/MM e-Pathway approach [49] , [50] , where the ET region between the donor and acceptor is described by QM and the remainder of the protein by MM level of theory . For details we refer to the supporting information . In brief , the iterative procedure starts by finding the first acceptor of the hole through localization of the spin density in the ET region , given by a single point calculation of the system having one electron missing and thus a doublet spin state . In the next iteration , the previously identified residue is excluded from the QM region , turning it into a classical residue . Therefore , an electronic description of this residue is no longer possible and the electron hole needs to find its next host . A set of residues is designated as an ET pathway , once a connecting chain of residues between the donor and acceptor is found through the stepwise application of the approach . The electronic coupling values were calculated by the FCD method [24] , [63]–[65] in combination with Koopmans' theorem [66] . Here , the properties of the adiabatic states get approximated through one-electron energies and the highest occupied molecular orbitals localized on the donor and acceptor sites in the corresponding neutral system . It is known , that DFT calculations of open-shell systems leads to artificial delocalization of the unpaired electron because of incomplete cancellation of the electron self-interaction [67] , [68] . It means that excess charge delocalization in radical cations and radical anions computed by DFT may be considerably overestimated . It was shown , however , for different functionals that the excess charge distribution is well described by Kohn-Sham orbitals of neutral dimers [69] . An alternative promising approach is the construction of the diabatic Hamiltonian using charge-localized broken-symmetry states [70] . The performance of this scheme is still not well established . In particular , it was found that calculated values of electronic couplings may be extremely sensitive to the choice of the functional [71] . Another important point is the performance of the two-state model based on a unitary transformation of adiabatic states to diabatic states . A general consideration has been revealed that the coupling derived with the two-state FCD scheme accounts properly for both the direct and bridge mediated superexchange interaction of the donor and acceptor in donor-bridge-acceptor systems [72] . All rmsV values were computed following reference [73] , applying 2 ( nearly ) degenerate states for the donor ( ND ) and acceptor ( NA ) site , respectively , and 1 for the bridge site . We note that ET from any initial state of the donor can occur to any of the NA final states of the acceptor ( NA parallel ET processes ) ; thus the rate computed with rmsV must be multiplied by NA . Alternatively , the effective electronic coupling can be defined as . We refer to direct coupling when the QM region consists solely of the donor and acceptor sites , and to bridge mediated coupling when the QM region also includes several specified bridging residues . The ET rate was calculated using Marcus expression [74] , where we estimated the driving force ΔG° as the energy change ΔE = Eproducts - Ereactants . QM geometry optimization of separated species CpdI , CpdII , CytcOx and CytcRed was performed in the gas phase as well as in the implicit solvent with the dielectric constant of 4 . 0 ( to simulate the protein environment ) . In addition , we also computed the optimal geometry of the CpdI - CytcRed ( reactant ) and CpdII - CytcOx ( product ) state using the QM/MM approach . The neglected entropy contribution of ΔG° appears to be small; we did not find significant conformational changes accompanying the ET reaction . In order to estimate the reorganization energy λ , we ran 4 ns of MD on both electronic states RO and OR of each donor-acceptor pair DA , DB and BA , respectively . We calculated the vertical energy difference ΔEET = ERO – EOR for 5 randomly chosen snapshots from the MD simulation and estimated λ using ( 2 ) where the brackets indicate averages over snapshots of MD either for the RO or the OR states , as specified by the subscripts [56] .
|
We have developed a protocol capable of describing long-range electron transfer mechanisms at an atomic detailed level . We demonstrate the maturity of the computational techniques in obtaining a quantitative view of the Cytochrome c Peroxidase/Cytochrome c electron transfer process , known to be a significant challenge . In excellent agreement with experimental data , our results allow for the description of the electron transfer pathway , its mechanism and the electron transfer rate at a quantitative level . The overall protocol is free of parameterization and can be applied to any complex electron transfer process . Furthermore , the results reveal the fine enzyme evolution of this protein-protein complex to optimize its electron transfer rate by a localized bridge state .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"protein",
"chemistry",
"computational",
"chemistry",
"quantum",
"chemistry",
"proteins",
"chemistry",
"biology",
"hemoproteins",
"biophysics"
] |
2013
|
In-silico Assessment of Protein-Protein Electron Transfer. A Case Study: Cytochrome c Peroxidase – Cytochrome c
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Among various innate immune receptor families , the role of C-type lectin receptors ( CLRs ) in lung protective immunity against Streptococcus pneumoniae ( S . pneumoniae ) is not fully defined . We here show that Mincle gene expression was induced in alveolar macrophages and neutrophils in bronchoalveolar lavage fluids of mice and patients with pneumococcal pneumonia . Moreover , S . pneumoniae directly triggered Mincle reporter cell activation in vitro via its glycolipid glucosyl-diacylglycerol ( Glc-DAG ) , which was identified as the ligand recognized by Mincle . Purified Glc-DAG triggered Mincle reporter cell activation and stimulated inflammatory cytokine release by human alveolar macrophages and alveolar macrophages from WT but not Mincle KO mice . Mincle deficiency led to increased bacterial loads and decreased survival together with strongly dysregulated cytokine responses in mice challenged with focal pneumonia inducing S . pneumoniae , all of which was normalized in Mincle KO mice reconstituted with a WT hematopoietic system . In conclusion , the Mincle-Glc-DAG axis is a hitherto unrecognized element of lung protective immunity against focal pneumonia induced by S . pneumoniae .
Streptococcus pneumoniae is the most prevalent pathogen causing community-acquired pneumonia ( CAP ) . Pneumococcal CAP frequently progresses to invasive pneumococcal disease ( IPD ) , which is associated with high morbidity and mortality rates worldwide [1–3] . Resident alveolar macrophages ( AM ) and neutrophils represent the first lines of host defense against lung-tropic bacterial pathogens , and have been characterized to express multiple pattern recognition receptors ( PRRs ) , including Toll-like receptors ( TLRs ) , NOD-like receptors ( NLRs ) , and RIG-I-like receptors , as well as C-type lectin receptors ( CLRs ) , all of which sense pathogen-associated molecular patterns ( PAMPs ) and/or danger-associated molecular patterns ( DAMPs ) . Activation of PRRs leads to production of NF-ĸB-dependent proinflammatory cytokines such as TNF-α , IL-6 , and IL-1β , followed by overlapping release of anti-inflammatory mediators , such as IL-1ra and IL-10 , which together orchestrate and shape downstream lung antibacterial immune responses by recruitment and activation/de-activation of inflammatory leukocyte subsets [3–6] . However , dysregulated pro-/anti-inflammatory cytokine responses ( ‘cytokine storms’ ) have been recognized to contribute to severe lung tissue damage , which is typically observed in severe CAP ( sCAP ) [7 , 8] . The macrophage-inducible C-type lectin receptor Mincle ( also termed Clec4e or Clecsf9 ) is a type II transmembrane C-type lectin , which is strongly induced in response to inflammatory stimuli , such as LPS , TNF-α , IL-6 or IFN-γ , and cellular stress [9 , 10] . Mincle is expressed on myeloid cells including macrophages , dendritic cells , neutrophils , but also on B cells , but not on NK cells [10–12] . In its transmembrane region , Mincle has a positively charged arginine residue [10] and is associated with an ITAM-containing adaptor molecule Fc receptor common γ chain ( FcRγ ) through charge-charge interaction to transduce activating signals into the cell [10 , 13] . Ligand binding to Mincle leads to phosphorylation of ITAM in the FcRγ chain and downstream recruitment of Syk kinase , followed by a heterotypic aggregation of Card9 with Bcl10 and Malt1 . This signaling pathway results in an adaptive Th1 and Th17 cytokine-dominated immune response and triggers production of cytokines such as TNF-α , IL-6 , MIP-2 , IFN-γ and IL-17 [13–15] . Mincle has been identified as sensor for the mycobacterial cell wall component trehalose-6 , 6’-dimycolate ( TDM , Cord Factor ) as well as its synthetic derivative trehalose-6 , 6’-dibehenate ( TDB ) [15 , 16] . Molecules with a similar structure like TDM are also reported to be Mincle ligands . For example , human Mincle recognizes glycerol monocorynomycolate derived from mycobacteria [17] . Brartemicin derived from actinomycetes binds to human and bovine Mincle [18] . Except for molecules having a similar structure with TDM , mannosyl fatty acids and β-gentiobiosyl glyceroglycolipids derived from Malassezia spp . are also reported as Mincle ligands [19] . Additionally , Mincle is induced in response to the pathogenic fungi Candida albicans as well as Malassezia spp . [19–21] . We recently demonstrated that Mincle is expressed on AM , newly recruited exudate macrophages and alveolar recruited neutrophils in response to Myocobacterium bovis ( M . bovis ) BCG infection , where it critically shaped the lung inflammatory response after mycobacterial challenge , and contributed to control of extrapulmonary M . bovis BCG infection in mice [22 , 23] . Lung infections with S . pneumoniae usually manifest as lobar pneumonia either or not progressing to invasive pneumococcal disease ( IPD ) , partially depending on the serotypes involved [24] . To mimic these different disease courses , in the current study , we used different serotypes of S . pneumoniae either causing focal pneumonia in the absence of bacteremia ( type 19F S . pneumoniae ) , or invasive serotype 3 S . pneumoniae rapidly progressing to IPD [25 , 26] . We here report that Mincle is specifically important to lung protective immunity against lobar pneumonia but not IPD .
In initial experiments , we assessed the expression of C-type lectin Mincle in WT mice infected with focal pneumonia inducing serotype 19F S . pneumoniae . As shown in Fig 1A , Mincle gene expression was found to peak in lung tissue of mice at 24 h post S . pneumoniae challenge , with a strong decline towards 72 h post-infection . Moreover , Mincle gene expression was significantly increased in alveolar macrophages and neutrophils of mice at 24 h post S . pneumoniae infection ( Fig 1B ) . Similarly , we found that neutrophils collected by bronchoalveolar lavage from the lungs of patients with confirmed pneumococcal pneumonia also exhibited significantly upregulated Mincle gene expression , relative to peripheral blood neutrophils of the same patients ( Fig 1C ) , demonstrating similar induction of Mincle gene expression in mice and humans in response to pneumococcal pneumonia . We next examined cell surface expression of Mincle on resident AM and alveolar recruited exudate macrophages ( ExMacs , S1 Fig ) and neutrophils in BAL fluids of S . pneumoniae infected WT mice . As shown in Fig 1 , we found increased Mincle cell surface expression on alveolar macrophages at 24 h post-infection , and a decline towards baseline levels by 72 h post-infection ( Fig 1E and 1H ) , relative to Mincle expression on resident AM from mock-infected mice ( D , CL in H ) . BAL fluid exudate macrophages of S . pneumoniae infected mice upregulated Mincle on their cell surface at 48 h post-challenge , with decline towards baseline levels at 72 h post-infection ( Fig 1F and 1I ) . Similarly , lung neutrophils from mock-infected WT mice demonstrated very low Mincle expression on their cell surface , which was sustained upregulated on alveolar recruited neutrophils at 24 h until 72 h post-infection ( Fig 1G and 1J ) . The next set of experiments aimed to determine whether S . pneumoniae would be recognized by Mincle through direct receptor-ligand interaction . Indeed , stimulation of NFAT-GFP reporter cells with S . pneumoniae resulted in strong reporter cell GFP fluorescence emission ( Fig 2A ) . Subsequent fractionation of pneumococcal lysates into an aqueous and organic ( chloroform:methanol , C:M ) phase and subsequent analysis of these fractions in our reporter cell assay revealed reporter cell activity only in the C:M but not aqueous fractions , implying that the putative ligand is contained in the organic phase of pneumococcal lysates ( Fig 2B ) . Subsequent fractionation of lipid extracts of S . pneumoniae by high performance liquid chromatography ( HPLC ) revealed sub-fractions triggering a strong reporter cell activation ( Fig 2C and 2D ) . We then purified these bands from sub-fractions with HPTLC . To identify the structure of these lipids , we performed electrospray ionization-mass spectrometry ( ESI-MS ) , which showed four major peaks with mass-to-charge ratios of 697 . 4875 , 725 . 5135 , 751 . 5316 , and 779 . 5608 , which gave the molecular formula C37H70 NaO10 , C39H74NaO10 , C41H76NaO10 and C43H80NaO10 ( calculated for 697 . 4861 , 725 . 5174 , 751 . 5316 , and 779 . 5644 , respectively ) ( S2A Fig ) . Composition of the glycolipid ligand was determined with GC-MS after acid hydrolysis using HCl/MeOH . The GC-MS chromatogram of FAMEs showed six FAMEs components and the major peak corresponded to methyl palmitate ( 16:0 ) ( S2B and S2C Fig ) . The GC-MS chromatogram of methanol layer after TMS derivatization showed peaks due to TMS-glycerol ( 6 . 3 min ) and TMS-glucose ( 13 . 9 and 14 . 1 min ) , respectively ( S2D Fig ) . From these data , we conclude that the ligand is glucosyl-diacylglycerol ( Glc-DAG ) , which contains various combinations of mainly C16:0 fatty acids binding to the glycerol backbone . Saturated palmitic acid was identified as the major fatty acid binding to the glycerol backbone , while various other saturated and unsaturated fatty acids were also contained in Glc-DAG ( S1 Table ) . Importantly , similar to TDM serving as prototypic Mincle ligand ( Fig 2E ) and pneumococcus-derived Glc-DAG ( Fig 2F ) , synthetic Glc-DAG ( Fig 2G and 2H ) also triggered Mincle reporter cell activation . Together , these data for the first time identify S . pneumoniae-derived Glc-DAG ( S2E Fig ) as a novel ligand of C-type lectin Mincle . We initially verified that Glc-DAG preparations were not contaminated with TLR4 ligands such as lipopolysaccharide ( LPS ) . TLR4 reporter cells responded to stimulation with LPS but not to stimulation with Glc-DAG ( S3A Fig ) . Moreover , we found that bone marrow-derived phagocytes from WT but not Myd88 KO mice responded to LPS stimulation with significantly increased TNF-α and MIP-2 cytokine release , whereas both WT and Myd88-deficient cells showed a similar TNF-α and MIP-2 cytokine release after Glc-DAG stimulation ( S3B and S3C Fig ) , collectively confirming that Glc-DAG preparations did not contain any contaminations signaling via TLR4 or Myd88-dependent pathways . We then determined the effect of Glc-DAG on cytokine liberation by freshly isolated resident AM of WT and Mincle KO mice , as well as resident AM collected from healthy human volunteers in vitro . As shown in Fig 3A and 3B , stimulation of mouse AM with Glc-DAG significantly increased proinflammatory TNF-α and anti-inflammatory IL-1ra protein release in cultures of WT but not Mincle KO macrophages , at both 24 h and 48 h post-stimulation , and a similar TNF-α and IL-1ra cytokine response was also observed in cultures of Glc-DAG stimulated human AM ( Fig 3C and 3D; 24 h post-stimulation ) . As expected , TDM representing a prototypic Mincle ligand also stimulated TNF-α release by WT but not Mincle KO alveolar macrophages , while LTA as TLR2 ligand not signaling via Mincle [19] triggered TNF-α release by both WT and Mincle KO macrophages ( Fig 3E and 3F ) . We next analyzed whether Glc-DAG purified from S . pneumoniae would directly provoke anti-bacterial respiratory burst formation in primary AM or neutrophils from WT as compared to Mincle KO mice . However , as shown in S4 Fig , Glc-DAG did not cause any burst induction in AM or neutrophils from WT or Mincle KO mice , whereas live S . pneumoniae triggered a comparable burst induction in both primary AM and neutrophils of both WT and Mincle KO mice in vitro . These data show that S . pneumoniae induced respiratory burst in AM or neutrophils is independent of the Mincle-Glc-DAG axis . We next examined survival of WT and Mincle KO mice in two infection models reflecting the main clinical phenotypes of pneumococcal lung infections , i . e . , invasive pneumococcal disease after infection with highly invasive serotype 3 S . pneumoniae , or focal pneumococcal pneumonia in the absence of bacteremia after infection with serotype 19F S . pneumoniae [25 , 27] . As shown in Fig 4A and 4B , both WT mice and Mincle KO mice similarly succumbed to IPD after infection with either 2x105 CFU/mouse ( Fig 4A ) , or 2 x 106 CFU/mouse ( Fig 4B ) of highly invasive serotype 3 S . pneumoniae , consistent with recent reports [26 , 28] . In contrast , infection of mice with focal pneumonia-inducing serotype 19F S . pneumoniae caused an overall mortality of just 10% in WT mice during an observation period of 8 days while Mincle KO mice demonstrated a significantly increased mortality of ~50% post-infection ( Fig 4C ) . Consistent with such increased mortality , Mincle KO mice demonstrated pneumococcal outgrowth in lung distal airspaces , whereas WT mice were able to purge bacteria in lung distal airspaces by day 4 post-challenge ( Fig 4D and 4E ) . Microscopic examination of lung tissue sections of mock-infected WT versus Mincle KO mice revealed normal lung architecture with regular bronchiolar and alveolar structures in either experimental group ( Fig 4F , CL ) . After type 19F S . pneumoniae infection , we observed purulent , mostly focal bronchopneumonia with accompanying organizing pneumonia in lung tissue sections of Mincle KO mice on day 3 and even more so on day 7 post-infection , which was significantly less pronounced in WT mice ( Fig 4F and 4G ) , collectively demonstrating that Mincle is particularly important to lung protective immunity against focal pneumonia-causing S . pneumoniae in mice . Based on the observation that Mincle KO mice had severe defects in purging bacterial loads in their lungs , we next examined inflammatory lung leukocyte recruitment in WT and Mincle KO mice during pneumococcal pneumonia . As shown in S5 Fig , we did not observe any significant differences in either numbers of resident AM ( S5A Fig ) , or newly recruited exudate macrophages ( S5B Fig ) , or alveolar recruited neutrophils in BAL fluids of WT versus Mincle KO mice until 72 h post-infection , except that just on day 4 post-challenge , Mincle KO mice had slightly but significantly increased neutrophil counts in their BAL fluids relative to S . pneumoniae infected WT mice ( S5C Fig ) . Collectively , these data illustrate that differences in mortality between groups were not due to differences in inflammatory lung leukocyte recruitment during pneumococcal pneumonia . Early proinflammatory and later developing anti-inflammatory cytokine responses are critical for orchestrating lung leukocyte recruitment and activation in response to lung bacterial infection . However , overwhelming ‘cytokine storms’ may be fatal for the outcome of severe bacterial pneumonia [2 , 7] . Based on differences in bacterial loads and lung histopathology between WT and Mincle KO mice , we measured pro- and anti-inflammatory cytokine release in WT and KO mice challenged with type 19F S . pneumoniae . WT mice exhibited tightly regulated waves of pro- and anti-inflammatory cytokine release peaking at 12 h-24 h with a decline to baseline levels by 96 h post-infection . In contrast , Mincle KO mice responded with a severely disturbed pro-/anti-inflammatory cytokine response with sustained increased secretion of proinflammatory cytokines TNF-α ( Fig 5A ) , KC ( Fig 5B ) , and IL-1β ( Fig 5C ) , accompanied by sustained release of anti-inflammatory cytokines IL-10 ( Fig 5D ) and IL-1ra ( Fig 5E ) during the observation period of 4 days . Moreover , Mincle KO mice responded with significantly increased alveolar macrophage necrosis to infection with type 19F S . pneumoniae , relative to control mice ( Fig 5F ) . Since Mincle KO mice had increased bacterial loads in their lungs after pneumococcal infection , we questioned whether lack of Mincle would affect macrophage or neutrophil phagocytosis and killing of S . pneumoniae in vitro . As shown in S6 Fig , resident AM and bone marrow-derived neutrophils from WT and Mincle KO mice were equally capable of phagocytosing S . pneumoniae ( 30 min value in S6A and S6B Fig ) . Similarly , the capacity of AM or neutrophils to kill intracellular bacteria at 90 and 120 minutes post-infection was comparable between groups , demonstrating that basic antibacterial features of AM and neutrophils including oxidative burst ( S4 Fig ) , phagocytosis and killing of pneumococci ( S6 Fig ) is not dependent on the presence of Mincle . Since Mincle KO mice demonstrated significantly increased bacterial loads in their lungs after infection with serotype 19F S . pneumoniae , we examined whether alveolar immigration of Mincle expressing effector cells would improve the attenuated antibacterial response in KO mice . Therefore , we reconstituted Mincle KO mice with the hematopoietic system of WT mice or Mincle KO mice serving as transplantation controls , thus allowing us to dissect the function of alveolar immigrating cells from that of alveolar residential cells in terms of lung protection against S . pneumoniae . Under baseline conditions , we found similar numbers of alveolar macrophages but no exudate macrophages or neutrophils in BAL fluids of WT onto Mincle KO mice , relative to Mincle KO onto Mincle KO mice ( CL in Fig 6A–6C ) . In response to S . pneumoniae infection , no major differences in cell counts of alveolar macrophages , newly recruited exudate macrophages and neutrophils were noted between groups , except for neutrophils that were significantly increased in BAL fluids of KO onto KO mice at 72 h post-infection ( Fig 6A–6C ) , similar to the findings made in Spn-infected Mincle KO mice ( S5C Fig ) . As expected , neutrophils represented the predominant leukocyte subset in BAL fluids of S . pneumoniae infected KO onto KO and WT onto KO mice at 24 h post-infection ( >96% ) , while only alveolar recruited neutrophils from WT onto KO , but not KO onto KO mice were found to express Mincle on their cell surface ( Fig 6D ) . Moreover , WT onto Mincle KO mice demonstrated normal purging of pneumococci in their lungs , whereas KO onto KO mice demonstrated pneumococcal outgrowth in their lungs ( Fig 6E and 6F ) , similar to Mincle KO mice infected with S . pneumoniae ( see Fig 4 ) . Moreover , just KO onto KO mice showed significantly increased pro- and anti-inflammatory cytokine liberation in their lungs by 72 h post-infection , when compared with WT onto KO mice ( Fig 6G–6K ) . Together , these results demonstrate that expression of Mincle on alveolar immigrating leukocytes , most apparently neutrophils , is a critical determinant of lung protective immunity against pneumococcal pneumonia in mice .
The current study aimed to evaluate the role of C-type lectin Mincle in lung protective immunity against pneumococcal pneumonia in mice , using a focal pneumonia-inducing type 19F strain of S . pneumoniae . We here identified Glc-DAG to be the specific ligand by which S . pneumoniae is recognized by Mincle , which is supported by the following aspects: 1 ) Glc-DAG satisfies the common signature of Mincle ligand deduced from its known crystal structure [29 , 30] , 2 ) the Glc-DAG activity is eliminated in Mincle-deficient cells , demonstrating that Glc-DAG signals exclusively via Mincle , and 3 ) the observed in vitro activity of Glc-DAG is not due to contaminations such as e . g . , endotoxin , as Glc-DAG has no activity on sensitive TLR4 reporter cells . Diacylglycerol-containing glycolipids from S . pneumoniae were previously reported to be presented by CD1d for recognition by natural killer T cells via their invariant T cell receptor [31] . Our study shows for the first time that C-type lectin Mincle expressed by professional phagocytes is another receptor of the innate immune system to recognize the pneumococcus-derived diacylglycerol-containing glycolipid Glc-DAG . In fact , Glc-DAG represents a lipid anchor moiety of the TLR2 ligand lipoteichoic acid ( LTA ) , one of the best characterized pathogen-associated molecular patterns of Gram-positive bacteria , such as S . pneumoniae and S . aureus [32 , 33] . Though LTA itself does not act as a Mincle ligand [19] , the current data show that Mincle can be activated through LTA fragments , i . e . its lipid anchor moiety Glc-DAG . These data add to our understanding how different moieties of the same ligand may be recognized by different classes of pattern recognition receptors . Most of the currently available literature on the role of Mincle in infectious diseases relates to its role in fungal and mycobacterial infections [13 , 15 , 16 , 21] , whereas relatively little knowledge exists regarding its role in bacterial infections . Recently , a protective role of Mincle in bacterial pneumonia caused by Gram-negative Klebsiella pneumoniae was reported , where lack of Mincle resulted in defective neutrophil phagocytosis of K . pneumoniae [34] . In the current model of pneumococcal pneumonia , macrophage and neutrophil phagocytosis as well as ROS production and hence oxidative intracellular killing were not dependent on the presence of Mincle . Moreover , neutrophil-dependent NET formation reported to play a role in host defense against K . pneumoniae [34] , according to previous reports , appears to be ineffective in antibacterial responses against S . pneumoniae [35] . More recent reports even demonstrate that NET formation may facilitate outgrowth of type 19F S . pneumoniae in a model of middle ear infection [36] . Based on currently available data , Mincle does not appear to induce direct effectors involved in antibacterial immunity against S . pneumoniae . Rather , we suggest that in pneumococcal pneumonia , the principal function of Mincle as ITAM-coupled receptor is to orchestrate immediate-early pro- and anti-inflammatory responses regulating lung protective immunity against pneumococci . We found that Mincle is not protective in a model of IPD , consistent with earlier reports [28] . In contrast , Mincle was indispensable for protection against focal pneumonia . The observed role for Mincle in protective immunity against focal pneumonia but not IPD is most likely due to the different pathogenicity profiles , and thus clinical disease courses , of the employed non-invasive as compared to invasive S . pneumoniae serotypes used in the current study . Since highly invasive strains of S . pneumoniae such as the currently employed serotype 3 ( A66 . 1 ) S . pneumoniae are known to cause early bacteremia and IPD in mice within 24 h [26] , lung-directed antibacterial immunity mediated by Mincle-expressing phagocytes is expected to be more effective against non-invasive as compared to invasive serotypes of S . pneumoniae rapidly escaping lung innate immune surveillance . This view is supported by our observation in chimeric Mincle KO mice ( carrying the hematopoietic system of WT mice ) that were found to recruit Mincle-expressing neutrophils to the alveolar air space in response to pneumococcal infection , which was sufficient to normalize antibacterial and cytokine responses after pneumococcal challenge . These data demonstrate a critical role for Mincle expressing leukocytes , most apparently neutrophils , to contribute to regulation of protective immunity against focal pneumonia-causing S . pneumoniae . Collectively , the current study provides novel informations about lung phagocyte recognition of S . pneumoniae by C-type lectin receptor Mincle , which critically contributes to lung protective immunity against this serious lung pathogen . The study may be relevant to the development of novel interventions to enhance lung phagocytic responses against this prototypic lung pathogen in a CLR specific manner .
WT C57BL/6J mice were purchased from Charles River ( Sulzfeld , Germany ) . Mincle KO mice on a C57BL/6J background were generated as previously described [21] and were obtained from the Consortium for Functional Glycomics ( CFG ) . Myd88-deficient mice on a C57BL6/J background were generated as described previously [37] . Sex- and age-matched mice ( 8–12 weeks of age ) were used for experiments . Animals were handled according to institutional guidelines of the Central Animal Facility of Hannover School of Medicine . All animal experiments were approved by the Lower Saxony State Office for Consumer Protection and Food Safety . Rat monoclonal anti-murine Mincle antibody ( clone 4A9 , IgG1κ ) specifically recognizing Mincle but not MCL was generated as recently described [13] . Respective purified rat IgG1κ isotype control ( clone R3-34 ) was purchased from BD Biosciences ( Heidelberg , Germany ) . Anti-CD11b PE-Cy7 ( clone M1/70 ) , anti-Ly6G PE ( clone 1A8 ) , anti-MHC class II PE ( clone 1G9 ) , biotinylated IgG1 ( clone RG11/39 . 4 ) , allophycocyanin ( APC ) -labeled Annexin V , APC-labeled streptavidin , and propidium iodide ( PI ) were all obtained from BD Biosciences ( Heidelberg , Germany ) . Anti-F4/80 FITC and anti-F4/80 APC ( clone CI:A3-1 ) were obtained from Serotec ( Düsseldorf , Germany ) . Anti-CD11c PE-Cy5 . 5 ( clone N418 ) was purchased from Invitrogen ( Darmstadt , Germany ) . Serotype 19F and serotype 3 S . pneumoniae were grown in Todd-Hewitt broth ( Oxoid , Basingstoke , UK ) enriched with 20% FCS ( Biochrom , Berlin , Germany ) to mid-log phase . Quantification of pneumococci was done by plating ten-fold serial dilutions on sheep blood agar plates ( BD Biosciences , Heidelberg , Germany ) followed by incubation at 37°C , 5% CO2 for 18 h and subsequent determination of CFU , as described [27 , 38 , 39] . For lipid extraction , bacteria were centrifuged at 2 , 400 g for 20 min . Lipids were extracted from bacterial pellets with chloroform-methanol-water ( C:M:W , 6:3:1 , v/v/v ) overnight , and the C:M layer was collected after centrifugation . After drying up in an N2 evaporator , lipids were reconstituted in C:M ( 2:1 , v/v ) and resolved by HPLC column ( Inertsil SIL-100A , 5 μm , 7 . 6 x 250 mm; GL Science ) with C:M ( 9:1 , v/v ) . Each sample fractionated with HPLC was dried up and dissolved with C:M ( 2:1 , v/v ) . After HPLC , fractions were analyzed on high-performance thin-layer chromatography ( HPTLC ) plates ( Silica gel 60; Merck ) with C:M ( 9:1 , v/v ) . Copper acetate was used for visualization of lipids . Those fractions providing GFP signals in NFAT-GFP reporter cell assays were further separated by scratching plates after TLC . Scratched lipids were extracted with C:M ( 2:1 , v/v ) again . Extracted Mincle ligand was subsequently analyzed with electrospray ionization time-of-flight mass spectrometry ( ESI-TOF-MS ) using a MicrOTOF II ( Bruker Daltonics Inc . , MA , USA ) . Glc-DAG was heated with 50 μl of 10% HCl/MeOH in a sealed tube at 80°C for 3 h . The reaction mixture was diluted with 0 . 5 ml of MeOH and extracted with n-hexane , and the n-hexane extract was concentrated in vacuo to give a mixture of fatty acid methylesters ( FAMEs ) . The FAMEs were dissolved in acetone and subjected to gas chromatography-mass spectrometry ( GC-MS ) using a Shimadzu QP-5050A ( Kyoto , Japan ) equipped with a TC-1701 capillary column ( GL science , Tokyo , Japan ) . The remaining MeOH layer was neutralized with Ag2CO3 , and filtrated . The filtrate was dried in vacuo and then dissolved in 25 μl of pyridine , followed by addition of 25 μl of 1- ( trimethylsilyl ) imidazole . The reaction mixture was heated at 60°C for 20 min , and the TMS ether of glycoside was analyzed by GC-MS . Synthesis of alpha-glucosyl-dimyristylglycerol ( C14:0 ) and alpha-glucosyl-distearylglycerol ( C18:0 ) was performed through the adaptation of literature reported methods [40 , 41] . 2B4-NFAT-GFP reporter cells expressing FcRγ only , or co-expressing FcRγ and Mincle were prepared as previously described [13] . Aliquots of lipid fractions ( prepared as stock solutions in C:M ( 2:1 ) at 1 mg/ml ) of S . pneumoniae were diluted in isopropanol and were then added to 96-well plates at various concentrations , followed by evaporation under a laminar flow hood . Subsequently , NFAT-GFP reporter cells were added to the wells ( 4 x 104 cells/well ) , then incubated for 18 hours , and NFAT-GFP reporter transgene activity was determined by flow cytometry [13 , 16 , 22] . For TLR4 reporter cell assay , see online supplement . To elucidate the effect of highly purified pneumococcal Glc-DAG as compared to TDM or LTA on macrophage cytokine responses , 96-well plates were coated with Glc-DAG or TDM ligand ( diluted in isopropanol ) at 5 μg per well ( TDM , 1 μg/well ) followed by incubation of the plates at room temperature under a laminar flow hood until the solvent was completely evaporated . Then , 7 . 5 x 104 murine or human AM were added and incubated for 24 h or 48 h , as indicated . Stimulation of murine alveolar macrophages with LTA ( dissolved in sterile water ) was done at 1 μg/ml for 24 h . Subsequently , proinflammatory cytokine release was measured in cell-free culture supernatants by enzyme-linked immunosorbent assay ( ELISA ) . WT and Mincle KO mice were anesthetized with xylazine ( 5 mg/kg of body weight ) ( Bayer , Leverkusen , Germany ) and ketamine ( 75 mg/kg ) ( Albrecht , Aulendorf , Germany ) and then intubated orotracheally ( o . t . ) with a 29-gauge Abbocath catheter ( Abbott , Wiesbaden , Germany ) as described recently [42 , 43] . Subsequently , mice were o . t . infected with either highly invasive serotype 3 ( A66 . 1 ) , or focal pneumonia-causing serotype 19F ( EF3030 ) S . pneumoniae or mock-infected in a volume of 50 μl PBS , as indicated . After infection , mice were returned to their cages and monitored daily for disease symptoms . Survival of S . pneumoniae-infected mice was recorded daily for 6 ( serotype 3 S . pneumoniae ) or 8 days ( serotype 19F S . pneumoniae ) . Bronchoalveolar lavage of mice was performed as outlined recently [23 , 27 , 42] and in the online supplement . Healthy volunteers and patients with severe pneumococcal pneumonia ( n = 3 each ) requiring mechanical ventilation underwent standard BAL procedure as previously described [44] . The diagnostic criteria for severe PN were characteristic chest X-rays , fever , dyspnea , and microbiological identification of pathogens in the lower respiratory tract as well as positive pneumococcal urinary antigen test ( PUAT ) . Briefly , fiber-optic bronchoscopy was performed , and 20 ml aliquots of sterile saline were instilled into a subsegmental bronchus of the middle lobe or the lingula and aspirated by gentle suction . The recovered lavage samples were filtered through sterile gauze to remove mucus and immediately placed on ice . BAL fluid neutrophils comprised > 97% of total BAL fluid cells in pneumococcal pneumonia patients , while in healthy volunteers , resident alveolar macrophages comprised the majority of cellular constituents in BAL fluids ( >95% ) , as analyzed by microscopic examination of Pappenheim-stained cytospin preparations . For isolation of peripheral blood neutrophils , heparinized peripheral blood ( 20 ml ) was collected from patients with pneumococcal pneumonia and subjected to Ficoll-based density gradient centrifugation , resulting in purities of peripheral blood neutrophils of >95% , as previously described [45] . Written informed consent was received from healthy volunteers and patients with pneumococcal pneumonia or their closest relatives prior to BAL . Bacterial loads were determined as outlined elsewhere [27] and in the online supplement . FACS analysis of Mincle expression on the various leukocyte subsets was performed as outlined recently [22 , 23] , and described in the online supplement . Analysis of apoptosis/necrosis induction in AM collected from WT and Mincle KO mice infected with serotype 19F S . pneumoniae was done as described recently [27 , 46] , and in the online supplement . Phagocytosis and bacterial killing were analyzed as described recently [27 , 46] . Briefly , alveolar macrophages recovered by BAL from untreated WT and Mincle KO mice were seeded at 2 x 105 cells per well into cell culture plates . After adherence ( 30 min . ) , AM were washed and infected with S . pneumoniae at MOI 50 for 30 min . in RPMI/10% FCS/1% glutamine at 37°C/5% CO2 . Neutrophils were purified from bone marrow cells of WT and Mincle KO mice [22] and were infected with S . pneumoniae at MOI 50 in polypropylene tubes for 30 min . in RPMI/10% FCS/1% glutamine at 37°C/5% CO2 . Subsequently , non-phagocytosed bacteria were removed by three washing steps , and residual extracellular pneumococci were killed by short incubation ( 10 min . ) in RPMI/10% FCS/1% glutamine/20 μg/ml gentamicin ( Sigma , Deisenhofen , Germany ) , after which neutrophils were seeded at 2 x 105 cells per well into cell culture plates . After 30 min . of infection , cells were either lysed for determination of pneumococcal uptake , or were incubated for another 60 and 90 min . followed by cell lysis in 0 . 1% saponin in HBSS to release intracellular pneumococci and determination of CFU by plating ten-fold serial dilutions of cell lysates on sheep blood agar plates and subsequent incubation of plates at 37°C/5% CO2 for 18 h . 96 well plates were coated with vehicle ( isopropanol ) or Glc-DAG ( 5 μg/well in isopropanol ) followed by evaporation of the solvent . AM were harvested from the lungs of WT and Mincle KO mice by BAL . Bone marrow-derived neutrophils were purified according to recently published protocols [22] . Resident AM and neutrophils were added to Glc-DAG coated wells at 7 . 5x104 cells/well . After addition of 2 mM luminol ( Sigma , Deisenhofen , Germany ) , burst induction was analyzed at 37°C after 3 h of AM or neutrophil exposure to vehicle , or Glc-DAG and is expressed as relative light units ( RLU ) using a luminescence reader ( BioTec Instruments , Bad Friedrichshall , Germany , KC4 software ) . As a positive control , AM and neutrophils were exposed to S . pneumoniae ( Spn , MOI 5 ) , and RLU were measured 3 h later . Mincle gene expression was determined in lung tissue or flow-sorted AM and neutrophils purified from the lungs of mice by high-speed cell sorting ( BD FACSAria II , BD Biosciences , Heidelberg , Germany ) , as recently described [23 , 27 , 42] , or in BAL fluid neutrophils from patients with pneumococcal pneumonia . For further details , see online supplement . See online supplement . Lung histopathology was assessed as described in the online supplement . All data are given as mean ± SD and were analyzed using GraphPad Prism Software . Differences between treatment groups were analyzed by Mann-Whitney U test . Survival curves were compared by log-rank test . Unpaired t-test was used to determine differences between Glc-DAG treated and vehicle treated cells in vitro . Statistically significant differences between treatment groups were assumed when P values were < 0 . 05 . Animal experiments were approved by the Lower Saxony State Office for Consumer Protection and Food Safety ( LAVES ) ( permission numbers 13/1063 and 15/1743 ) , and followed the European Council Directive 2010/63/EU as well as the German Animal Welfare Act .
At indicated time points , S . pneumoniae-infected WT and Mincle KO mice were euthanized with an overdose of isoflurane ( Baxter , Unterschleissheim , Germany ) and subjected to bronchoalveolar lavage . Briefly , the trachea was cannulated with a shortened 20-gauge needle and 300 μl aliquots of cold PBS ( Biochrom ) supplemented with EDTA ( Versen , Biochrom , Berlin , Germany ) were instilled , followed by careful aspiration , until a volume of 1 . 5 ml was collected . BAL was then continued until an additional BAL fluid ( BALF ) volume of 4 . 5 ml was obtained . BAL fluids were centrifuged at 1 , 400 rpm at 4°C for 9 min and cell pellets were resuspended in RPMI 1640 supplemented with 10% FCS and total cell numbers of BAL fluid leukocytes were determined . BAL fluid leukocyte subsets were differentiated on Pappenheim-stained cytospin preparations based on overall morphological criteria , including cell size and shape of nuclei , and were then quantified by multiplication of respective percent values with total BAL cell counts . After BAL was performed , individual lung lobes were removed and dissected into small pieces , and were then homogenized in 2 ml of HBSS using a tissue homogenizer ( IKA , Staufen , Germany ) . Lung tissue homogenates were then filtered through a 100 μm cell strainer ( BD Bioscience , Heidelberg , Germany ) . Bacterial loads in BAL fluids and lung tissue homogenates were determined by plating ten-fold serial dilutions of lung tissue homogenates on sheep blood agar plates , followed by incubation at 37°C/5% CO2 for 18 h and subsequent determination of total CFU counts . Mincle KO mice received whole body irradiation ( 8 Gy ) , followed by transplantation with bone marrow cells ( 107 cells/mouse i . v . ) from either WT mice , or Mincle KO mice serving as transplantation controls . Seven weeks later , mice were infected orotracheally with 1x107 CFU/mouse of type 19 S . pneumoniae , followed by determination of bacterial loads in BAL fluids and lung tissue of mice . In selected experiments , Mincle expression was analyzed on the cell surface of neutrophils contained in bronchoalveolar lavage fluid from S . pneumoniae-infected ( 24 h ) chimeric Mincle KO mice reconstituted with the hematopoietic system of WT or Mincle KO mice . In selected experiments , we verified that Mincle deficiency did not impact on hematopoietic engraftment efficacy in chimeric WT ( CD45 . 1pos ) onto Mincle KO mice , and in chimeric Mincle KO ( CD45 . 2pos ) onto WT ( CD45 . 1pos ) mice at 6 weeks post-transplantation , which was always found to be >90% . Lungs were perfused in situ via the right ventricle with HBSS . Then , lung lobes were collected , teased into small pieces and digested in RPMI/collagenase A ( 5 mg/ml ) and DNase I ( 1 mg/ml ) ( Roche , IN ) for 90 min at 37°C . Tissue digestion was stopped by addition of RPMI/10% FCS , followed by filtration of digested lung tissue through 40 μm cell strainers ( BD Falcon ) . CD11c-positive lung leukocyte subsets were enriched by magnetic cell purification ( Miltenyi , Bergisch Gladbach , Germany ) . Aliquots of lung tissue digests were employed for analysis of Mincle expression on lung neutrophils . BAL and lung leukocyte subsets were immunophenotyped as described in detail recently [27 , 46 , 47] . Briefly , after pre-incubation with Octagam ( Octapharma , Langenfeld , Germany ) , 2–5 x 105 cells were incubated with fluorochrome-labeled mAbs with specificity for F4/80 , CD11b , CD11c , Ly6G , and MHC II for 20 min . at 4°C . Subsequently , cells were washed twice with FACS buffer and subjected to FACS analysis of their cell surface antigen ( Ag ) expression profiles . Resident AM contained in BAL fluids were characterized according to their green autofluorescence and F4/80pos , CD11bneg , CD11cpos antigen expression profile , and green autofluorescent , inflammatory recruited alveolar ‘exudate’ macrophages ( ExMacs ) were characterized by their F4/80pos , CD11bpos , CD11cpos Ag expression profile ( see S1 Fig ) . Note that gating of alveolar recruited exudate macrophages at 24 h post-infection may to a small extent ( 5–10% ) include inflammatory activated resident alveolar macrophages , according to previous reports [48] . Neutrophils in BAL and lung tissue of WT and chimeric mice were characterized according to their CD11cneg , CD11bpos , Ly6Gpos antigen expression profile . Subsequently , appropriately gated resident AM and ExMacs in BAL fluids , as well as lung and BAL neutrophils were analyzed for their respective Mincle cell surface expression profiles using anti-Mincle Ab clone 4A9 . Analysis of apoptosis/necrosis induction in AM collected from WT and Mincle KO mice after infection with serotype 19 S . pneumoniae was done by incubating BAL cells with APC-labeled annexin V ( apoptosis marker ) in the presence of propidium iodide for 15 min at room temperature according to the manufacturer’s instructions ( BD Biosciences ) , followed by FACS-based determination of annexin Vneg/propidium iodidepos necrotic macrophages in the fraction of F4/80-positive AM . Total RNA from lung tissue or cell specimen was isolated using RNeasy Micro kit ( Qiagen , Hilden , Germany ) , following the manufacturer’s instructions . For cDNA synthesis , 100 ng of purified total cellular RNA was reverse transcribed and quantitative real-time RT-PCR was performed on an ABI 7300 real-time PCR System ( Applied Biosystems , Warrington , United Kingdom ) using SYBR Green dye ( Eurogentec , Seraing , Belgium ) , as recently described . Murine Mincle specific primers were forward primer 5’-‘TCAACCAAATCGCCTGCAT-3’ , and reverse primer 5’-GAGGCCCCGGCTATCGT-3‘ . Primers were designed using Primer Express software ( Applied Biosystems , Warrington , UK ) , based on the gene sequence data retrieved from GenBank . For normalization , murine β-actin ( forward primer , 5’-CCACAGCTGAGAGGGAAATC-3’ , and reverse primer 5’-TCTCCAGGGAGGAAGAGG AT-3’ ) was used as the housekeeping gene . Human Mincle specific primers were forward 5’-CATTTCGCATCTTTCAAACCTGTG-3’ , and reverse 5’ ATTCCCAGTTCAATGGA CAACAATT-3’ . Human β-actin specific primers were forward 5’-GCCA CGGC TGC TTCCA-3’ and reverse 5’-GAACCGCTCATTGCCATTG-3’ . Mean fold changes were calculated using the 2-ΔΔCt method [49] . WT and Mincle KO mice were euthanized and non-lavaged lungs were inflated in situ with PBS-buffered formaldehyde solution ( 4 . 5% , pH 7 , Roth , Deisenhofen , Germany ) , and were then removed en bloc and fixed in PBS-buffered formaldehyde solution at room temperature for at least 24 h . Following automated dehydration , routine paraffin embedding , lung tissue sections ( 3 μm ) were prepared and then stained with hematoxylin/eosin ( HE ) . Subsequently , the percentage of inflamed lung tissue from each lung lobe of the left and right lung per mouse was determined in S . pneumoniae-infected WT and Mincle KO mice as mean values of affected lung tissue using a Zeiss Axiovert 200 M microscope ( Carl Zeiss , Wetzlar , Germany ) . Lung histology assessment was performed under blinded conditions . To exclude that Glc-DAG contained any lipopolysaccharide ( LPS ) or other contaminants signaling via TLR4 or Myd88 , control experiments were performed in TLR4 reporter cells and bone marrow-derived phagocytes from WT and Myd88 KO mice . HEK-Blue mTLR4 reporter cells and TLR4 deficient HEK-Blue Null1-v cells ( both InvivoGen ) were employed to exclude any TLR4 ligand activity in our Glc-DAG preparations , while bone marrow-derived phagocytes from WT and Myd88-deficient mice generated as recently described [22] were used to exclude any contaminations in Glc-DAG preparations signaling via Myd88-dependent pathways . Lipopolysaccharide ( LPS , L4516 derived from Escherichia coli 0127:B8 , Sigma ) serving as prototypical TLR4 ligand was used as positive control . HEK-blue cells stably express secreted embryonic alkaline phosphatase ( SEAP ) gene inducible by NF-κB . Cells were seeded in a 96-well plate ( 3x104 cells/well in 100 μl ) with or without stimulants ( LPS at 0 . 1 ng/ml or Glc-DAG at 5 μg per well ) and were then incubated overnight . Medium samples ( 5 μL ) were then mixed with QUANTI-Blue ( InvivoGen ) medium ( 45 μL ) and incubated at 37°C for 3 hours . Levels of SEAP in the medium were determined by measurement of OD values at 630 nm using a Multiskan microplate reader ( Thermo ) . Pro- and anti-inflammatory cytokines were measured using commercially available ELISA kits for TNF-α ( detection limit: 11 pg/ml ) , IL1-β ( detection limit: 12 pg/ml ) , KC ( 6 pg/ml ) , IL-10 ( detection limit: 16 pg/ml ) , or IL-1ra ( 32 pg/ml ) , according to the manufacturer’s instructions ( R&D Systems , Wiesbaden , Germany ) .
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Bacterial infections of the lung cause significant morbidity and mortality worldwide . The Gram-positive bacterium Streptococcus pneumoniae is the most prevalent pathogen causing bacterial lung infections in humans . Among the various innate immune receptors by which lung sentinel cells are able to sense bacterial invasion of the lung , relatively little knowledge exists regarding the role of C-type lectins in the process of bacterial recognition by the immune system . In this report , we show that S . pneumoniae is recognized by the C-type lectin receptor Mincle , which is a receptor specialized to bind pathogen-derived carbohydrate structures . In the current study , we identify a specific glycolipid of S . pneumoniae by which the bacterium is recognized by lung sentinel cells . Moreover , we show the critical importance of the described receptor-ligand interaction for survival of pneumococcal pneumonia in mice . Collectively , we identify the Mincle-Glc-DAG axis as an important element of lung host defense against focal pneumococcal pneumonia .
|
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2016
|
C-type Lectin Mincle Recognizes Glucosyl-diacylglycerol of Streptococcus pneumoniae and Plays a Protective Role in Pneumococcal Pneumonia
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To date , most molecular investigations of schistosomatids have focused principally on blood flukes ( schistosomes ) of humans . Despite the clinical importance of cercarial dermatitis in humans caused by Trichobilharzia regenti and the serious neuropathologic disease that this parasite causes in its permissive avian hosts and accidental mammalian hosts , almost nothing is known about the molecular aspects of how this fluke invades its hosts , migrates in host tissues and how it interacts with its hosts’ immune system . Here , we explored selected aspects using a transcriptomic-bioinformatic approach . To do this , we sequenced , assembled and annotated the transcriptome representing two consecutive life stages ( cercariae and schistosomula ) of T . regenti involved in the first phases of infection of the avian host . We identified key biological and metabolic pathways specific to each of these two developmental stages and also undertook comparative analyses using data available for taxonomically related blood flukes of the genus Schistosoma . Detailed comparative analyses revealed the unique involvement of carbohydrate metabolism , translation and amino acid metabolism , and calcium in T . regenti cercariae during their invasion and in growth and development , as well as the roles of cell adhesion molecules , microaerobic metabolism ( citrate cycle and oxidative phosphorylation ) , peptidases ( cathepsins ) and other histolytic and lysozomal proteins in schistosomula during their particular migration in neural tissues of the avian host . In conclusion , the present transcriptomic exploration provides new and significant insights into the molecular biology of T . regenti , which should underpin future genomic and proteomic investigations of T . regenti and , importantly , provides a useful starting point for a range of comparative studies of schistosomatids and other trematodes .
The bird fluke Trichobilharzia regenti is a member of the Schistosomatidae ( = blood flukes; Class Trematoda ) , a family of parasitic flatworms of medical and veterinary importance [1 , 2] . T . regenti is widely distributed geographically and is highly prevalent , for instance , in parts of Europe ( including Russia ) , New Zealand and Iran [3–6] . Like blood flukes of the genus Schistosoma , T . regenti is dioecious , has a two-host life cycle ( including a lymnaeid snail of the genus Radix ) and has an invasive furcocercarial stage that actively penetrates the skin of a definitive vertebrate host . Unlike members of the genus Schistosoma , T . regenti invades and migrates through skin and nerves to then establish within the nasal mucosa [7–9] . During its aquatic phase , T . regenti can accidently penetrate human skin and cause cercarial dermatitis . Cercarial dermatitis , caused by avian schistosomes , is regarded as an emerging disease [10–12] although global economic losses are not known , it is accepted that this condition can have a considerable impact on local , tourism-based economies , and may also represent a debilitating occupational disease of rice farmers ( see Horák et al . , 2015 for review [12] ) . As avian ( including T . regenti ) and human schistosomes can occur in the same water reservoirs , there are at least two issues of relevance in relation to the differential diagnosis of disease: ( a ) Based on clinical signs , cercarial dermatitis caused by avian schistosomes can be confused with that caused by human schistosomes [13] . ( b ) Prevalence surveys of hepatointestinal or urogenital schistosomiasis of humans might be influenced/affected by serological cross-reactivity resulting from exposure to cercariae of avian schistosomes [14] . To better understand T . regenti and the diseases that this parasite causes , considerable research has focused on exploring its life cycle . Once shed from the intermediate aquatic snail host , the cercariae survive only for a limited time in water ( 1 to 1 . 5 days in related avian schistosomes [15] , consuming their glycogen reserves acquired from the intermediate host [16] . Upon contact with the skin of the definitive host , the cercariae release secretions containing proteolytic enzymes ( peptidases ) from their circumacetabular and postacetabular penetration glands [17] , which enable tissue penetration [18–20] . During penetration , the cercariae transform to schistosomula within ~ 12 h [9 , 21]; for schistosomes , this process is accompanied by a loss of their tail , formation of a double ( heptalaminar ) membrane covering the tegument and a reduction of surface glycocalyx [21 , 22] as well as a switch from aerobic to anaerobic metabolism , depending on the amount of accessible glucose [23 , 24] and the activation of metabolic processes in the parasite’s gut [25] . In contrast to human schistosomes , T . regenti schistosomula do not migrate directly to blood vessels , but rather enter peripheral nerves , and migrate to the spinal cord and brain of the host , during which they feed on neural tissue [8 , 26] . Having reached the pre-adult stage in the meninges , the schistosomula start to feed on blood and then migrate into the nasal cavity , likely via an intravascular route [27] . The significant damage to nerve tissue caused by migrating schistosomula can lead to behavioural changes , disorientation , paralysis or even death in some hosts [7 , 28] . Despite the importance of cercarial dermatitis in humans caused by T . regenti and the unique neuropathogenic effects of this parasite on its permissive avian hosts as well as experimental rodent hosts , little is known about the molecular mechanisms underlying tissue penetration , transformation of cercariae to schistosomula , tissue invasion and parasite-host interactions . Here , we propose that exploring the developmental transcriptomes of cercaria and schistosomulum of T . regenti will provide vital insights into the fundamental molecular biology of this parasite , and identify essential pathways and protein classes linked to early tissue invasion . An analysis of the developmental transcriptome of T . regenti should also fill gaps in our knowledge of the parasite’s biology , as , to date , major molecular investigations have focused mainly on human blood flukes . Therefore , in the present study , we ( i ) assembled and annotated the transcriptome of two consecutive life stages of T . regenti involved in the first phases of infection of the avian host , ( ii ) identified key biological and metabolic pathways specific to each of these two developmental stages , and ( iii ) undertook comparative analyses using data available for taxonomically related blood flukes of the genus Schistosoma .
The maintenance and care of experimental animals was carried out in accordance with the European Directive 2010/63/EU and Czech law ( 246/1992 and 359/2012 ) for biomedical research involving animals . Experiments have been performed under legal consent of the Expert Commission of the Section of Biology , Faculty of Science , Charles University in Prague and the Ministry of Education , Youth and Sports of the Czech Republic ( ref . no . MSMT-31114/2013-9 ) . Trichobilharzia regenti was maintained in snail intermediate ( Radix lagotis ) and definitive ( Anas platyrhynchos f . domestica; breed—Cherry Valley strain ) hosts in the Laboratory of Helminthology , Faculty of Science , Charles University in Prague , using an established protocol [1] . Four separate groups of infected snails ( n = 20 snails per group ) , each representing a distinct biological replicate , were established to obtain four independent biological replicates of pooled cercarial and schistosomula samples ( Fig 1 ) . Schistosomulum replicates: Upon light stimulation for 2 h , cercariae ( mixed-gender ) shed from each snail group were collected and used to infect seven-day old ducks ( n = 4 replicates; 2 , 500 cercariae per duck ) . Pooled schistosomula were collected from the spinal cord of each infected duckling seven days following inoculation using established methods [7 , 28] . Briefly , the spinal cord was carefully prised apart manually ( using dissection needles ) in phosphate-buffered saline ( PBS ) and exposed to bright light for 1 h . Schistosomula ( n = 4 replicates; 150 to 400 individuals per duckling ) were collected , washed extensively in PBS and stored in TRIzol reagent ( Invitrogen ) at -80°C until further processing . For each biological replicate , a sample of cercariae ( shed from the same snail group used to infect the ducks ) was also collected for RNA isolation . Cercaria replicates: Cercariae were collected every second day for one week , with each batch washed twice in tap water , centrifuged at 2 , 500 ×g at 4°C , and then stored in TRIzol reagent ( Invitrogen ) at -80°C . Total RNA was purified from individual biological replicates ( four for both cercariae and schistosomula ) using TRIzol , and residual genomic DNA removed ( DNA-free kit , Invitrogen ) following the manufacturer’s instructions . The integrity and quality of total RNA were determined using a Bioanalyzer 2100 ( Agilent ) and Qubit RNA BR assay kit ( Invitrogen ) . Messenger RNA ( mRNA ) was purified , and short-insert ( 330 bp ) complementary DNA ( cDNA ) libraries constructed and barcoded according to the manufacturer’s instructions ( TruSeq RNA Sample Preparation v . 2 , Illumina ) . All cDNA library was paired-end sequenced ( 2 × 211 base reads ) on a single line using the HiSeq 2500 platform ( Illumina ) . Sequencing adaptors and nucleotides with a Phred quality score of < 20 were removed using Trimmomatic v . 0 . 3 [29] . The quality of filtered paired-end read data was manually assessed using FastQC [30] For each RNA-seq dataset , reads were corrected using Spades v . 3 . 1 . 0 [31] and normalized digitally using the program khmer v . 1 . 1 [32] . For each of the cercarial and schistosomula RNA-seq data sets , replicate datasets were pooled and used to assemble non-redundant transcriptomes using Oases v . 0 . 2 . 8 [33] , employing coverage cut-offs of 13 and 14 , and k-mer values of 47 and 49 , respectively . A final , merged transcriptome was generated by concatenating cercarial and schistosomula transcriptomes , and removing redundancy using CD-HIT-EST [34] using a nucleotide sequence identity threshold of 85% . Finally , coding domains were predicted using Transdecoder [35] , and only transcripts encoding proteins of ≥ 30 amino acids were retained . The proportion of genome annotation represented by the non-redundant larval transcriptome was assessed using the program CEGMA [36] . Transcripts homologous ( BLASTn; E-value cut-off: < 10−5 ) to avian , bacterial or viral nucleotide sequences in the NCBI non-redundant nucleotide database [37] and translated proteins homologous ( BLASTp; E-value cut-off: 10−5 ) to transposable elements in the RepBase database [38] were quarantined as well as sequences shorter than 50 amino acids ( aa ) with no homology in public databases . The non-redundant , merged transcriptome was then annotated using an established pipeline [39] . Briefly , protein sequences inferred from transcripts were annotated using their closest homologues ( BLASTp; E-value cut-off: ≤ 10−5 ) in the following databases: NCBI non-redundant protein [37]; SwissProt [40]; MEROPS peptidase and peptidase inhibitor [41]—with predicted peptidases of unknown catalytic type and inhibitor homologues of unassigned peptidases being excluded; Kyoto Encyclopedia of Genes and Genomes ( KEGG ) [42] , excluding KEGG “Human Diseases” and “Organismal Systems” categories . Conserved domains and their associated gene ontology ( GO ) annotations were predicted using the program InterProScan [43] . The server REVIGO was used to summarize GO terms and define a representative subset of terms using a simple clustering algorithm that relies on semantic similarity measures [44] . Excretory/secretory ( E/S ) proteins were predicted based on the presence of a signal peptide and the lack of a transmembrane domain; in addition , proteins were subjected to analysis using the program MultiLoc2 [45] to predict their sub-cellular location . Only proteins predicted to be extracellular or lysosomal ( score: > 0 . 5 ) were included from the final set of predicted E/S proteins . For each biological replicate , paired , trimmed and corrected reads were mapped to the final transcriptome using RSEM [46] . The expected counts predicted were rounded to the highest whole number , and used as counts per transcript for differential gene transcription analysis using edgeR v . 3 . 6 . 7 [47] and R v . 3 . 10 [48] software packages , with read counts being normalized to account for any GC bias [49] and using the trimmed mean of M-values ( TMM ) [50] . Transcripts with more than a log2 fold-change in transcription between the two developmental stages ( i . e . cercaria and schistosomulum ) and with a false discovery rate ( FDR ) of ≤ 0 . 01 were recorded as differentially transcribed . Enriched GO terms for transcripts recorded to be differentially transcribed in either developmental stage were tested using topGO [51] and the Fisher’s exact test ( p ≤ 0 . 05 ) ; representative enriched GO terms were inferred using the program REVIGO [44] . In addition , transcripts specific to either the cercaria or the schistosomulum were those with RSEM expected counts of > 2 in at least one of four replicates representing one but not the other developmental stage .
The sequencing of eight T . regenti cDNA libraries ( four representing each the cercaria and schistosomulum biological replicates ) produced 146 , 921 , 480 high quality reads ( 75 , 733 , 168 for cercariae; 71 , 188 , 312 for schistosomula ) , with an average read length of 132 ± 30 bp ( mean ± standard deviation; Tables 1 and S1 ) . Pooled RNA-seq data were used to assemble a non-redundant transcriptome , which included 12 , 705 assembled transcripts ( average nucleotide length: 2 , 697 . 1 ± 2 , 166 . 4 bp; 115 to 41 , 111 bp; N50 = 3 , 333 ) , each encoding a predicted protein ( average length: 514 . 5 ± 537 . 7 residues; range: 30 to 8 , 133 residues ) , excluding transcripts that did not code for a protein ( n = 6 , 899 ) . Of the selected coding regions , 9 , 514 commenced with a start codon , and 11 , 434 terminated with a stop codon . Despite sequencing only two developmental stages , the T . regenti transcriptome includes 89 . 5% of the 358 conserved eukaryotic genes [36] ( Table 1 ) , and thus represents a substantial proportion of the gene set . On average , 61 . 5% and 74 . 4% of the sequence reads representing the cercaria and schistosomulum , respectively , mapped to the non-redundant T . regenti transcriptome ( S1 Table ) . The final transcriptome and RNA-seq read data are available for download via the NCBI transcript reads archive and sequence read archive ( SRA ) , respectively ( BioProject ID: PRJNA292737 ) . Totals of 88 and 243 potential contaminants ( avian , viral and bacterial ) were removed from the cercaria and schistosomulum transcriptomes , respectively . Following the removal of these sequences , the larval transcriptome was shown to encode 10 , 900 ( 77 . 5% ) and 8 , 347 ( 57 . 8% ) predicted proteins that were homologous ( BLASTp; E-value ≤ 1e-05 ) to those in the NCBI ( non-redundant proteins ) and SwissProt databases , respectively ( Table 1 ) . In addition , 5 , 935 predicted proteins were assigned 41 unique KEGG BRITE protein families ( Fig 2A; Tables 1 and S2 ) , and 3 , 611 predicted proteins were assigned 172 biological KEGG pathways ( Tables 1 and S2 ) . Using the MEROPS peptidase and inhibitors database , 318 peptidases , including key molecules recognized to be involved in cercarial penetration and schistosomulum migration , nutritional uptake and/or immune evasion [19] were identified ( S3 Table ) . Transcripts encoding metallopeptidases ( n = 129 ) were abundant , and included ubiquinol-cytochrome c reductase proteins ( n = 23 ) , kell blood-group proteins ( n = 8 ) and leucine aminopeptidases ( n = 4 ) . Transcripts encoding cysteine peptidases ( n = 106 ) including cathepsin B ( n = 11 ) , cathepsin L ( n = 6 ) cathepsin C ( = dipeptidyl-peptidase; n = 3 ) , ubiquitin-specific peptidases ( n = 10 ) and legumains/aspariginyl endopeptidases ( n = 2 ) and a ubiquitin-specific peptidase , were also well represented . Transcripts encoding serine peptidases ( n = 62 ) represented indeterminate peptidases ( n = 43 ) , cathepsin A ( = carboxypeptidase A; n = 3 ) and mitochondrial inner membrane peptidase 2 ( n = 2 ) . Transcripts encoding threonine peptidases ( n = 15 ) were represented by proteasome subunits ( n = 4 ) . Also identified was a small number of transcripts encoding aspartic proteases ( n = 6 ) , including one cathepsin D . In total , transcripts representing 260 inhibitors of peptidases were identified in the ( non-redundant ) transcriptome of T . regenti , most of which represented inhibitors of metallo- ( n = 110 ) , serine ( n = 77 ) and cysteine peptidases ( n = 41 ) ( S3 Table ) . A relatively large number of proteins predicted were homologous to those encoded in the genomes of other trematodes , including schistosomes ( 10 , 909 proteins; 85 . 6% being similar to Schistosoma mansoni , S . japonicum and/or S . haematobium ) ( Fig 2B ) and Asian liver flukes ( 10 , 080 proteins; 79 . 3% being similar to Clonorchis sinensis and/or Opisthorchis viverrini ) ( Fig 2C ) . Of note were 1 , 722 transcripts that had no homology to other trematode species; only 12 of them ( including collagen alpha-3 ( VI ) chain-like , 40S ribosomal protein S7-like , ReO_6 , membrane magnesium transporter 1-B-like , VWFA and cache domain containing protein 1 and UPF0729 protein C18orf32 homolog ) shared homology to proteins in the NCBI database . In addition , collagen , type VI , alpha and small subunit ribosomal protein S7e were predicted to be involved in five biological pathways ( S4 Table ) . In addition , the larval transcriptome encoded 135 ES proteins , including various peptidases and their inhibitors , phosphatases , kinases , transferases and ribonucleases ( S5 Table ) . A total of 11 , 058 transcripts were shared by cercariae and schistosomula . Mapping results revealed 270 and 951 transcripts to be specific to the cercaria and schistosomulum stages , respectively ( Fig 3A; S6 and S7 Tables ) . In total , 1 , 301 transcripts were up-regulated in cercariae and 1 , 876 in schistosomula ( S8 and S9 Tables ) . The top twenty most differentially transcribed genes in cercariae encoded venom allergen-like protein 8 , tegumental protein , calcium-binding proteins , glutamine synthetase and some uncharacterized proteins ( with no homology to any sequences in public databases ) . The top twenty most differentially transcribed genes in schistosomula encoded peptidases ( e . g . peptidase M26 , cathepsin B1 ) and beta galactosidase , some uncharacterized proteins with homology to those of S . mansoni , two of which ( Treg_015087 , Treg_015334 ) were homologous to a saposin-like protein and beta hexosaminidase B based on InterPro classification respectively ( Table 2 ) . A number of up-regulated transcripts encoded proteins with conserved functional domains ( 1 , 178 and 1 , 699 for cercariae and schistosomula , respectively ) and/or similarity to proteins in the KEGG database [605 and 786 ( BRITE ) ( Fig 3B ) , and 389 and 487 ( pathway ) for cercariae and schistosomula , respectively] . Using these transcripts , we were able to identify enriched KEGG BRITE protein families , biological pathways and GO terms ( biological process ) in each of the two larval stages ( Tables 3 , 4 , S10 and S11 ) . In cercariae , 162 up-regulated transcripts represented five enriched KEGG BRITE protein families ( Tables 3 and S10 ) , with most transcripts encoding exosome-related proteins , including calmodulin ( n = 10 ) , long-chain acyl-CoA synthetase ( n = 4 ) , creatine kinase ( n = 4 ) and tropomyosin 1 ( n = 3 ) . Other protein families were associated with: ( a ) metabolic processes involving lipid biosynthesis proteins ( n = 9 ) and amino acid-related enzymes ( n = 14 ) , and ( b ) cellular processes linked to protein translation , ribosomes ( n = 26 ) and ribosome biogenesis ( n = 38 ) . In addition , 202 transcripts up-regulated in cercariae represented 21 enriched KEGG ( biological ) pathways ( Tables 3 and S10 ) , with almost one quarter of them ( n = 50 ) linked to pathways associated with carbohydrate metabolism , including the tricarboxylic acid cycle ( n = 23 ) , glycolysis ( n = 21 ) and pyruvate metabolism ( n = 13 ) . Other pathways enriched in the cercariae were linked to amino acid metabolism [alanine , aspartate and glutamate ( n = 11 ) ; arginine and proline metabolism ( n = 11 ) ; and glycine , serine and threonine metabolism ( n = 7 ) ]; energy metabolism [oxidative phosphorylation; n = 21; nitrogen metabolism ( n = 4 ) ]; the metabolism of cofactors and vitamins and nucleotide metabolism [nicotinate and nicotinamide metabolism ( n = 15 ) and purine metabolism ( n = 24 ) ]; environmental information processing [calcium signaling pathway ( n = 23 ) and two component regulatory system ( n = 4 ) ] ( Tables 3 and S10 ) . In addition to these enriched protein families and biological pathways , 161 transcripts up-regulated in the cercariae were linked to 36 GO terms for ‘biological process’ that were enriched in the cercarial stage ( Tables 3 and S10 ) . These GO terms were represented by eight representative biological processes , including cellular respiration ( 115 transcripts linked to 17 GO terms , including ATP metabolic process , glycerol-3-phosphate metabolic process , nucleotide biosynthetic process , organophosphate biosynthetic process and oxidation-reduction process ) , glucose metabolism ( 29 transcripts representing five GO terms , including carbohydrate catabolic process , cellular carbohydrate metabolic process , glucose metabolic process and organic substance catabolic process ) , acto-myosin structure organization ( 23 transcripts representing five GO terms , including actomyosin structural organization , cell wall macromolecule metabolic process , cell wall organization or biogenesis , energy-coupled proton transport , down electrochemical gradient , and ribosome biogenesis ) and coenzyme metabolism ( 22 transcripts representing four GO terms , including acetyl-CoA metabolic process , coenzyme catabolic process , coenzyme metabolic process and cofactor catabolic process ) . Other biological processes were represented by single GO terms and included carbohydrate metabolism ( 40 transcripts ) , cofactor metabolism ( n = 22 ) , generation of precursor metabolites and energy ( n = 23 ) and pyridine-containing compound metabolism ( n = 9 ) . In schistosomula , 145 up-regulated transcripts represented five enriched KEGG BRITE protein families ( Tables 4 and S11 ) , with most encoding peptidases ( 61 transcripts ) including cathepsin B ( n = 11 ) , cathepsin D ( n = 8 ) , separase ( n = 4 ) , leucyl amino peptidase ( n = 3 ) and legumain ( n = 3 ) . Other protein families enriched were associated with: ( a ) metabolic processes involving heparan sulfate/heparin binding proteins ( n = 22 ) and proteoglycans ( n = 6 ) , ( b ) genetic information processing involving chaperones and folding catalysts ( n = 54 ) and ( c ) environmental information processes represented by cell adhesion molecules and their ligands ( n = 42 ) . In addition , 128 up-regulated transcripts represented 10 enriched KEGG biological pathways ( Tables 4 and S11 ) . Metabolic pathways involved carbohydrate , amino sugar or nucleotide sugar metabolism ( n = 32 ) ; glycan biosynthesis and metabolism , including glycosaminoglycan degradation ( n = 32 ) , and glycosphingolipid biosynthesis ( n = 33 ) . In each metabolic pathway , 30 different transcripts encoding hexosaminidase were inferred to be involved . Pathways associated with signalling were also significantly enriched in the schistosomula , and represented by cell adhesion molecules ( n = 6 ) and extracellular matrix—receptor interaction molecules ( n = 10 ) . Other enriched pathways in the schistosomula were associated with cellular processes , such as cell cycle ( n = 21 ) and processes linked to lysosome function ( 78 transcripts , including 30 encoding hexosaminidases ) . In addition to the enriched protein families and biological pathways , 332 transcripts were linked to 28 GO ( ‘biological process’ ) terms enriched in the schistosomulum stage ( Tables 4 and S11 ) . These GO terms represented five core processes: cell adhesion ( n = 105 transcripts; 18 associated GO terms ) , proteolysis ( n = 215; 7 GO terms ) , biological adhesion ( n = 37; one GO term ) , multicellular organismal process ( n = 15; one GO term ) and developmental processes ( n = 20; one GO term ) .
Based on similarity searches , the proteins predicted from the T . regenti transcriptome have 85 . 9% sequence homology to those of human schistosomes ( BLASTx , E-value 10−5 ) , although divergent molecules ( 14 . 2% ) are proposed to relate to considerable differences in biology of bird and human schistosomes . Trichobilharzia regenti shares 110 transcripts exclusively with S . japonicum , with no homologues in either S . mansoni or S . haematobium . This finding is consistent with S . japonicum being the most similar of the three human schistosomes to T . regenti in terms of chemical tools serving for skin penetration . In particular , a shared feature of T . regenti and S . japonicum is the absence , at both the mRNA and protein levels , of cercarial elastase [18 , 55–57] . By contrast , S . mansoni and S . haematobium both use elastase for cercarial invasion of the definitive host [58 , 59] . While humans represent exclusive/dominant hosts of S . haematobium and S . mansoni , S . japonicum has an ability to infect a broader range of mammals ( including pigs , water buffalo and water rats; [60] ) , but not birds as natural final hosts . In this case , therefore , the absence of elastase in both S . japonicum and T . regenti seems to be an interesting example of convergence . In other words , the data here indicate that T . regenti shares more unique transcripts ( n = 110 ) with S . japonicum than either S . mansoni ( n = 52 ) or S . haematobium ( n = 57 ) ( Fig 2B ) ; the apparent absence of cercarial elastase from the two former species might reflect their distinct host affiliations/broader spectra compared with the latter two . Interestingly , 1 , 722 ( 13 . 6% ) of predicted proteins of T . regenti had no homology to those of any other trematode species , for which molecular data are available ( none of which are parasites of birds ) ( Fig 2B ) . Of these 1 , 722 predicted proteins , only 151 had homologues in public databases . Remaining 1 , 571 transcripts represented orphans ( genes with no homology to known domains or proteins ) . However , some of these orphans were highly transcribed in cercariae and/or schistosomula . Interestingly , 10 and 8 of 20 genes exhibiting the highest transcription in cercariae and schistosomula , respectively , encoded orphans . Such molecules might have unique particular biological functions or processes in T . regenti associated with the penetration of avian skin ( cercaria ) , specific migration through neural tissue ( schistosomulum ) and an adaptation to the avian definitive host ( both stages ) . This statement is supported by biological and clinical evidence [26] , showing that T . regenti is not able to effectively establish infection in the mammalian hosts under natural conditions . In digenetic trematodes , interestingly , the cercaria are considered to be less transcriptionally active than other developmental stages [61–63] , although the high transcription of genes encoding proteins participating in particular metabolic pathways described here likely reflects the specific biological requirements of this larval stage . During their invasion of the definitive host , the transformation of cercariae to schistosomula is associated with rapid and major morphological , biochemical and molecular changes . Unlike most schistosomes studied to date , the schistosomula of T . regenti do not enter the bloodstream , but rather seek out and migrate in nerves and consume neural tissue ( as nutrition ) during migration [26] . Compared with the circulatory system , the nervous system represents an immunologically and physiologically distinct environment ( in terms of nutrients and immune responses ) . The present study investigated the schistosomula of T . regenti seven days after infection of the avian host and explored the molecular adaptations required for the parasite to establish and survive in this unique niche—the neural system .
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Despite the clinical importance of Trichobilharzia regenti in bird hosts and as a cause of cercarial dermatitis in humans , almost nothing is known about the molecular aspects of this fluke and its interactions with its hosts . Here , we sequenced , assembled and annotated the transcriptome representing two life stages ( cercariae and schistosomula ) of T . regenti involved in the first phases of infection of the bird host . We identified key biological and metabolic pathways specific to each of these two developmental stages and also undertook comparative analyses using data available for related flukes . Detailed analyses showed the unique involvement of carbohydrate metabolism , translation and amino acid metabolism , and calcium in T . regenti cercariae during invasion and in growth and development , as well as cell adhesion molecules , microaerobic metabolism ( citrate cycle and oxidative phosphorylation ) , peptidases ( cathepsins ) and other histolytic and lysozomal proteins in schistosomula during migration in neural tissues . These molecular insights into T . regenti biology should support future genomic and proteomic investigations of T . regenti , and comparative studies of flatworms .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
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2016
|
Comparative Transcriptomic Exploration Reveals Unique Molecular Adaptations of Neuropathogenic Trichobilharzia to Invade and Parasitize Its Avian Definitive Host
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Dopamine is thought to directly influence the neurophysiological mechanisms of both performance monitoring and cognitive control—two processes that are critically linked in the production of adapted behaviour . Changing dopamine levels are also thought to induce cognitive changes in several neurological and psychiatric conditions . But the working model of this system as a whole remains untested . Specifically , although many researchers assume that changing dopamine levels modify neurophysiological mechanisms and their markers in frontal cortex , and that this in turn leads to cognitive changes , this causal chain needs to be verified . Using longitudinal recordings of frontal neurophysiological markers over many months during progressive dopaminergic lesion in non-human primates , we provide data that fail to support a simple interaction between dopamine , frontal function , and cognition . Feedback potentials , which are performance-monitoring signals sometimes thought to drive successful control , ceased to differentiate feedback valence at the end of the lesion , just before clinical motor threshold . In contrast , cognitive control performance and beta oscillatory markers of cognitive control were unimpaired by the lesion . The differing dynamics of these measures throughout a dopamine lesion suggests they are not all driven by dopamine in the same way . These dynamics also demonstrate that a complex non-linear set of mechanisms is engaged in the brain in response to a progressive dopamine lesion . These results question the direct causal chain from dopamine to frontal physiology and on to cognition . They imply that biomarkers of cognitive functions are not directly predictive of dopamine loss .
Successful and adaptive completion of cognitive tasks requires tight integration between performance monitoring [1 , 2] , which provides information about task outcomes , and cognitive control [3] , which drives behavioural adaptation as necessary . These systems are associated with neurophysiological markers in the frontal lobes that are modulated by motivation [4] . Error- and feedback-related potentials ( error-related negativity [ERN] and feedback potentials [FRPs] ) recorded over the medial part of the frontal lobe in electroencephalography ( EEG ) [5–7] , electrocorticography ( ECoG ) [8] , and local field potential ( LFP ) [9] differentiate outcome valences . These performance-monitoring signals are in many cases generated in midcingulate cortex ( MCC [10 , 11] ) . These signals appear to provide information about the value of the feedback in terms of behavioural adaptation [12 , 13] , be it for directly driving adaptation on subsequent trials [14] or for motivating more extended behaviours beyond simple trial-to-trial adaptation [15–17] . A second key constituent of this integrated system implements the chosen level of control and is associated with lateral prefrontal cortex ( PFC ) . Control implementation is signaled , for example , in modification of classical working memory delay activity [18] , and has been linked to PFC beta oscillatory power . In frontal cortex , beta oscillations are implicated in top-down control of behaviour in cognitively engaging tasks [19–22] , whilst also altering within-session to reflect attentional effort on the task [23] . Dopamine ( DA ) is proposed to have a critical role in regulating these systems and the related behaviour [24] , and theoretical and computational models support a link between dopamine dysfunction and a range of cognitive symptoms in neurological disorders [25 , 26] . A working model has been proposed that directly links DA to both performance monitoring and cognitive control in frontal cortex . First , the mesocortical dopaminergic projections are thought to provide a prediction error signal that regulates performance monitoring functions implemented in MCC [10] . However , causal proof for this relation remains sparse [8] , dopamine antagonist interventions have variable effects on behavioural outcomes [27 , 28] , and so the functional significance of this link is debated [29] . Second , dopamine has been directly or indirectly linked to neurophysiological prefrontal mechanisms of cognitive control [30 , 31] , working memory [32–34] , and motivation [35] . If dopamine has a clear role in these mechanisms , it should be revealed in diseases with an altered dopaminergic system [2] , and dopamine loss should be related to the relevant behavioural and cognitive deficits . But it remains unclear whether this relationship is as direct and simple as the model proposes [36] . There is evidence for ERN modification in Huntington’s disease [37] and schizophrenia [38] , though the extent to which these effects are a result of dopaminergic changes is unclear . The dopamine system is implicated in impairments of cognitive control and motivation in Parkinson’s disease ( PD ) [39] , yet neurophysiological studies of PD patients provide only mixed evidence for and against the modification of ERN [40–43] , and FRP [44] . Proper testing of this working model requires a systemic approach combining dopaminergic modulation , neurophysiology of frontal mechanisms , and related cognitive control performance . This approach is absent from the literature , and yet this test is a mandatory step to understanding dopamine-neurophysiology-cognition links , the role of dopamine in driving frontal functions , and how to target treatments of the relevant conditions . Here , we reveal the dynamic of performance monitoring , cognitive control , and their neurophysiological markers during a progressive lesion of the dopamine system . In particular , we use a test of cognitive control [18] known to share direct prefrontal neuronal mechanisms with dopamine-sensitive working memory [45 , 46] . Contrary to the working model , we found dissociations between evoked markers of performance monitoring ( feedback-related potentials ) and performance on the task itself , and between induced markers of cognitive control and motivation ( frontal beta oscillations ) . Our data , therefore , argue against a simple interaction between dopamine and frontal functions .
Two monkeys learned the problem-solving task ( PST , Fig 1A ) , [18] , a test of cognitive control during which they had to search ( SEA phase ) by trial and error using feedback amongst four visually identical stimuli to find the location rewarded by juice . Once monkeys had found the rewarded location , they could repeat that rewarded choice three times ( repetition phase , REP ) , before a signal to change ( STC ) informed them that the rewarded location had been re-randomized . Previous research has shown that the PST induces high or low cognitive control on different trials [8 , 12 , 18 , 23] . Low control is sufficient on any repetition trial after correct feedback , as the monkey simply has to repeat the previous choice . High control is required when the outcome of the previous trial necessitates a behavioural adaptation—notably , in three cases , after an incorrect feedback , after an STC directing a new SEA phase , and after the monkey makes a break in fixation or touch . This task is a well-established test of cognitive control with well-established neural correlates , notably delay activity in PFC comparable to working memory tasks [18] and feedback responses sensitive to dopamine [8] . As such , it allows us to probe control in terms of both performance monitoring and control implementation . In the BL period , monkeys were tested for at least 10 weeks with sham injections to establish baseline performance and neurophysiology . During this time , monkeys’ performance approached optimality . Their level of non-optimal responses ( repeated choices in SEA , errors in REP; see Materials and Methods ) was low , at less than 10% ( Fig 1B ) , and they showed , as expected , lower levels of non-optimal choice after low-control than high-control trials ( ANOVA , Monkey R: F ( 1 , 26189 ) = 638 , p < 0 . 0001; Monkey S: F ( 1 , 13449 ) = 563 , p < 0 . 0001 , Fig 1B ) . Furthermore , they showed clear and responsive transition between REP and SEA phases , taking into account the STC and changing their choice on the following trial ( Fig 1C ) . Response times ( RTs ) over choices also reflected these levels of control , with faster RTs on low-control trials after a correct response ( ANOVA , Monkey R: F ( 1 , 26189 ) = 59 , p < 0 . 0001; Monkey S: F ( 1 , 13449 ) = 236 , p < 0 . 0001 , Fig 1D ) . A similar effect is present in the reaction times , more commonly used in human experiments ( S2 Fig ) . Together , these behavioural data demonstrate that monkeys are able to apply cognitive control to search for and then exploit reward possibilities , as previously shown in this task [12] . Monkeys were implanted with grids of 22 and 31 trans-cranial ECoG electrodes covering the frontal lobes ( Monkeys R and S respectively , S1B Fig ) . We aligned ECoG signals to analyze individual trials during the delay epoch ( Fig 1A ) , when the monkey awaits the start of the trial , and the feedback epoch . In BL , a medial frontal evoked response after feedback differentiated correct ( COR ) from incorrect ( INC ) feedback , with a significant response difference between 50 and 200 ms ( grand average waveforms in Fig 2A , permutation test , p < 0 . 001 in both monkeys ) . This FRP therefore reflects critical information that might be required to adapt behaviour in the following trial , as best indexed by the difference curve shown in Fig 2B , a standard measure in the literature [47] . The FRP signal was highly stable over sessions , as we have previously demonstrated [8] . The surface Laplacian FRP is located relatively medially over prefrontal cortex , with a maximum contralateral to the working arm of each monkey ( Monkey R left handed , Monkey S right handed ) . We and others have previously reported this marker in monkeys [8] and humans [5] . It is thought to arise from a source in the MCC [11] and to be sensitive to dopaminergic modulations [8 , 10] . The contrast INC–COR can reveal effects of feedback valence and/or feedback expectancy . Although the task is not perfectly designed to dissociate the two because monkeys are making free choices , we can provide evidence for one or the other by focusing on trials from the SEA phase . This includes INC and first correct ( CO1 ) trials from each problem , excluding repeated COR feedback , for which the monkey has a higher expectation than CO1 . In SEA , the probabilities of observing negative or positive feedback ( INC and CO1 ) are roughly equivalent on average ( S3B Fig , Monkey R: p ( INC ) = 0 . 46 , 95% CI [0 . 4 , 0 . 51]; Monkey S: p ( INC ) = 0 . 61 , 95% CI [0 . 57 , 0 . 65]; p ( CO1 ) is the complementary in each case ) . S3A Fig shows that the difference curve is maintained in BL when considering the contrast INC-CO1 . This suggests , therefore , that it is the valence of the feedback that mainly drives the observed FRP , rather than the expectancy of receiving each type of feedback . During the delay epoch at the start of a trial , the monkey can prepare the upcoming choice based on previous choices and outcomes . Both monkeys showed strong induced oscillations in the beta band ( 15–30 Hz ) throughout the delay ( Fig 2C ) . We analysed the band of beta power that we had previously identified as being modulated by the cognitive elements of the task in each monkey [23] ( see also Materials and Methods ) . The absolute value of delay beta power varies in a trial-by-trial manner with a number of factors . We used linear mixed-effects modeling [48] to reveal the contributions of these factors and account for the repeated measures nature of our design [23] . Importantly , here and throughout the study , we selected a linear mixed-effects model to describe the data through a model selection procedure . The process and selected model are presented in detail in the Materials and Methods . All models discussed herein contain only behavioural factors that have survived model selection . A number of potential factors notably did not survive model selection , including response times and optimality of choice ( in each case , likelihood ratio test between nested models , p > 0 . 05 ) . Note that the term “beta” refers to power of high beta oscillations , and never to any form of model beta ( i . e . , estimates ) . The effect of cognitive control requirements was strong and consistent: any outcome that required the monkey to adapt behaviour—incorrect feedback , STC , or breaks—led to increased beta power during delay in the following trial , when compared to a positive outcome ( “correct” ) that simply led to a repetition of the previous choice ( Fig 2D , Wald conditioned F test: Monkey R: F ( 2 , 22790 ) = 370 , p < 0 . 0001; Monkey S: F ( 2 , 11312 ) = 39 , p < 0 . 0001 ) . In addition to cognitive control , two factors potentially related to motivation had significant impact on beta power . First , beta power significantly increased with time “within-session”—that is , in a given session , power correlated with the time the monkey had spent continuously working ( Fig 2E , Wald conditioned F test: Monkey R: F ( 1 , 22790 ) = 209 , p < 0 . 0001; Monkey S: F ( 1 , 11312 ) = 22 , p < 0 . 0001 ) . We have previously linked this within-session change to an increase of attentional effort of the monkey during sustained work , not least because the power increase is “reset” by a voluntary pause in work [23] . In that study we also showed that this attentional effort effect is independent of cognitive control . Second , the frequency with which the monkey engaged trials had a smaller but significant effect on beta power ( Fig 2F , Wald conditioned F test: Monkey R: F ( 1 , 22790 ) = 12 , p = 0 . 0004; Monkey S: F ( 1 , 11312 ) = 5 . 4 , p = 0 . 02 ) . Engagement is potentially a measure of the motivation for the task , although its interpretation is not unambiguous . The interaction between measures of motivation and cognitive control is a significant subject of interest ( and confusion ) in the field [4] . Here , trial-by-trial engagement and attentional effort both influenced beta power , but there were no interactions between these effects ( likelihood ratio test between nested models , Monkey R: p = 0 . 23; Monkey S: p = 0 . 57 ) , nor did they interact with cognitive control ( same test , p > 0 . 15 in each case ) . This clearly suggests three separable drivers of beta power . Hence , data presented in Figs 1 and 2 reveal that during the BL period , monkeys were performing the PST near optimally using performance monitoring and cognitive control , and that these processes are reflected in stable neurophysiological measures in frontal cortex by FRPs and beta oscillatory power . Monkeys then received doses of 0 . 2 mg/kg of MPTP , a dose well established in progressive protocols [49 , 50] . MPTP injections were given at most once per week—significantly less frequently than most other studies . The protocol was designed to induce very slow degeneration whilst permitting concurrent recordings with sufficient task performance ( see Materials and Methods ) . The protocol was long ( Monkey R: 33 weeks; Monkey S: 56 weeks ) so that gradual emergence of neural changes could be observed . Treatment continued until monkeys obtained a “significantly symptomatic” score of 5 on the Parkinsonian Monkey Rating Scale ( PMRS ) [50] . Monkeys therefore remained below this significantly symptomatic level throughout the MPTP period ( Fig 3A ) , and the final period during which monkeys worked before attaining this level of symptoms is referred to as the “full dose . ” Whilst the total cumulative dose was different , the pattern of symptomology across treatment was similar between the two monkeys ( Fig 3A ) . This pattern is consistent with slow emergence of a dopaminergic lesion with MPTP , in line with other progressive protocols [49–51] . Note that the PMRS motor scale scoring is included for evaluation of the Parkinsonian state as applied in the literature . Our aim is to contrast it with changes in frontal neurophysiology and cognition , and it is not intended as an assessment of these latter measures . PMRS scoring acted as the principle measure of lesion progress and determined cessation of the protocol . The use of a progressive MPTP protocol in conjunction with motor scoring is well established in the literature [49 , 51] . Monkeys showing full motor symptoms following MPTP treatment already have significant loss of nigral dopaminergic cells [52] , and monkeys brought to a motor symptomatic state who subsequently recover nevertheless show reduced tyrosine hydroxylase ( TH ) cell labeling in the mesencephalon [51] . Previous work in our laboratory has measured the binding potential of the selective dopamine active transporter ( DAT ) radiotracer [11C]PE2I in monkeys in a progressive MPTP protocol [53] . The use of this tracer is also established in patients with Parkinson’s disease [54] . We showed that DAT binding is increased in the early phases of a progressive MPTP lesion , returning to baseline levels around the onset of symptoms and then dropping as motor symptoms become persistent . The final strong motor symptomatic phase is associated with significant striatal TH depletion after immunohistochemical analyses [53] . On the basis of this previous work , we consider that at the onset of significant motor symptoms , the monkeys in the current protocol have received a significant lesion to the nigrostriatal dopamine system . However , we chose not to sacrifice these highly trained and implanted animals at this moment of the study , and so we are unable to provide histological confirmation of this assertion . Nevertheless , we acquired PET scans during our protocol , again using the ligand [11C]PE2I , to demonstrate that there was modulation of the DA system as previously observed . S4 Fig confirms that across the scans carried out , the MPTP lesion modulates the DA system ( repeated measures ANOVA , main effect of scan , Monkey R: F ( 4 , 50 ) = 25 . 36 , p < 0 . 0001; Monkey S: F ( 8 , 94 ) = 17 . 91 , p < 0 . 0001 ) . Importantly , as for the motor symptoms , the two monkeys show the same pattern of modulation over the time-course of the lesion . Specifically , DAT binding is increased above baseline levels at the start of the lesion and then returns to or drops below baseline levels at full dose . This pattern replicates our previous result [53] . Vezoli et al . posited this early increase as a potential compensatory response to DA cell death . Under this interpretation , DA cell death and loss of dopaminergic transmission will be well advanced by the time DAT binding begins to reduce below baseline levels , as they appear to do at the end of the protocol . We can , however , draw only limited conclusions from the PET data set with respect to direct PFC and MCC physiology , due to the low levels of DAT in those regions [55 , 56] . Binding of DAT in lateral prefrontal cortex was indeed negligible , but S4 Fig shows binding potential of the anterior cingulate region of interest ( ROI ) ( derived from [57] ) , which includes the region we refer to as MCC [11] , as well as for caudate and putamen ROIs . Binding potential in this cingulate ROI is much lower than the striatum , but as in our previous study , DAT binding in cingulate was the highest across all cortical regions , and there is support from immunohistochemical localisation for DAT in this region [56] . We provide these data as indicative . Further studies will require alternative approaches to provide more direct indications of the impact of MPTP on prefrontal dopamine . We followed the evolution of behavioural and neurophysiological measures throughout the protocol . Figures presented , such as Fig 3C , show the measure in BL ( boxplots on left ) , and then the evolution of the measure with MPTP ( lines ) . The change relative to the BL period is presented as significance bars on the figures . We also tested , at each time-point in the MPTP period , whether the effects reported for the BL period were still significant in and of themselves . These tests are not shown in the figures but are described below . We considered the RTs to look for early motor changes during the motivated cognitive task . RTs showed no significant slowing despite the dopaminergic lesion ( Fig 3C ) . In fact , RTs showed some sessions with significant speeding in both monkeys ( colored bars on Fig 3C , non-parametric comparison with BL using bootstrap , p < 0 . 01 for both monkeys ) . The reflection of cognitive control in the RTs was significant for Monkey S throughout ( ANOVA corrected for multiple comparisons , p < 0 . 01 throughout ) but was lost at the onset of MPTP in Monkey R , yet later recovered . Hence , despite the lesion , monkeys maintained similar RT in the task . Outcome-related potentials are modulated in some studies in PD , and so we anticipated modulation of the FRPs as a result of our dopamine lesion . At onset and for much of the lesion , FRP difference was maintained ( Fig 4A ) . But at full-dose MPTP , at the end of the protocol , the early peak difference FRP was significantly attenuated in both monkeys ( Fig 4A , permutation test between BL and MPTP full dose , p < 0 . 01 ) . Furthermore , there was in fact no longer a significant difference between the correct and incorrect FRP for Monkey S ( Fig 4B , permutation test between INC and COR , no significant change from distribution of permutations ) , although Monkey R did maintain a marginally significant difference ( same permutation test , p < 0 . 05 ) . As for the BL period , we performed the same analysis restricted to the SEA phase , to further address whether FRP change is driven by changes in coding the valence of feedback or changes in coding the expectancies . S3C Fig shows that , as in Fig 4A , there is significant attenuation of the INC-CO1 difference at full dose compared to BL for Monkey R . This effect does not reach significance for Monkey S , although the difference between the INC and CO1 is not significant at full dose for this monkey ( permutation test between INC and CO1 , no significant change from distribution of permutations ) , with a high variance as can be seen in S3C Fig . It therefore appears that loss of feedback valence coding , rather than feedback expectancy coding , is driving the observed effect . As noted above , however , a design that explicitly equalizes the feedback probabilities would provide a definitive answer . Analysis of the peak latencies of this difference wave was inconclusive and noisy , and Fig 4B shows clearly why this is the case; after the full dose , a peak difference is no longer truly observed . This attenuation is greatest in the anatomical locations of the original peak ( Fig 4B inset , change in peak difference from BL to full dose ) . This loss of sensitivity to feedback valence in the FRPs might therefore predict impaired performance , if it is the case that performance monitoring signals provide information necessary to adapt cognitive control and efficient choice . Contrary to this prediction , cognitive performance on the PST did not worsen during the lesion . Fig 5A shows that at no point , for neither monkey , and for neither level of cognitive control , did choice become less optimal than in the BL period . More optimal choice on low-control trials was also maintained ( ANOVA corrected for multiple comparisons: p < 0 . 01 throughout for both monkeys ) . The only significant effect was a slight but significant reduction of the proportion of non-optimal choices in high control , meaning improved cognitive performance , particularly in Monkey R ( colored bars on Fig 4A , non-parametric comparison with BL using bootstrap , p < 0 . 01 ) . We further tested whether there was an acute effect of MPTP injections that was subsequently compensated for after a few days of recovery . The number of days since the last injection had no significant effect on the proportion of non-optimal responses , despite a trend in Monkey S ( Monkey R: F ( 1 , 35959 ) = 0 . 073 , p = 0 . 787; Monkey S: F ( 1 , 40231 ) = 3 . 73 , p = 0 . 054 ) . Finally , monkeys maintained the same level of optimal problem transitions , showing that they continued to take into account the STC ( Fig 3B , non-parametric comparison with BL using bootstrap , p > 0 . 1 throughout ) . The lack of impairment on the task was somewhat surprising , given that evidence from the literature shows the early emergence of cognitive symptoms in monkeys treated with MPTP [50 , 58–60] and in cognitively less complex tasks than PST , albeit with higher frequency injections . We discuss this discrepancy below . We further tested whether monkeys’ strategy of initial target choice remained the same , by calculating the Shannon entropy of their first two choices within the SEA phase—that is , how consistent their initial choices were . Notably , this criterion is independent of optimality—initial choice strategy could change , but if incorrect choices were never repeated , search could remain optimal . Throughout treatment , this quantity was maintained ( Fig 5B , no change from BL bootstrap , p > 0 . 1 ) . We next investigated whether the measures of cognitive control reflected in the beta oscillations would be affected as the FRPs were . Cognitive control significantly modulated beta power throughout the MPTP period in both monkeys ( statistical model selected on BL and applied throughout the MPTP period using Wald conditioned F tests corrected for multiple comparisons; see Materials and Methods: Monkey R numerator df = 2 , denominator df > 1955 , p < 0 . 0001 throughout; Monkey S numerator df = 2 , denominator df > 2061 , p < 0 . 05 throughout ) . It is important to stress , therefore , that in both monkeys the reflection of cognitive control in beta power is strongly significant throughout . The dynamic of the coefficient is presented in Fig 5C ( solid lines ) . The significant effect does weaken with respect to BL levels when approaching full dose; but , critically , at full dose when the FRPs are significantly attenuated , both monkeys maintained a significant positive coefficient , Monkey R showing an effect as strong as in BL . We further confirmed that cognitive control did indeed contribute to explaining beta power even after the full dose , by repeating the model selection procedure on full dose data ( Fig 5C inset , Wald conditioned F test: Monkey R: F ( 2 , 5395 ) = 83 , p < 0 . 0001; Monkey S: F ( 2 , 4211 ) = 3 . 55 , p = 0 . 029 , to be compared with Fig 2D ) . Indeed , the model selection procedure on full dose revealed all of the same factors to be significant as in BL . As such , beta power continued to reflect cognitive control throughout , and related performance was maintained . There is , therefore , a striking dissociation pattern in these data , in particular at the full dose of MPTP just prior to motor symptom emergence . The assumed cognitive control loop breaks down; the marker of performance monitoring is attenuated at a moment when the cognitive performance , and the representation of that performance in beta power , is maintained . Fig 6 presents these results at full dose side-by-side for comparison . After MPTP ( yellow shading ) , the behavioural output and beta oscillatory representation of cognitive control are both maintained , whilst the measure of performance monitoring thought to drive these processes was attenuated or lost when compared to the BL period ( grey shading ) . Although cognitive performance was maintained , we did record a behavioural effect of the dopamine lesion—reduced engagement in the task . Engagement is the rate at which the monkeys initiate trials offered to them . Fig 7A shows the level of engagement in BL and then the evolution of this measure over the MPTP period . Monkey R showed reduced engagement compared to BL throughout the MPTP period . Monkey S showed reduced engagement , but later in the MPTP period ( colored bars Fig 7A , non-parametric comparison with BL using bootstrap , p < 0 . 01 ) . Indeed , the effect on engagement was present in monkey R from the very onset of the MPTP treatment ( Fig 7A inset , same test , p < 0 . 01 ) , demonstrating a rapid effect of the lesion . We conceived the engagement measure as an index of motivation . It must be noted , however , that this interpretation is not unambiguous: a motivated monkey will engage quickly , but a monkey applying high cognitive control might engage more slowly to ensure optimal performance . There is therefore a behavioural dissociation between cognitive performance and motivation . We sought to understand whether the beta power during MPTP lesion reflected the changing engagement as well as the maintained cognitive control . In the BL period , time within-session ( the attentional effort effect ) and engagement frequency both significantly contributed to explain beta power ( Fig 2 ) . Both factors could arguably be related to motivation , and neural markers have been proposed as a manner of understanding the complicated relationship between motivation and cognitive control [4] . The remainder of Fig 7 shows the dynamic of these influences on beta power throughout the MPTP period . Within-session time , the factor linked to attentional effort , continued to significantly influence beta power throughout the MPTP period ( Fig 7B , Wald conditioned F tests as above: Monkey R: numerator df = 2 , denominator df > 1955 , p < 0 . 015 throughout; Monkey S numerator df = 2 , denominator df > 2061 , p < 0 . 0001 throughout ) . So attentional effort modulates beta power despite the dopamine lesion . Fig 7B shows a strengthening of this effect in the middle of the protocol , potentially signaling a compensatory increase in attentional effort to maintain the good performance as the lesion continues . In contrast to this , the trial-by-trial engagement frequency immediately ceased to influence beta power at the onset of the MPTP period ( Fig 7C inset , Wald conditioned F test: Monkey R: F ( 1 , 6216 ) = 0 . 53 , p = 0 . 46; Monkey S: F ( 1 , 5340 ) = 0 . 26 , p = 0 . 61 ) , potentially reflecting the early behavioural effect , although the behavioural effect at onset is limited to one monkey . But this loss of effect was not permanent , and indeed Fig 7C shows that the influence of engagement on the beta power varied non-linearly throughout the protocol , reflecting neither the behavioural engagement nor the maintained within-session effect .
The proposal that dopamine-influenced MCC performance monitoring signals do drive subsequent adaptation of behaviour [10 , 61 , 62] remains a mainstay of the current literature . Perturbation or lesion of the MCC leads to behavioural impairment , at least over choice sequences [63–65] , whilst neurophysiological signals in MCC clearly show trial-by-trial adjustment on the current task [12 , 13 , 66] . Reinforcement-learning theory of medial frontal performance monitoring signals hypothesizes a link with dopamine [10] , and these signals are modified in some cases of diagnosed PD [40 , 43 , 44] . We found attenuated FRPs after dopamine lesion . Yet despite this change , behaviour remained near optimal , and the beta power continued to represent trial-by-trial control levels and adjustments . A compensatory change of the performance monitoring system may therefore occur as the dopamine system is modulated , maintaining cognitive control and performance . Compensation might occur through network [67] and/or neurochemical [68] changes . Ascribing a behavioural non-impairment after lesion to compensation can become an uninformative catch-all interpretation . The power of combining a lesion approach with neurophysiology is that we can provide evidence for and a potential source of that reorganisation . Here we show that the beta oscillatory cognitive control signal is maintained ( albeit weakened slightly at the end of the protocol ) , so the focus of any compensation should be the source of FRP , putatively MCC . It is therefore tempting to conclude that the MCC has reorganized in the face of changing dopamine input , in order to continue to provide necessary information to the control system , even though the FRP signal itself is lost . Our PET data provide tentative support for this interpretation , in that they indicate an increase in binding to DAT in cingulate regions in the early phase of the lesion , a phenomenon also observed in striatum and ascribed a compensatory role in our previous work [53] . Binding to DAT is then decreased at full dose , when the FRP is modulated . A weakness with this interpretation , however , is that there remains a lack of conclusive evidence that ( 1 ) the FRP has its source in MCC , and ( 2 ) that the FRP is a direct product of dopaminergic prediction error signals in MCC . Answers to these questions require direct inactivation or dopaminergic modulation locally within MCC . The alternative to this compensatory hypothesis is to conclude that the FRP is not a signal necessary for trial-to-trial adaptations of control . The alternative proposition would be that the actual trial-by-trial adaptations are mediated by the striatum [69] , whilst the MCC and the dopaminergic input it receives would be the source of a motivational control signal driving the selection of extended behaviour sets ( options ) [15 , 17 , 69 , 70] . An increasing body of work questions the direct trial-to-trial influence of the FRP on behaviour . For example , a simple behavioural modulation such as the provision of task contingencies is sufficient to dissociate changes in the FRN from behaviour in human subjects [16] . Under this hypothesis , the changing FRP that we observe is indeed a marker of the dopamine lesion but should not be expected to lead to immediate cognitive optimality deficit , but rather an impairment in behavioural set selection , which might manifest itself in reduced motivation . This interpretation is consistent with our previous work showing modulation of the FRP in this task following systemic injection of the dopamine antagonist haloperidol , in the context of maintained cognitive performance but reduced motivation for the task [8] . In the current study , the significant reduction in motivation in both animals ( Fig 7A ) further supports this argument . More complicated to interpret is the relationship between motivation measures and beta power . Trial engagement effect on power was immediately abolished ( Fig 7C inset ) but then followed a dynamic that did not match the continued reduced behavioural engagement in both monkeys . Such a pattern might itself be a signal of compensatory processes and represents a target of future study . In contrast to this , the within-session increase in beta power remained a strongly significant factor throughout ( Fig 7B ) . Indeed , this effect even strengthened in both monkeys with respect to BL in the middle part of the protocol . We discuss the latter effect further below . Lowered behavioural engagement is reminiscent of apathetic symptoms in PD . Our frontal markers only partially reflect this effect , and separation of motivational functions within these signals may require careful computational analysis [71] , a topic for future work . Nevertheless , our results add to a literature questioning a simple mechanistic link between dopamine depletion , neurophysiology , and apathy in PD [72] . A second element that may dissociate FRP from trial-by-trial performance is overtraining . Premorbid practice is known to have a protective effect on cognitive tasks [73] . As in the majority of monkey neurophysiology protocols , our animals were extensively trained on the cognitive task . It is important not to forget , however , that monkeys were already well trained in the BL period when there was a large FRP . Moreover , even a well-trained monkey is obliged to take feedback on each trial into account in order to display the near-optimal performance we report in Fig 5A . Automatic responding cannot lead to such performance , and this questions whether truly habitual performance is possible in this task . Nevertheless , it has already been suggested that over-training might diminish the need for differential feedback signals and the related dopaminergic signals in trial and error adaptation [74 , 75] . Thus , it may be possible that dopamine prediction error-driven modulation of the feedback response is necessary to learn the significance of feedback , but not to perform the task once this is learned . Longitudinal recordings throughout the long training protocol for such a task are necessary to reveal any such effect . The difference signal we report in BL would therefore be a no-longer-necessary residue of this process , hence the lack of behavioural effect of an attenuated difference signal . In contrast to the effect of MPTP on the FRP , modulation of beta power with control implementation remained significant throughout , although reduced compared to BL at the end of the protocol . The relationship between this beta signal and established dopamine-sensitive neural correlates of cognitive control and working memory remains an open question . Cells in PFC that respond to this task show delay activity , as in working memory ( delayed response ) tasks , and this delay activity is modified by control demands in different phases of the task [18] . PFC delay activity relies on DA [45] in multiple ways , in that D1 receptor modulation impacts tonic delay activity and related behaviour [32 , 34 , 46] , whilst D2 receptor modulation impacts phasic activity [33] . These separate roles are hypothesized to relate to differing dopamine-induced states that drive maintenance and robust representations through D1 [76] and transitions and flexibility through D2 [25] . It is unclear how the beta oscillations that we observe relate to this established single-unit activity in the prefrontal cortex . Delay beta power occurs at the same delay period as the single unit activity in [18] , and both phenomena are more pronounced when control demands are high ( Fig 5B of that study , Fig 2D here ) . We can therefore speculate that they reflect similar processes . Under this hypothesis , within-session increase in power may relate to an increased D1 response impacting single unit and beta delay activity that modulate maintenance in the face of distractors and fatigue , thereby leading to an attentional effort effect . To our knowledge , within-session analysis of single-unit delay activity along similar lines is absent from the literature , but it will be the target of future study . On this basis , the increase in within-session effect under early MPTP lesion reported in Fig 7B might represent an augmentation of this effect , providing compensation for the lesion . Two observations from our study support this assertion . First , as the within-session effect in Fig 7B returns to baseline levels , at around 0 . 65 of full dose , so the cognitive control effect in Fig 5C begins to weaken . Second , the increase in within-session effect coincides with the increased DAT binding in the striatum ( and putatively cingulate cortex ) that we have associated with compensatory responses to the MPTP lesion [53] . Meanwhile , the lack of impairment on the task in terms of cognitive optimality suggests we are having little impact on D2 mediated processes within this lesion , in that D2 has been linked to updating processes necessary for adapting to changing problems [25] . Again , these speculative interpretations are the subjects of future study , but it is increasingly clear that careful dissection of motivational , motor , and cognitive deficits is an important future route for DA and PD research [71] . In PD and some progressive MPTP protocols , the lesion progresses dorsally to ventrally within the striatum [52 , 77] . This pattern of degeneration suggests greater impact on motor than cognitive functions , and has been linked to later development of cognitive symptoms and the ambivalent effects of dopaminergic medication on cognition [78] . Our behavioural results are consistent with this account in that we see no cognitive impairment before motor symptoms appear . They are inconsistent with previously reported premotor cognitive impairments [50 , 58–60] . But we record frontal neurophysiological changes early in the lesion and , in particular , FRP modulations prior to significant motor or cognitive symptoms . If these changes precede alterations of motor neurophysiology , they are incompatible with the dorsal-ventral account . We are unable to provide histology at each phase of the protocol to investigate lesion progress in terms of both pattern within striatum and impact on PFC and MCC . This would require sacrifice of a large number of animals . The measure that we recorded using PET ( DAT binding using radiotracer [11C]PE2I ) provided good indication of striatal DAT levels , but in cortex , DAT levels are low and only cingulate DAT binding was significant . We have confirmed that MPTP at this dose induces a putative compensatory increase in DAT , followed by a global loss of DAT binding once motor symptoms becomes significant [53] . Here we have revealed the dynamic of a multidirectional relationship between dopamine , motivation , and cognitive control over longitudinal dopamine depletion . Future work must focus on the extent to which these dynamics can be ascribed to the dopamine lesion itself or the compensatory processes combatting it .
Ethical permission was provided by “Comité d’Éthique Lyonnais pour les Neurosciences Expérimentales , ” CELYNE , C2EA #42 , ref: C2EA42-11-11-0402-004 . This permission endorsed our MPTP safety protocol , drawn from published NIH guidelines for all elements of MPTP use and housing of treated animals . Monkey housing and care was in accordance with European Community Council Directive ( 2010 ) and the Weatherall report , "The use of non-human primates in research . " Laboratory authorization was provided by the "Préfet de la Région Rhône-Alpes" and the "Directeur départemental de la protection des populations" under Permit Number: #A690290402 . This article has been written to comply with the ARRIVE guidelines for reporting animal research , and an ARRIVE checklist forms part of the supporting information . Two rhesus monkeys ( Macaca mulatta ) —Monkey R , a 17-y-old female weighing 7 kg , and Monkey S , a 16-year-old male weighing 8 . 5 kg—served as subjects . Monkeys were trained in a recording box , seated in a primate chair ( Crist Instrument Co . , Hagerstown , MD , USA ) and in front of a tangent touch-screen monitor ( Microtouch System , Methuen , MA , USA ) . An open window in front of the chair allowed them to use their preferred hand ( monkey R , left-handed; monkey S , right-handed ) . All elements of the task were controlled and recorded on a PC running the CORTEX software ( NIMH , Bethesda , MD , USA ) . Eye movements were monitored using an Iscan infrared system ( Iscan Inc . , Woburn , MA , USA ) . Electrophysiological data were recorded using an Alpha-Omega multichannel system ( Alpha Omega Engineering , Israel ) . We reported details of tasks and implantation of these monkeys in [23] , but reproduce important elements below . Each monkey received an implant consisting of a head-post and a grid of transcranial electrodes for ECoG recordings . We performed the implantation surgery in aseptic conditions . Monkeys received full anaesthetic along with appropriate antibiotic and analgesic treatments during and after the surgery , along with extensive monitoring . Details of the doses administered and further surgical detail can be found in [23] . We had previously acquired structural MRI images of each monkey , and we used these scans to guide the implantation location of the electrodes and to ensure consistent depth of insertion across electrodes . The MRI images provided us with stereotaxic coordinates at which we drilled individual holes through the skull . We then screwed stainless steel surgical screws ( Synthes ) into each hole , such that at each site the end contact point of the screw rested on the dura mater , acting as an ECoG electrode . The grid of electrodes was then soldered to a connector constructed in-house , to permit the daily recordings . The electrodes , connectors , and head-post ( Crist Instrument Company , USA ) were anchored together with dental acrylic . Schematics of the electrode grids can be seen in S1C Fig . Monkey R received a 5-mm-spaced grid of 14 electrodes over prefrontal cortex . This monkey then received a further eight electrodes over sensorimotor cortex and around the central sulcus in a second operation ( S1C Fig , left panel ) . Monkey S received a larger 7-mm-spaced grid of 31 electrodes in a single operation . Again , the implant covered the prefrontal and sensorimotor cortex ( S1C Fig , right panel ) . Finally , we implanted a single reference electrode in each monkey , in the form of an additional screw inserted into the think bone of the brow , on the midline and well anterior to the most anterior prefrontal electrodes . The BL period provided a baseline for all measures and allowed habituation to sham injections of MPTP . Sham injections were given at the end of each week , in exactly the same safe conditions as subsequent MPTP injections . Sham injections were 0 . 5 ml sterile water IM . The BL was , respectively , 46 and 55 d for monkeys R and S . The MPTP protocol was then induced . We employed a chronic low-dose protocol with injections of MPTP . Treatment consisted of i . m . injections of MPTP-HCl ( Sigma M0896 ) diluted in sterile water at 0 . 2 mg/kg . The aim of the protocol was to induce a dopaminergic system lesion modeling the slow rate envisioned in the premotor period of PD [51] , and to permit concurrent electrophysiological recordings . The protocol used a dosage of 0 . 2mg/kg , well established in progressive protocols of MPTP [49 , 50] , but delivered this dose and therefore attained symptoms much more slowly . MPTP injections were performed a maximum of once per week , at the end of a week of recordings , in the home cage , without prior sedation . Monkeys remained in the home cage for 72 h after each injection , with ad lib access to water and food , and were regularly monitored . There was both a safety aspect ( allowing time for the removal of MPP+ from the excreta ) and an experimental aspect ( avoiding any acute injection effects ) to this procedure . After this time , the monkey would resume work and recordings until the next injection . The typical schedule in this protocol was , therefore , as follows: work and recordings from Monday to Friday , MPTP injection Friday afternoon , recovery during the weekend , and restart of work the following Monday . We used the Parkinsonian Monkey Rating Scale , adapted from the UPDRS and compatible with rating scales used for monkeys [50 , 53 , 80 , 81] to score symptoms and judge the cessation of treatment . At least two authors and a colleague blind to the aims of the experiment scored monkeys through the week , giving weekly average scores . As previously , we used the motor subscale of the PMRS [50]: 0 = complete absence of motor symptoms; 1–5: pre-symptomatic , slight but observable symptoms; and 5 = clinical threshold , adjudged to be the equivalent of diagnosed symptoms in a human . The end of the MPTP period was when monkeys reached a score of 5 or more . In practice , both monkeys ceased to work for the task reliably in the week that their symptoms reached a score of 5 , so we considered only data up to and including the dose prior to this . The “full dose” period therefore refers to the sessions in the 3 weeks prior to the week during which monkeys reached a score of 5 ( Fig 3A , Monkey R 14 sessions , Monkey S 15 sessions ) . To test for acute effects in the week after injection , monkeys had regular “recovery” fortnights , during which the testing protocol continued in identical fashion , but there was no MPTP injection . These recoveries were spaced with decreasing frequency throughout the protocol: the number of weeks of MPTP injections between recovery weeks was as follows: 2 , 2 , 2 , 3 , 3 , 4 , 5 . After this , Monkey R completed the protocol , and Monkey S continued with 5 weeks of MPTP between recovery fortnights . Induction of symptoms up to the clinical motor threshold requires a significantly increased cumulative dose in slower , progressive protocols [50 , 51] . Our slow protocol is representative , as the cumulative dose required to bring monkeys to 5 on the PMRS was coherent with the previously observed range [50]; Monkey R required a cumulative “full dose” of 3 mg/kg , and Monkey S required 10 . 6 mg/kg . Importantly , the study brought both animals to symptomatically equivalent states as the functional endpoint of the protocol; both attained a clinical score on PMRS of 5 , and both ceased to work on the task at this point . From these functional points of view , therefore , the two cases can be considered comparable , and the pattern of PMRS scoring across the MPTP period up to full dose was highly comparable ( Fig 3A ) . Progression of the lesion is presented as the proportion of the cumulative “full dose , ” a proportion of zero referring to the BL period . Detailed descriptions of the PET protocol and analysis methods can be found in full in [53] . We reproduce the essential elements here . We obtained images from PET scans using ( E ) -N- ( 3-iodoprop-2-enyl ) -2beta-carbomethoxy-3beta- ( 4′-methylphenyl ) -nortropane labelled with carbon 11 ( [11C]PE2I ) throughout the protocol . [11C]PE2I has high affinity and selectivity to DAT and is used to index the integrity of the DA pathway [55 , 82] . We used an ECAT Exact HR+ tomograph ( Siemens CTI ) , in 3D acquisition mode , covering an axial distance of 15 . 2 cm . The trans-axial resolution of the reconstructed images was about 4 . 1 mm full-width and half maximum in the centre . Transmission scans were acquired with three rotating 68Ge sources . We anaesthetised monkeys with 15 mg/kg Zoletil ( Tiletamine & Zolazepam , Virbac , France ) after premedication with 0 . 1 mg/kg atropine sulphate , and placed them in the scanner in an MRI-compatible stereotaxic frame ( Kopf , CA , USA ) . We injected [11C]PE2I as a bolus followed by a saline flush through a cannula in the femoral vein . Radioactivity was measured in a series of 24 sequential time frames of increasing duration ( from 30 s to 10 min; total time 70 min ) . We used the anatomical-MRI and maximum probability atlas [57] to define 88 ROIs . Anatomical MRI acquisition was performed in a different session and consisted of a 3D anatomical T1-weighted sequence using a 1 . 5-T Siemens Magnetom scanner ( Siemens AG , Erlangen , Germany ) . The anatomical volume covered the whole brain with 0 . 6 mm cubic voxels . The registration and transformation process to allow extraction of regional PET time activity curves ( TACs ) of the 88 ROIs is described in detail in [53] , as is the quantification of regional [11C]PE2I non-displaceable binding potentials ( BPND ) . Because this procedure is semi-automated , we repeated it within and between two experimenters independently in order to account for within-measure variance . For each monkey , a PET scan was acquired in the BL period ( prior to MPTP ) as well as at regular intervals throughout , and once for each monkey during the 3-week “full dose” period . As in the previous study , cortical levels of [11C]PE2I-BPND were much lower than striatal levels , but the distributions of cortical and striatal DAT did overlap ( ranksum , p > 0 . 05 ) . These highest cortical DAT binding values were in the cingulate cortex ROI of [57] . Given the importance of ongoing recording of neurophysiology and cognitive performance to the protocol , and the necessity of anaesthetising the animals , PET scanning was limited to a single radioligand and to three to eight weekly intervals . Note that [11C]PE2I-BPND is a specific measure of the presence of the dopamine transporter , and cannot be considered as a direct index of dopamine levels . Note also that there are more PET scans for Monkey S as a result of the longer treatment period necessary to induce threshold symptoms . Future research on this topic will be required to link the neurophysiological and behavioural results here with more detailed consideration of cortical DA function under MPTP lesion . All statistical testing was performed within-monkey . During MPTP intoxication , we tested two results at each time-point throughout the lesion . First , we tested whether the measure in question had changed with respect to BL . To do this we used a non-parametric approach: we constructed a bootstrap distribution on the BL period data by resampling with replacement 10 , 000 times . Then we compared each MPTP period value with that bootstrap distribution . This bootstrap comparison is represented on the figures of the MPTP period as the statistical significance bars , as described in the figure legends . Second , we tested whether the measure in question still showed the same between-condition effect as reported for the BL period . For example , in Fig 3C we test whether the difference in RT between high and low control trials reported for the BL period is maintained at each time-point in the MPTP period . To do this we repeated the test applied in the BL at each time-point and then corrected for the multiple comparisons using a conservative Bonferroni approach . These statistics are presented in the results section . For the model coefficients in Figs 5 and 7 , the significant coefficients are shown on a solid line , whereas the non-significant coefficients are still shown for illustration , but on a dotted line ( notably in Fig 7 ) . Individual statistical approaches for the different electrophysiological analyses are described below . Electrodes were referenced to the frontal reference electrode ( S1 Fig ) . The signal was amplified and filtered ( 1–250 Hz ) , and digitized at 781 . 25 Hz . Data analysis was performed with FieldTrip toolbox [83] and in-house Matlab scripts ( Matlab , The MathWorks Inc . , USA ) . Movement artifacts were removed by decomposing ECoG recordings with an independent component analysis ( ICA ) using the logistic infomax algorithm [84] . For analysis of induced oscillations in the delay epoch , we aligned single trial data to the target onset ( ON signal ) , whilst for analysis of evoked responses to feedback we aligned to the onset of the visual feedback . In addition to the evident information being processed just after presentation of feedback , we focused on the delay epoch because this is when the monkey is integrating feedback information from the previous trial with preparation for the upcoming trial . It is therefore likely to be a moment of implementation of cognitive control [23] . All electrophysiological analyses were developed on data from BL and then applied to the data from MPTP treatment .
|
To successfully complete a task , we need to monitor our performance . If performance drops , we need to change our behaviour . We do this by adjusting cognitive control , an ensemble of processes through which behaviour is adapted to suit the task . In this study , we first used chronic recordings in the frontal lobe of macaque monkeys to characterise neurophysiological markers that reflect these processes: a brain potential reflecting performance monitoring and a sustained oscillatory signal reflecting cognitive control . It has been suggested that cognitive control , performance monitoring , and their neurophysiological markers are under the influence of dopamine . To understand how the input of dopamine is critical , we followed changes in the markers and performance during slow dopaminergic depletion . This protocol doubles up as a study of the early phase of Parkinson’s disease , when dopaminergic cells are dying but motor symptoms have yet to emerge . Whilst the performance monitoring potential attenuated at the end of the depletion , the performance itself did not . The oscillatory signals showed only subtle changes in comparison , despite the depletion . Together these results bring into question the simple idea that dopamine directly modulates frontal cortex , which in turn directly modulates cognition . We consider how the brain may compensate for a dopamine lesion , and whether the markers measure what we think they do . Our results question a current idea that neurophysiological markers can be directly used to predict dopamine loss in patients with conditions like Parkinson’s disease .
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2016
|
Prefrontal Markers and Cognitive Performance Are Dissociated during Progressive Dopamine Lesion
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Traditionally brain function is studied through measuring physiological responses in controlled sensory , motor , and cognitive paradigms . However , even at rest , in the absence of overt goal-directed behavior , collections of cortical regions consistently show temporally coherent activity . In humans , these resting state networks have been shown to greatly overlap with functional architectures present during consciously directed activity , which motivates the interpretation of rest activity as day dreaming , free association , stream of consciousness , and inner rehearsal . In monkeys , it has been shown though that similar coherent fluctuations are present during deep anesthesia when there is no consciousness . Here , we show that comparable resting state networks emerge from a stability analysis of the network dynamics using biologically realistic primate brain connectivity , although anatomical information alone does not identify the network . We specifically demonstrate that noise and time delays via propagation along connecting fibres are essential for the emergence of the coherent fluctuations of the default network . The spatiotemporal network dynamics evolves on multiple temporal scales and displays the intermittent neuroelectric oscillations in the fast frequency regimes , 1–100 Hz , commonly observed in electroencephalographic and magnetoencephalographic recordings , as well as the hemodynamic oscillations in the ultraslow regimes , <0 . 1 Hz , observed in functional magnetic resonance imaging . The combination of anatomical structure and time delays creates a space–time structure in which the neural noise enables the brain to explore various functional configurations representing its dynamic repertoire .
When subjects are not actively engaged in goal-directed mental activity , spontaneous brain activity has been suggested not to simply represent “noise” , but rather implicate spontaneous and transient processes involved in task-unrelated imagery and thought [1]–[9] . The resting state networks that are not associated with sensory or motor regions have been thought of as a “default-mode” network specific for the human and include medial prefrontal , parietal , and posterior and anterior cingulate cortices [4] , [5] . Recent results by Raichle and co-workers [10] showed similar networks in monkeys during deep anesthesia suggesting that this default-mode network is , first , not specific for the human and , second , that it transcends levels of consciousness . Furthermore , the assumption of a link between resting state activity and mental processes is founded largely “ex negativo” upon Positron Emission Tomography ( PET ) and fMRI studies showing the deactivation of the “default-mode” network in correlation with the increase in task-related activity in sensory-driven areas during goal-directed behavior . The dynamics of these spontaneous fluctuations evolves on a slow time scale of multiple seconds . On faster time scales of 10–500 ms , EEG and MEG identify characteristic oscillatory modes of brain activity showing transient spindle like behaviors , which repeat themselves intermittently . These wave patterns are strongly dominated by alpha waves ( 8–12 Hz ) when subjects have their eyes closed , and weaker but still clearly present for eyes open condition . In contrast to the well-studied phenomenology of alpha waves , no firm explanation exists regarding their genesis [11] . Similarly , since the first report of coherent rest state fluctuations observed in fMRI by Biswal et al . [1] more than 10 years ago , the mechanism for their generation remains poorly understood . Most hypotheses on the underlying mechanisms of rest state dynamics in the EEG/MEG consider alpha wave generation and postulate either of two hypotheses: pacemaker oscillators in the thalamus or cortex generate rhythms endogenously , which entrain the remainder of the cortex [12] , [13] . Alternatively , the neural resting state activity arises from the network interactions of the cortex and thalamus . For the latter hypothesis , the neuronal network may either act as a narrow band transmission system ( i . e . , as a filter originally proposed by Prast in 1949 [14] ) receiving white noise as input and producing the irregular rhythms; or the neural network generates a purely deterministic , often chaotic , signal reflecting the dynamics of coupled nonlinear oscillators [15]–[19] . All these computational models have some experimental support , but in general are too vague to pinpoint specific mechanisms . None of these models so far attempts to address the generation of the ultraslow oscillations observed in the fMRI . In a recent study by Honey et al . [20] , chaotic oscillators representing neural population activity were linked mimicking the connectivity of the macaque . When computing the corresponding hemodynamic response signal from their simulations , the authors were able to reconstruct inter-area correlations found experimentally in the fMRI . Though the temporal dynamics of the hemodynamic response appears realistic on the ultraslow scale , their generating neural network model does not attempt to model faster electrophysiological rhythms as observed in EEG and MEG recordings . From these attempts it is evident , that there is currently no satisfactory explanation of the various phenomena related to rest state activity on multiple scales . To shed light on the emergence of the resting state networks and their dynamics on various temporal scales , we performed a network simulation study in which the major ingredients were biologically realistic primate connectivity of brain areas , time delays via signal propagation between areas and noise . Our rationale is as follows: populations of neurons are dynamic systems capable of displaying oscillatory behavior . Imagine an isolated neural population that has no connections and is quiescent in the absence of noise . When noise is present , a fluctuation can perturb the population from its equilibrium state , to which it then returns in a characteristic transient manner . The latter transient will crucially depend on the “dynamic repertoire” of the population , which is the set of dynamic behaviors that a neural population can perform in the proximity of its equilibrium state . For instance , a damped mechanical pendulum is only capable of showing an oscillation with fixed frequency and exponentially decreasing amplitude following a perturbation , which defines its dynamic repertoire . Clearly , when neural populations are connected in a network , then the network connectivity will shape the dynamic repertoire of the entire network . Since the rest state networks are large scale networks distributed on spatial scales ranging up to almost 20 cm , the time delays via signal transmission between populations need to be considered . This can be understood intuitively along the following example: two systems shall oscillate in a synchronous fashion at 10 Hz . Their coupling shall be such that it reinforces synchronous in-phase oscillation when no signal transmission delay exists . If the delay increases to 50 ms , then the previously stable synchronous oscillation may become unstable , because the transmitted signal from one oscillator arrives now during the antiphase of the other oscillator . This example illustrates that the space-time structure of the couplings defined by the anatomical connectivity ( space ) and the time delays ( time ) will be the primary component shaping the dynamic repertoire of any large scale network . In the following we study these components systematically and evaluate their potential contributions to the emergence of rest state networks .
We first performed a graph theoretical analysis of the anatomical connectivity matrix of a single hemisphere obtained from the CoCoMac database [21] . Thus , we initially consider only the spatial aspect of the couplings . The connectivity matrix collated from macaque tracing studies comprises 38 nodes with weights ranging from 0 to 3 ( see Figure 1; see also Table 1 for abbreviations ) . The corresponding “Regional map” gives the translation between macaque and human neuroanatomy [22] . It is to be noted that some connections between some areas are not known . For the subsequent simulations we assign random weights to these unknowns within the range of 0 and 1 , but omit these in the graph theoretical analyses . The connectivity matrix is shown in Figure 1B , where the columns are targets and the rows are sources . To explore the connectivity characteristics quantitatively , we compute a set of network connectivity measures [20] , [23] for all nodes including the in- and out-degree of connectivity , the clustering coefficient and betweeness centrality ( see Methods ) are computed on the binarized graph , and are shown in Figure 1C . When computing these measures for the weighted graphs , no significant differences are found . If the putative components of the resting state networks ( see Table 2 ) differentiated themselves from other network nodes on the pure basis of anatomical connectivity , we would anticipate finding a clustering of these components in some of the graph theoretical measures , likely at the largest values . For better visualization , we use a color coding for the various components in Figure 1C . Anatomically , the prefrontal cortex is characterized by a large degree of afferent and efferent connectivity , whereas the temporal and medial parietal areas display only an intermediate degree of connectedness . Clustering index and betweeness centrality are commonly used to identify hubs in a network , but do not clearly differentiate the default network either , though the betweeness centrality measure shows a cluster of six components comprising prefrontal , parietal and cingulate cortices ( PFCCL , PFCVL , CCA , CCP , PCIP , PCI ) for midrange values . Based on this graph theoretical analysis , we find that pure anatomical connectivity of the large scale network does not suffice to reliably identify the network constituents during rest . To evaluate the temporal aspect of the couplings , i . e . , the time delays , we determine these as a function of the spatial position of a given brain area . More specifically , the time delay Δt between any two coupled network nodes is estimated as the ratio d/v , where d is Euclidean distance between two nodes in the three-dimensional physical space and v the propagation velocity along the connecting fibres . The node locations in physical space are chosen to mimic the human brain's geometry and distances based on a standard human atlas . As a consequence , the estimated time delay structure represents a lower estimate . Realistic fibre tracking would generally result in longer pathways than the here estimated shortest distance . Figure 2A illustrates the distribution of the Euclidean distances , which scale linearly with the time delay . The space–time structure of the couplings is illustrated in Figure 2B , in which the individual weights of the connectivity matrix are plotted as a function of the indices of brain areas and their time delay . The projection of all the entries onto the slice with time delay equal to zero yields the anatomical connectivity matrix . To explore the network dynamics supported by the given space-time structure , we perform simulations for finite signal transmission speeds and investigate the stability of its rest state . We place neuronal oscillators at each network node and couple these via time-delayed interaction terms ( see Methods ) . We have tested multiple oscillator types which are commonly used in neural population modeling including Hopf oscillators [24] , Wilson-Cowan systems [25] , FitzHugh-Nagumo systems [26] , [27] , and finally mixed populations of coupled FitzHugh-Nagumo neurons [28] , all of which provided similar results . Each population is characterized by a degree of excitability , in which the increase of excitation parameterizes the onset of oscillations emerging from a quiescent state . When the populations are embedded in a network , the network's dynamic repertoire will be shaped by the space-time structure of the couplings . To quantify the total connectivity strength , we introduce a parameter , c , which scales all connection strengths without altering the connection topology of the weight distribution of the matrix , nor affecting the associated time delays Δt = d/ν . Using this computational framework , we carry out the network simulations with initially identical neuronal population models at each node . The purpose of our simulations is the identification of the critical boundary , which separates the stable and unstable regions of the quiescent state in the parameter space of c and Δt . In its immediate proximity ( but still in the stable region ) , the effect of noise driving the network transiently out of its equilibrium state will be most prominent ( see Figure 3C for an illustration of the noise effect upon a single oscillator ) , and hence easiest to identify . Our results are plotted in Figure 3A , in which the degree of instability of the equilibrium state is plotted as a function of the connection strength , c , and propagation velocity , v . The degree of instability is quantified by the real part of the eigenvalue , Re[λ] , from a linear stability analysis of the network's equilibrium state ( see Methods ) . For small values of c , Re[λ]<0 denoting the parameter regions of stability of the equilibrium state , whereas for large values of c the network's equilibrium state is unstable , Re[λ]>0 , and displays oscillatory behavior . The two regions are separated by a critical boundary showing a characteristic shape ( Figure 3A ) , of which one segment is more prominent and coincides with the physiologically realistic range of propagation velocities around 5–20 m/s for the adult primate brain ( see points A and B in the cross section displayed in Figure 3B ) . Other points of biological interest ( from a clinical and developmental perspective ) in the parameter space are the regions indicated by C and D in Figure 3B , which correspond to the transmission speeds of unmyelinated axons , around 1–5 m/s . The emergence of coherent spontaneous fluctuations will be most likely observed in the neighborhood of the critical boundary , since farther away from the boundary all oscillations are either strongly damped or display high amplitude oscillatory behavior , which resembles pathological ( e . g . , epileptic ) activity . Before we proceed to an analysis of the network dynamics , we test the sensitivity of the critical boundary to manipulations of the network architecture in order to gain confidence in its validity ( see supplementary materials ) . To account for errors in the anatomical connectivity , we introduce a distribution of the connection weights , but preserve the general connection topology of the matrix . Further , the impact of parameter heterogeneity of the neuronal populations is assessed by introducing a distribution in their excitability . In all cases , the characteristic shape of the critical boundary ( see Figure 3B ) proves robust against surprisingly large variations ( Figure S7 – weight perturbations; Figure S8 – excitability parameter perturbations ) . However , when the network is rewired , i . e . , changing the connectivity without preserving its connection topology , then the critical boundary disintegrates rapidly ( Figure S9 ) . These findings show that the critical boundary displayed in Figure 3A and 3B may be generic for the connection topology of the primate connectivity matrix . To perform a spatiotemporal analysis of the network dynamics , we identify the dominating sub-networks involved in the ongoing transient oscillatory dynamics . We implement the network parameter settings according to point B close to the instability in Figure 3A . Results for other representative parameter settings are presented in the supplementary materials . Our challenge here is to extract the network nodes contributing the most variance to the network dynamics , because these nodes will be the most visible in experimental data . Mathematically speaking , we wish to identify a linear vector space spanned by n vectors ψk , where n is the dimension and typically smaller than the total dimension of the network ( in the present network the total dimension is 38 ) . These vectors span the directions of a subspace , in which the network is most sensitive to perturbations and noise . Equivalently , these vectors can be considered to be network patterns or network modes of operation . In this subspace most of the variance of the network dynamics is contained and define the dynamic repertoire of the sorts of the behaviors the network is capable to perform following a perturbation . In other words , the activity of the ith network node u ( i , t ) can be written as , where t is the time and ξk ( t ) is the time dependent coefficient capturing the dynamics of the kth network pattern ψk . The contribution of the ith network node is given by ψk ( i ) . To identify and quantify the contributions of the subspace , we perform the following procedure ( see Methods for details ) : When the network dynamics relaxes into its equilibrium state , we perform a small parameter change towards the unstable region . A typical time series plot is shown in Figure S1 . As a consequence of this minimal parameter change , the previously least stable network modes cross the critical boundary first , become unstable and grow with the fastest growth rate . The mathematical basis thereof is the center manifold theorem [29] . As a consequence , only the unstable network modes are present during the transition . Of course , after the transition the nonlinearities and all the network modes become relevant for the network dynamics . During the transition , though , we use a sliding temporal window analysis and perform a Principal Component Analysis ( PCA ) to identify the dominant network modes ( see Figure 4 ) . We find that only two network modes ψk contribute to the transient dynamics . The nodes of both networks ψk ( i ) are ordered according to power ( see Figure 4C ) . We find that prefrontal , parietal and cingulate cortices rank highest in this ordering scheme and hence contribute most to the two network patterns present during the transient of the instability . We confirm our findings by performing a complete computational network simulation with noise just below the critical boundary and verify that these sub-networks are most commonly present during the transient oscillations of rest state activity . Exemplary time series for the network nodes in the presence of noise are shown in Figure 4D and resemble the characteristic transient and spindle-like time courses with dominant frequencies of 8–12 Hz known from real human resting EEG [30] . To illustrate the spatiotemporal nature of the network dynamics during such an intermittent spindle , we plot a sequence of activation patterns in a cortical surface-based coordinate system for 240 ms in Figure 5 . To test for the emergence of ultra-slow oscillations in the hemodynamic response , we implement the Balloon-Windkessel model [31] and compute the blood oxygen level dependent ( BOLD ) signal for each of the 38 network nodes ( see Methods ) . A representative time series for the same parameter settings as in Figure 3 ( corresponding to point B in the parameter space ) is shown in Figure 6 . The BOLD time series and their power spectrum show clearly the presence of frequency components in the ultra-slow range of 0 . 1 Hz . A systematic increase of the transmission speed v and hence a reduction of the time delays in the space-time structure results in a reduction of the power in the ultra-slow frequency band . Since our PCA analysis of the neural network dynamics showed the presence of two dominating network patterns , ψk , we expect correlated and anti-correlated patterns of activity ( captured by the sign of ψk ( i ) ) on multiple scales , including the one of the BOLD signals . To test for the emergence of anti-correlated networks as reported in Fox et al . [3] , we compute the 38×38 cross correlation matrix of the BOLD signals ( see Figure 6 ) and find that mostly positive correlations are present amongst the dominant network nodes as identified in Figure 4 . , together with various anti-correlated nodes and networks comprising other regions . To perform a more detailed and semi-quantitative comparison with the Fox et al . study [3] , we reproduce their analysis . Fox and colleagues chose six predefined seed regions and computed the correlations against all other regions . The seed regions included three regions , referred to as task-positive regions , routinely exhibiting activity increases during task performance , and three regions , referred to as task-negative regions , routinely exhibiting activity decreases during task performance [3] . Task-positive regions were centered in the intraparietal sulcus ( IPS; in our notation: PCIP ( intraparietal sulcus cortex ) ) , the frontal eye field ( FEF ) region ( same in our notation ) , and the middle temporal region ( MT; in our notation this area is part of VACD ( dorsal anterior visual cortex ) ) . Task-negative regions were centered in the medial prefrontal cortex ( MPF; in our notation this area corresponds mostly to PFCM ( medial prefrontal cortex ) and to a lesser extent to PFCPOL ( prefrontal polar cortex ) ) , posterior cingulate precuneus ( PCC; in our notation CCP ( posterior cingulate cortex ) , but note that the precuneus comprises also our medial parietal cortex PCM ) , and lateral parietal cortex ( LP; in our notation PCI ( inferior parietal cortex ) ) . We compute the cross correlations of the seed regions from our simulated data set and illustrate our findings in a surface-based coordinate system in Figure 6 . For ease of comparison with the experimental findings in [3] we identify in Table 2 the sign of the cross correlations in experimental and simulated data . Since the cross correlation matrix is symmetric and the diagonal always positive , there remain 15 relevant cross correlations . Notably we find that all cross correlations except one ( PCIP-FEF ) have the same sign and hence show good correspondence between experimental and simulated data . To underscore further the importance of the transmission delays for biological realism , we perform the identical correlation analysis for a network with infinite transmission speeds ( see Figure S10 ) and find that the cross correlations break down as the transmission speed increases ( see Table S1 ) . In particular , out of 15 possible cross correlations , only 7 are captured correctly .
Various mechanisms for the genesis of rest state activity have been put forward including pacemaker oscillators [12] , [13] , filters [14] and emergent deterministic network dynamics [15]–[20] . The mechanism proposed in this paper lies in between the latter two: noise , omnipresent in any biological system , aids in the sampling of the flow in the vicinity of the brain network's stable equilibrium state . This sampling is reflected in the well-known waxing and waning of EEG and MEG waves during rest . In our computational model , the flow around the equilibrium state is captured by the emergent large scale network dynamics; more specifically , we have demonstrated that the space-time structure of the network's connectivity shapes the flow and actually gives rise to the emergence of coherent fluctuations on a wide range of scales from the ultra slow range <0 . 1 Hz to high frequencies <100 Hz . To strengthen evidence that the temporal aspect of the couplings does shape the spatiotemporal dynamics , we scrambled the original time delays under preservation of the actual delay values . The actual spatial aspect of the couplings , i . e . , the anatomical connectivity , was kept constant . When performing the same sliding window analysis leading to the results in Figure 5 , the resulting emergent networks show different spatial configurations ( see Figure S2 for a particular example of scrambled temporal couplings ) . Different scrambling always results in different emergent network configurations . Furthermore , in a network of identical neuronal populations with instantaneous couplings ( no time delay ) , the anatomical connectivity is the only distinguishing factor amongst the nodes and hence determines the network dynamics . This is illustrated in Figure S3 , where the emergent network dynamics is dominated by the area PFCORB . For increasing values of propagation velocity , v , the rest state networks engage the parietal and cingulate areas for v = 5–10 m/s ( Figure 4 and Figure S4 ) ; upon further decrease of velocity to v = 1 m/s ( points C , D in stability diagram Figure 3B ) corresponding to unmyelinated fiber transmission speeds , the rest state networks disengage the parietal components and a set of prefrontal areas is distinctly active ( Figure S5 and Figure S6 ) . In the various scenarios considered here , the prefrontal areas generally show the largest contributions due to their large degree of connectivity . It shows that the temporal aspects of the coupling will never override the anatomical connectivity , however , as the temporal aspects of the couplings vary , the relative contributions of the nodes change . These changes in the spatial configuration of the resting-state patterns as a function of transmission speed suggest relevance for development and potentially have clinical implications in diseases , in which degradation of myelination is involved . Recent research on rest state activity in infants establishes a partial overlap of the rest state networks with the counterparts in adults , however with an absent component along the posterior-anterior direction [32] . In the adult brain resting-state activity shows a functional correlation both across hemispheres and across brain regions that are spatially separated along the anterior–posterior direction [3] , [5] , [33] . Our findings regarding the reorganization of the space-time structure of the connectivity explain the difference in spatial network configurations . Indirect anatomical support for our hypothesis is also provided by diffusion tensor MR imaging studies , which revealed a significantly lower anisotropy index in the inferior longitudinal fasciculus , inferior fronto-occipital fasciculus , and superior longitudinal fasciculus compared with the detected degree of anisotropy in the interhemispheric callosal fibers [34] . These findings suggest that the white matter tracts supporting functional connectivity in the anterior–posterior direction are less well developed in the infant brain than the tracts supporting transcallosal functional connectivity [35] . It is worth to reemphasize that our results are obtained for a range of conduction velocities that is in the physiological range . The parameters of the neural population model at each node are constrained to a range to reflect a biologically realistic dynamics in response to a single stimulus . This constraint determines the temporal scale , whereas the spatial scale follows from the locations of the network nodes in the three-dimensional physical space ( see Methods ) . As a consequence , the spatiotemporal scales for the resting state dynamics are fixed within a certain range and the freedom for parameter adjustment is limited . Does it mean that the physiologically observed conduction delays have been somehow selected during development to generate appropriate resting state dynamics ? At this stage , the answer is not obvious . Here we showed that the inclusion of time delays into the space-time structure of the connectivity results in the recruitment of parietal and cingulate cortex for biologically realistic transmission speeds . In contrast , Honey et al . [20] introduced an increased degree of complexity into their network model by utilizing a chaotic dynamics for the brain areas . Their connectivity is also based on biologically realistic primate ( though limited to visual and sensorimotor ) connectivity , but their assumed transmission speeds are infinite resulting in instantaneous communication within the network . In this configuration , the authors identify BOLD network activations which favorably compare to characteristic rest state networks . Hence the question arises , whether we really need to consider time delays on the order of 10–100 ms when studying BOLD signal fluctuations on the order of <0 . 1 Hz . After all it would be a computationally most desirable simplification if the time delays could be neglected , since network computations involving time delays are numerically costly . However , since the BOLD signal ( in our current understanding of the neurovascular coupling ) is generated by the local neural dynamics , which itself evolves on multiple scales including the time scale of signal transmission between areas , neglecting the time delay does not seem permissible . In other words , it is not the BOLD signals on the slow time scale that interact with each other across areas ( in which case the neglect of time delay would be justified ) , but the neural signals evolving on faster time scales . Neither does the chaoticity of the network nodes in Honey et al . [20] substitute for the time delays , but rather introduces another component to a network's node dynamics which we did not address . Our findings hold strictly only if the network nodes display damped oscillatory dynamics in absence of connectivity . In conclusion , we have demonstrated that the space–time structure of the couplings between brain areas plays a critical role in the functional organization of the emergent network dynamics at rest . On this basis and in the presence of noise , the genesis of a variety of rest state dynamic phenomena including multi-scale oscillations , spatial configurations of networks and some effects of developmental changes can be understood .
We quantified the anatomical connectivity using graph theoretical measures [23] where the in-degree and out-degree are the number of incoming and outgoing connections to/from a node . The degree is the sum of in- and out-degree . The clustering coefficient is the number of all existing connections between a node's neighbors divided by all such possible connections . The betweeness centrality is the fraction of the shortest path between any two pairs of nodes passing through a particular node . The network model with the coupling term of strength c is implemented as: ( 1 ) where ui , νi are the state variables of the ith neural population and fij is the connectivity matrix . White Gaussian noise nu ( t ) , nν ( t ) is introduced additively . The functions g and h are based on FitzHugh-Nagumo systems [26] , [27] with and h ( ui , νi ) = − ( 1/τ ) [ui−α+bνi] , and α = 1 . 05 , β = 0 . 2 , γ = 1 . 0 , τ = 1 . 25 . For the stability analysis ( no noise ) we employed Matlab DDE23 to solve the coupled delay differential equations . The coupled delay differential equations with additive noise were solved in Matlab by a simplified and faster algorithm . More specifically , we employed a standard fourth order Runge-Kutta method for integrating the intrinsic Fitz-Hugh Nagumo dynamics while the coupling and the stochastic terms were integrated using Euler method . The step size for the simulation was 0 . 001 and we confirmed that no better convergence of solution was achieved using smaller step sizes to ensure numerical convergence . The time delays are computed from the Euclidean distance matrix dij of the locations of the brain areas i and j . To do so , the three-dimensional regional map locations were converted to approximate Talairach stereotaxic atlas locations by first identifying the mapping of regional map locations as designated on the human brain to the anatomical locations in Talairach space using the Anatomical Automatic Labeling ( AAL ) image provided by Tzourio-Mazoyer et al . [36] . Once the approximate location was identified in the AAL brain , the coordinate for the centre of the AAL region was used for the location of the corresponding regional map location . Each region was represented as a surface composed of a sufficient number of triangles . To obtain the triangulation , a T1-weighted MR image from a single human subject was segmented in grey and white matter compartments and the cortical surface represented as a triangular net using the CURRY software package ( Compumedics Neuroscan , Ltd ) . The T1 image was co-registered to a standard MRI atlas ( MNI305 , [37] ) using a 12-parameter affine transform with sinc interpolation as implemented in SPM99 ( see http://www . fil . ion . ucl . ac . uk/spm/ and [38] ) . The transform matrix from the co-registration was then applied to the triangulated cortical surface to the MRI atlas . The stability diagram for the network in Equation ( 1 ) is obtained by linear stability analysis leading to the characteristic equationwhere ū is the fixed point solution . The eigenvalue λ has 2N non-trivial roots withThe equilibrium state is stable if all eigenvalues λ have negative real parts , Re ( λ ) <0 , which were found numerically . The stability diagrams in Figure 3 were constructed using this procedure . We also cross-validated the presence of negative real parts of the eigenvalues by direct numerical simulations of Equation 1 . We obtain activity at different areas by simulating Equation 1 for parameter values indicated in the stability diagram . The parameters are chosen to lie on or just below the critical boundary of stable and unstable regions . Network data are simulated for numerical values of parameters in the stable region . Once the network dynamics settles into its equilibrium state ( see Figure S1 ) , the coupling parameter c is increased just beyond the critical boundary . We use the smallest increase of c possible given the discretization of the parameter space . As a consequence , now in the unstable regime , the network dynamics increases towards high-amplitude oscillations . A typical time series plot is shown in Figure S1 . Using a sliding temporal window of 500 ms width , we perform a Principal Component Analysis ( PCA ) during the transient as the oscillations increase . The local Center Manifold Theorem guarantees that the network modes with the largest positive real part of the eigenvalue grow fastest and hence dominate the transient initially . Hence , the eigenvectors of PCA span a linear vector space , in which the dominant network modes will be represented . In other words , the networks implicated in rest state activity will be a linear superposition of the PCA eigenvectors . Then the spatiotemporal data can be decomposed as:where the kth PCA eigenvector ψk spans a spatial network . During all transients observed in our simulations , the first two PCA eigenvectors contribute together at least 99 . 995 percent ( see Figure 4B ) . Hence it does suffice to represent the entire transient dynamics by the first two PCA eigenvectors . Since , in a given PCA eigenvector ψk , each node is multiplied by the same time-dependent coefficient ξk ( t ) , the magnitude of the ith vector element will scale the resulting contribution of the ith node to the network dynamics . The most dominant nodes of these two networks ψk ( i ) are then identified through an ordering process: we compute ψk ( i ) 2 for all nodes i and both network modes k = 1 , 2 and order these according to power ( see for instance Figure 4C ) . There is no hard criterion to identify a threshold for the inclusion of nodes in a network . For reasons of clarity , we choose to show the first three dominating nodes for each eigenvector in Figure 4A , which corresponds to at least 90% of the power per eigenvector in all cases . To relate the simulated neural activity to recent fMRI studies , we have generated BOLD signal for each regions by using a hemodynamic model . This model combines the Balloon/Windkessel model comprised in venous volume and deoxyhemoglobin content with a linear dynamical model of how synaptic activity causes changes in regional cerebral blood flow [31] . For each region , neural activity causes an increase in a vasodilatory signal inducing blood flow , which changes blood volume and deoxyhemoglobin content . The BOLD signal is given by a volume-weighted sum of extra- and intra vascular signals as the function of volume and deoxyhemoglobin content . The local neural activity , which is taken to be the absolute value of the time derivative of the output occurring by our network model in each brain region , is used as the main model input to estimate a BOLD signal . For the analyses , the global mean signal ( average over all regions ) has been regressed out from the single BOLD time series . All parameters regarding blood flow , deoxyhemoglobin content , and vessel volume in the model equation are taken from [31] .
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There has been a great deal of interest generated by the observation of resting-state or “default-mode” networks in the human brain . These networks seem to be most engaged when persons are not involved in overt goal-directed behavior . These networks are also thought to underlie certain aspects of conscious introspection and to be specific to humans . Our paper provides a new explanation for rest state fluctuations by suggesting that they reflect a deeper biological principle of organization and are a consequence of the space–time structure of primate anatomical connectivity . In a computational study using a biologically realistic primate cortical connectivity matrix , we show that the rest state networks emerge only if the time delays of signal transmission between brain areas are considered . The combination of anatomical structure and time delays creates a space–time structure in which the neural noise enables the brain to explore various functional configurations representing its dynamic repertoire . The latter repertoire spans temporal scales of multiple orders of magnitude including scales observed in electric potentials and magnetic fields on the scalp , as well as in blood flow signals . Our results provide a testable explanation of the real-world phenomenon of rest state fluctuations in the primate brain .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"neuroscience/theoretical",
"neuroscience"
] |
2008
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Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire
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Dendrites form predominantly binary trees that are exquisitely embedded in the networks of the brain . While neuronal computation is known to depend on the morphology of dendrites , their underlying topological blueprint remains unknown . Here , we used a centripetal branch ordering scheme originally developed to describe river networks—the Horton-Strahler order ( SO ) –to examine hierarchical relationships of branching statistics in reconstructed and model dendritic trees . We report on a number of universal topological relationships with SO that are true for all binary trees and distinguish those from SO-sorted metric measures that appear to be cell type-specific . The latter are therefore potential new candidates for categorising dendritic tree structures . Interestingly , we find a faithful correlation of branch diameters with centripetal branch orders , indicating a possible functional importance of SO for dendritic morphology and growth . Also , simulated local voltage responses to synaptic inputs are strongly correlated with SO . In summary , our study identifies important SO-dependent measures in dendritic morphology that are relevant for neural function while at the same time it describes other relationships that are universal for all dendrites .
Neurons of the central nervous system have a variety of shapes and possess dendritic trees that exhibit complex branching patterns . Apart from providing neurons with adequate connectivity , dendritic trees are not just simple passive signal conductors but are thought to be involved in sophisticated signal processing and neural computation [1 , 2] . Theoretical studies have suggested that dendritic morphology alone is able to influence a neuron's functional properties such as its firing patterns [3 , 4] . In particular , the topology of dendrites has been associated with strong effects on the temporal structure in the spiking behaviour [5 , 6] . Furthermore , the size of a neuron's dendritic tree , its diameter and its branching properties are all factors that influence the decay of synaptic signals on their way to the soma [7 , 8] . Understanding the principles governing dendrite morphology is therefore important for understanding neural computation . In order to better characterise and quantify dendritic branching structure , a number of branching statistics have been proposed [9 , 10] . Yet , these quantities exhibit strong correlations that are mostly unexplored [11] . Even when taken together , a commonly used set of existing branching statistics is not sufficient to cluster morphologies according to their given cell types [12] . In the following , we explore how sorting branching statistics by the precise order of the occurrence of nodes in a tree can increase the interpretative power of these statistical measures . Different methods have been developed to sort branches in dendrites . They mainly divide into those that start ordering the branches from the root , i . e . at the soma ( centrifugal ) , and those that start from the terminal branches ( centripetal ) [13] . The centrifugal branch ordering method assigns a lowest order of 0 ( or 1 depending on the definition ) to the root , and increases the order by 1 at each branch point . Centrifugal branch ordering has found common use in many tree-like structures and has been specifically applied to dendritic trees on many occasions [14–20] . Among others , the maximum and mean branch order of dendritic trees have been used to measure dendritic tree complexity [21] . Centripetal ordering schemes , on the other hand , have become increasingly common in recent years and we focus here on the so-called Horton-Strahler or Strahler order ( SO ) , which was originally developed by Robert E . Horton as a stream ordering method for river networks [22] . This scheme was later refined and slightly modified to be objectively quantifiable by Arthur N . Strahler [23] . In Strahler's version , which we use in this study , all terminal branches are assigned order 1 . The remaining orders are then constructed in an iterative way: When two branches of order k meet , the order of the parent branch is increased to order k + 1 . When two branches of different order meet , the higher order prevails ( see Fig 1A ) . The highest order of the tree always occurs at the root of the tree . The Strahler order of the root ( or the maximal Strahler order assigned to a segment in the tree ) is referred to as the Strahler number ( SN ) of the tree . While SO started out in the field of geology as a stream classification scheme for river networks , it has since found use in many other scientific fields . For example , SO has been employed to quantitatively describe other tree-like structures such as bronchial trees or pulmonary arteries [24–27] , as well as actual botanical trees [28–30] . Yet , it is important to note that certain findings that have been reported using Strahler orders have little descriptive power if the underlying structure is a binary tree . Most prominently this applies to the so-called “Horton’s law of stream numbers” [22] , a power law between the counts of branches of a given SO and the SO itself . The slope of this distribution corresponds to the tree’s overall bifurcation ratio ( i . e . the ratio of the number of branches between any two consecutive orders ) . This power law asymptotically approaches 41−k for SO k [31] and the corresponding bifurcation ratio converges to 4 [32 , 33] . The fact that its descriptive power is weak was only discovered much later in the 1990s using Monte Carlo methods [34] . These findings caused some discussions in the field and , interestingly , seem to be less known to the scientific community outside of hydrology . We will therefore comment on them in the following and distinguish results that are close to the expected case from ones carrying more descriptive power . To our knowledge , Strahler’s method was first applied to the analysis of neuronal morphologies by Hollingworth and Berry , who used it to quantify and compare the branching structures of Purkinje and pyramidal cell dendrites in rats [35] . Later it was used to analyse the growth patterns of axons in cat visual cortex [36] . In recent years , SO also became popular as a measure of branching complexity in Drosophila dendritic arborisation ( da ) neurons of different classes [37–42] . Despite its wide applicability and relative simplicity , SO has not been studied in detail especially in relation to larger samples of neuronal cell types . Hence , this study uses Strahler's centripetal branch ordering method to investigate and describe the morphology of a variety of reconstructions of real dendrites as well as of synthetic model dendrites . We observe that other SO-sorted distributions of topological measures apart from Horton’s law are also nearly invariant to cell types and reflect universal features of binary trees . However , the metric measures that we studied exhibit differences between distinct cell types and may thus be used to quantify , categorise and better understand dendritic tree structure .
Topological measures of dendritic trees can be calculated without any metric information , simply by analysing the succession of branch points ( BPs ) and termination points ( TPs ) in the tree . In the following , we first describe topological relationships with Strahler order ( SO ) while distinguishing between either segments ( from BP—BP or BP—TP ) or branches ( consecutive segments ) of a given SO k ( Fig 1B ) . In order to better interpret results from SO-sorted relationships in dendritic trees , we first obtained results from the set of all possible binary trees with a given number of nodes ( Fig 2A–2E ) . After calculating all unsorted binary trees with 16 terminal nodes , we also calculated the reduced set of all sorted binary trees in which the ordering of subtrees at each node is discarded by allowing permutations at all BPs to identify topologically equivalent trees ( see Methods; the two trees in the green box in Fig 2A are topologically equivalent since they can be transferred into one another by rotations of subtrees ) . For such small trees ( enumerating this set quickly becomes computationally expensive for larger trees as it grows exponentially with tree size ) that are typical for some real dendrites ( e . g . dentate gyrus granule cells ) , the distributions of SO-sorted segments ( Fig 2B ) and branches ( Fig 2C ) could vary widely in different binary trees . At one extreme , the so-called “herringbone” tree that is maximally asymmetric ( Fig 2A , sample trees in the green box ) showed a flat line with SO-sorted segment number ( Fig 2B , green bold line ) with SO values restricted to 1 and 2 . At the other extreme , the complete binary tree ( CBT ) , which is completely filled with nodes on every level ( Fig 2A , sample tree in the magenta box ) , doubled the number of nodes at every step that decreased SO , leading to a 2−k trend ( Fig 2B , magenta bold line ) . By contrast , the mean values for these distributions ( Fig 2D and 2E ) followed much clearer trends . With increasing SN ( the maximal SO assigned to a segment in the tree ) , the average number of segments per SO for all possible trees of degree 16 was well described by the same 2−k trend predicted by the complete binary tree ( Fig 2D , magenta dashed line ) . This is partly explained by the fact that we grouped trees according to their SN: Maximally asymmetric herringbone trees are characterised by an SN of 2 . By contrast , symmetric CBTs exhibit maximal SN values for their respective number of nodes with distributions of 2−k . Asymmetric trees naturally have lower SN values , therefore groups of trees with larger SN will be more symmetric and behave more like the complete binary tree . The possible distributions for the number of branches per SO also varied widely ( Fig 2C ) while the averages ( Fig 2E ) tended to a specific trend , in this case 41−k ( Fig 2E , grey dashed line ) . This is a consequence of Horton’s law and the 41−k power described in the introduction . Generally , their topology has previously linked dendritic trees to certain classes of random binary trees [43] . We therefore compared our results from the set of all possible binary trees of degree 16 with a set of random trees produced by a critical Galton-Watson ( GW ) random branching process [44] that generates a distribution of trees of different sizes ( Fig 2F ) . Such a GW process has been used in the past to generate a number of topologically distinct binary trees and to model dendrite branching patterns [45] . We obtained a large number of GW binary trees by randomly choosing to either terminate or branch further at every new terminal node in an iterative manner . The branching process was terminated when no further branching occurred or when a total number of 800 nodes was reached . The number of segments distribution grouped by SN ( Fig 2G ) again followed the 2−k trend that would be expected for the CBT and was very similar to that seen in Fig 2D ( see above ) . As expected from Kirchner [34] , the number of branches per SO ( Fig 2H ) tightly approximated the same relationship as observed for all possible binary trees of degree 16 ( Fig 2E ) . Due to the larger magnitude of GW random binary trees compared to the set of all possible binary trees of degree 16 , the trends were much more pronounced . The 41−k trend in SO-sorted branch numbers can further be observed in the branch bifurcation ratios ( Fig 2I ) , a related topological measure that compares the number of branches of SO k with that of the next higher order k + 1 . Since bifurcations do not allow ratios lower than 2 , this lower limit value is true for the CBT where SO increases at every single branch point ( Fig 2I , magenta line; see also Fig 2C where the line is an upper bound ) . In this representation , most data points are evenly scattered around the average bifurcation ratio of 4 ( coefficient of determination R2 = 0 . 9925 ) , the asymptotic bifurcation ratio calculated previously for a large number of nodes [32–34] ( see Discussion ) . Finally , we studied the topological subtree sizes capturing the number of daughter BPs and TPs for all BPs of a given SO in our GW random binary trees ( Fig 2J ) . Since all nodes with SO 1 are TPs , the values here start at SO 2 . We found an exponential increase in subtree size with SO that was not well described by the topological subtree sizes expected for a CBT ( Fig 2J , magenta dashed line , root node SN 6 ) but was rather well approximated by 4k−SN ( Fig 2J , grey dashed line shown for all segment SN values ) , a mirror image of the relation that we found for the number of branches . Since dendrites serve the particular purpose of network connectivity , we investigated how their resulting branching pattern distributions compare to those of random binary trees . We have previously introduced a minimum spanning tree ( MST ) based growth algorithm that connects a set of target points to generate synthetic dendrites . Meeting the requirements for dendritic connectivity , such MST-based model trees guarantee short total dendritic lengths and with one parameter , the balancing factor ( bf ) , also increasingly prohibit long paths along the tree towards the root to reduce conduction times in the neural circuit [46] . When the resulting synthetic dendrites are restricted to binary trees by ruling out more than two daughter branches at a branch point , MST-based model trees represent a specialised , optimally-wired distribution over the set of all possible binary trees: Since they are grown on the basis of random target points distributed within a specific area , they rely on metric information to produce the resulting topology . For this reason , the binary trees resulting from the MST process might be distributed in a highly selective manner . In order to test this , we examined two-dimensional circular morphologies that varied the two parameters bf and the number of target points ( in order to obtain trees of SN 3–6 , see Methods for details; Fig 3A ) . The results for such MST-based model trees were similar to the set of all possible binary trees of degree 16 and the GW random binary trees ( Fig 3B–3E ) , indicating that the specific sample of binary trees that perform optimal wiring is not easily distinguishable from a set of random trees by the SO-based metrics we used here . The branch bifurcation ratio ( Fig 3D ) in MST-based model trees was also tightly scattered around a ratio of 4 ( R2 = 0 . 9814 , over all trees ) in agreement with the results from the random binary Galton-Watson model trees . Overall , bf 0 –the pure minimum spanning tree—seemed to be a special case potentially because it represents the least symmetric tree . We then investigated the same topological measures in six real reconstructed dendrite types ( Fig 4A ) and found that they , too , behaved very much like the binary tree models shown above ( Fig 4B–4E ) . Firstly , the normalised number of segments per SO approximated 2−k for SO k ( Fig 4B ) with a slope between -0 . 89 and -1 . 20 for a fit by linear regression in binary logarithmic space in the six groups of reconstructed dendrites ( R2 > 0 . 9686 for slope fits in all groups ) . Secondly , the expected invariance of the SO-sorted number of branches matching a 41−k decay for SO k ( Fig 4C ) was pronounced and we found linear slopes ranging from -0 . 45 to -0 . 54 in the log10 scale ( R2 > 0 . 996 for slope fits in all groups ) . Thirdly , the bifurcation ratios for reconstructions of real dendrites ( Fig 4D ) exhibited linear regression slopes varying between 2 . 23 for dentate gyrus granule cells and 3 . 77 for lobula plate tangential cells ( LPTCs; Table 1 ) , and the fit for all lumped data was 3 . 44 . However , the coefficient of determination for a fit of 4 was R2 = 0 . 9387 . Finally , the subtree sizes distributions ( Fig 4E ) followed the 4k−SN increase with SO k observed previously , with linear slopes on the logarithmic average data ranging from 0 . 54 to 0 . 65 ( R2 > 0 . 9898 for slope fits in all cases ) . Taken together , these analyses show that the SO-sorted topological measures yielded very similar distributions over a wide range of possible binary tree samples including all real dendritic trees , rendering these measures unsuitable for morphological classification , cf . [34] . Dendritic trees in the brain are embedded in 3D tissue , adding metric information such as X , Y and Z coordinates as well as diameter values to the nodes in their tree structures that are not captured by the topologies of abstract binary trees . While any local branching statistics could exhibit interesting relationships with SO , we focused on the distributions of total dendritic length , mean segment lengths , mean branch lengths , and branch diameters , as well as basic passive electrotonic properties . The amount of total dendritic length as a function of SO followed an approximately exponential decay for all reconstructed dendrite types that we analysed , as seen by straight lines in the semi-logarithmic plots ( Fig 5B ) . However , the slope of the decay was clearly different for dendrites of various types: The decay was slower for planar , 2D morphologies ( e . g . LPTCs , Purkinje cells ) , for which 50–60% of the total dendritic length was SO 1 ( terminal segment or branch length ) . By contrast , the decay was faster in 3D morphologies such as dentate gyrus granule cell dendrites and basal pyramidal dendrites with the combined terminal branch length making up more than 80% of the total wiring length . Linear regression fits on the semi-logarithmic data yielded slope values between -0 . 31 and -0 . 76 ( R2 > 0 . 9892 in all cases ) . Normalised mean segment length distributions with SO also varied pronouncedly with cell type ( Fig 5C ) . Mean segment lengths in planar lobula plate tangential cell ( LPTC ) dendrites and Purkinje cells were nearly constant over all SOs . By contrast , the distributions for 3D cells featured longer mean segment lengths in the terminals , followed by a rapid decrease over the remaining SOs in dentate granule cells ( linear regression fit slope -0 . 45 , R2 = 0 . 9996 ) , basal pyramidal dendrites ( -0 . 43 , R2 = 0 . 9894 ) , apical pyramidal trees ( -0 . 23 , R2 = 0 . 9748 ) , and motoneurons ( -0 . 17 , R2 = 0 . 9995 ) . SO-sorted distributions of mean branch lengths varied even more strongly between different dendrite types ( Fig 5D ) . Some distributions increased exponentially with SO up until a certain point; e . g . Purkinje cells and LPTCs ( exponential increase until their peak in the second-to-last order with linear regression slopes in logarithmic space of 0 . 18 and 0 . 30 , respectively; R2 = 0 . 9766 and R2 = 0 . 9978 ) . Others decreased exponentially ( granule cells -0 . 32 , R2 = 0 . 9805 , basal pyramidal dendrites -0 . 33 , R2 = 0 . 9999 ) , and yet others still were nearly constant ( motoneuron dendrites and apical pyramidal dendrites ) . In order to understand which features of the dendritic geometry led to the differences that we observed in SO-sorted metric measures , we designed simple MST-based model trees that reproduced the properties observed in Fig 5 ( Fig 6 ) . The MST results depended strongly on the spatial distribution of the target points that were to be optimally connected . We matched the results for SO-sorted measures seen in real dendrites by modulating basic parameters of the MST model such as hull shape , root node location , balancing factor bf , number of target points pts and the mode of target point distribution ( Fig 6A , bottom row; Table 2 ) . The slope of exponential decay observed previously for SO-sorted total dendritic length ( Fig 5B ) was replicated when using 2D vs 3D spanning hulls for the MST-generated trees ( Fig 6B ) . However , the details of the distributions were not entirely captured in the 2D models ( LPTC and Purkinje cell models ) , indicating that potentially more complex features of morphology determine the traits observed in Fig 5B . Both the nearly constant mean segment length distribution seen in LPTCs and Purkinje cells ( Fig 6C ) and the more complex relationships of branch length distributions there as well as in motoneurons and apical dendrites of pyramidal cells ( Fig 6D ) could be replicated easily by geometric adjustments to the MST models . However , granule cell and basal pyramidal dendrites with their similar distributions in Fig 5 required precise reconstruction also of the inhomogeneous quadratic target point density along the height of the cone in which the MST-based model trees were grown ( Fig 6A , violet model ) . Even then , the model did not capture the exponential decrease of segment and branch length seen in Fig 5C and 5D very well . These findings suggest that complex cell type-specific differences in the geometry of the growth process determine the different SO-sorted distributions of metric branching statistics that we observed in Fig 5 . It is well known that terminal segments of dendritic trees exhibit the smallest diameters [8 , 47 , 48] and that this contributes to the local input resistance being highest there [47 , 49] . At the same time , even short branches in close proximity to the soma typically reach the smallest diameters , suggesting a centripetal increase in diameter rather than a regular taper away from the root . In the following , we investigate a potential relationship between SO and these features that are expected to be important for neuronal computation . The relationship between diameters and SO was striking and followed a similar trend in all cell types ( Fig 7A ) . This increase of diameters with SO would be consistent with quadratic fits ( R2 > 0 . 9956 for all morphologies ) , which is in agreement with our predictions that quadratic tapers optimise current transfer in dendritic trees [8 , 47] . Since we showed that SO correlated with subtree sizes ( Fig 4E ) it was not surprising that diameters also weakly correlated with subtree sizes ( Fig 7B ) . As mentioned above , local diameter values are influential in the processing of synaptic inputs and small diameters result in large local input resistances with strong voltage deflections for a given synaptic input . Additionally , electrotonic properties depend in part on dendritic topology [5 , 6 , 50] . We therefore also analysed simulated voltage responses to small steady-state synaptic currents ( 10 pA ) in passive entire dendrites ( see Methods ) and indeed found strong relationships with SO ( Fig 8A for Purkinje cells with different passive properties and Fig 8B for the different cell types and their respective passive properties ) . Interestingly , all cell types apart from Purkinje cells exhibited strong relationships with SO . This matches well with our previous finding that diameters in Purkinje cells were not optimised to transfer currents to the root [8] and could indicate a particular functional role of the Purkinje cell dendrite that is to date not understood .
Regardless of the method used to select samples out of the set of all binary trees , whether it was the average of all sorted or unsorted binary trees , randomly selected binary trees , or trees that guaranteed optimal wiring ( MST-based model trees ) , we found that the relationships between topological measures and SO followed universal trends . This was also the case for all dendritic trees we studied , independently of cell type , and spanned measures from branch numbers distributions and bifurcation ratios to distributions of segment numbers and subtree sizes . As mentioned above , it has previously been shown analytically that the mean number of branches of a given Strahler order k in random binary trees asymptotically tends to 41−k as the number of terminals goes to infinity [31] , with a corresponding overall bifurcation ratio of 4 [32 , 33] . Additionally , most binary trees lie close to a bifurcation ratio of 4 [34] , and it has been suggested that it is inherent to the definition of Strahler order that no binary tree can depart indefinitely far from this branch number power law [51] . In fact , Van Pelt et al . [52] have shown that there are only a few unique values that the overall branch bifurcation ratio ( i . e . , the averaged ratio between the number of branches of any two successive SOs ) can take for the set of all possible binary trees of a given size ( e . g . 7 unique values for the 98 sorted possible binary trees of degree 10 , or 18 unique values for the 10 , 905 sorted trees of degree 16 ) . It is therefore not surprising that we found this relation to be true in Galton-Watson ( GW ) random trees ( Fig 2H , dashed grey line ) and in the set of all possible binary trees of a given size ( Fig 2E ) . The universality of this distribution of branch numbers and bifurcation ratios extends to a wide range of tree-like structures in nature that most likely do not reach an exact bifurcation ratio of 4 because of their relatively small size . In our study , overall bifurcation ratios varied from 2 . 23–3 . 77 for different dendritic tree types . In river networks , they commonly range from 3–5 [22 , 32] . Similar bifurcation values as well as the general exponential decay relation with increasing SO have also been observed with bifurcation ratios between 3 . 05–3 . 61 in the dog bronchial system [24] , 2 . 99–3 . 10 in the human pulmonary arteries [25] , 3 . 41–4 . 12 in networks of conducting particles in a dielectric liquid [53] , and 3–5 . 76 in social networks [54] . They are also present in several different species of botanical trees , with bifurcation ratios ranging from 3–5 . 18 [28–30] . As we demonstrated here , this general range is similar for neuronal dendritic trees . Previously , the number of branches per SO in Purkinje cell dendrites has been found to decay exponentially with a linear regression slope for log-transformed data of -0 . 52 for cells of SN 6 and -0 . 46 for cells of SN 7 [35] , which are values in a range similar to what we find in the reconstructed dendrites investigated in this study . Furthermore , Binzegger et al . [36] investigated axonal branching in cat visual cortex and found it to be topologically self-similar , i . e . with a bifurcation ratio that is similar between each two consecutive orders and amounts to 3 . 32 for both spiny and smooth axons ( r = 0 . 99 ) . While a significant number of publications have explored branch number distributions and bifurcation ratios in detail , the universal trend of the SO-sorted subtree size distribution is more elusive . Subtree sizes at branch points of a given SO increased exponentially with SO in a similar manner for all groups of binary trees studied here , including those of real dendrites . Subtree sizes are connected to distributions of number of branches , since the number of TPs and BPs in a tree can never be lower than the number of branches . In fact , subtree sizes appeared to mirror the distributions of number of branches with a steady 4k−SN for SO k . We assume that those relations could be proven analytically using similar methods as in [31–33] . Surprisingly , a distribution very similar to that of SO-sorted topological subtree size ( Fig 4E ) was found when calculating the ratio of total dendritic length contained in the subtree of topological nodes of a given SO ( S1 Fig ) . Such an exponential increase of local subtree weight with SO may have functional implications for electrotonic compartmentalisation and synaptic current transfer , in particular since we also found a relationship between subtree sizes and local diameters ( Fig 7B ) . Furthermore , the distribution of segment numbers with SO was very similar for all binary trees we studied . It has previously been found to decay in an exponential manner in Purkinje cells [35 , 55] , and we observed that this relation holds true for many additional dendrite types . Here , on average , binary trees behaved similarly to the complete binary tree ( CBT ) , characterised by its doubling of segments at every level where SO decreases . This is explained by the fact that any tree of a given SN > 2 must necessarily contain a certain number of complete subtrees in order to increase SO at branch points until the corresponding SN is reached ( see Results ) . The apparent universality and low variability of the SO-sorted segment and branch numbers and the branch bifurcation ratio in reconstructed dendrites can thus be explained by the fact that these statistics are universal for most binary trees and therefore of low descriptive power , cf . [34] . But it is important to note that if dendrites had followed a particular given blueprint , the distributions could have been widely different ( Fig 2B and 2C ) . In this way , however , the universal property of SO-sorted topology in binary trees renders those distributions essentially useless for quantifying dendritic trees in a meaningful way ( see also “Concluding remarks on Strahler order and neuronal dendrites” below ) . The results were very different for metric measures , which exhibited strong correlations with SO that were cell type-specific in many cases . For example , we found that SO-sorted distributions of total dendritic length followed a pronounced exponential decay that seemingly depended on the dimensionality of the dendrites , since planar dendritic trees ( e . g . Purkinje cell dendrites ) revealed more shallow slopes than dendrites that extended into 3D space ( e . g . granule cells ) . In line with this , SO-sorted total length in frog retinal ganglion cell ( RGC ) axons has been reported to decrease in a mostly exponential fashion , with 40–50% of the total length contributed by terminal segments and with a slope that closely resembles our LPTC data ( black line in Fig 5B ) [56] . We were able to reproduce this dimensionality effect using simple MST-based model trees based on optimal wiring principles for the different dendrites , where the slope of decay was additionally related to the bf parameter ( see Fig 6B ) . The total dendritic length distribution does not denote a universal relation as seen with the number of segments or branches but is reflective of specific morphological attributes such as how planar a dendrite is . Similar observations were made for SO-sorted mean segment and branch lengths . Interestingly , we were unable to accurately replicate the exponential decay of mean segment and branch lengths with SO in basal pyramidal and granule cell dendrites using simple MST models . This might indicate that these trends are a result of the particular features of these cells , and the measures that we studied here could indeed help to better classify dendrites of such cell types . While dendritic trees followed Horton's law of stream numbers as expected , not all of them obeyed Horton's law of stream lengths , which expresses the mean branch length of SO k as a direct geometric series starting with the mean branch length at SO 1 [22] . In dendrites , we found highly varying SO-sorted distributions of mean branch lengths , as opposed to the exponential increase postulated by Horton's law . For real dendritic trees that are flat and were represented with a low balancing factor in our respective MST models ( e . g . LPTCs and Purkinje cells ) , mean branch length did appear to follow Horton’s law of stream lengths to some extent: The distribution increased exponentially with SO until it peaked in the second-to-last order , i . e . close to the root . Similarly , Hollingworth and Berry [35] observed an exponential increase in the mean lengths of branches of successive SO in rat Purkinje dendrites , and an increase was also reported by Yen et al . in frog RGC axons [56] . For granule cell dendrites and basal pyramidal dendrites , however , the distribution exhibited an exponential decrease . Since river networks are planar , it is conceivable that Horton's law of stream lengths applies only to 2D trees . Meanwhile , motoneurons and apical pyramidal dendrites appeared to fall somewhere in between those extremes and did not exhibit clear trends . The most striking correlation was found between local branch diameters and SO . While the general presence of a correlation may be reasonably expected in a centripetal ordering system since diameter has been well established to taper towards the terminals of neurons , there seems to be no precedent of an investigation of SO-sorted branch diameter in neurons , apart from a report that diameter increases with SO in frog RGC axons [56] . Because diameter values strongly determine electrotonic properties of neurons , we also studied the consequences for synaptic integration and found that simulated local voltage responses to synaptic currents correlated strongly with SO . Interestingly , similar correlations between diameters and SO have been observed in other tree structures in nature . Branch diameters appear to increase exponentially with SO in the bronchial tree of dogs [24] and in botanical trees [29 , 30] . Additionally , topological subtree size was strongly correlated with SO and to a lesser extent with diameter , showing a functional relevance of SO . Potentially , the variations in SO-sorted statistics could also reflect differences in the growth process: While some neurons such as granule cells could “blossom” like flowers , elongating mainly the branches close to the soma , others such as Purkinje cells could mostly develop by growing new terminal branches and densifying the fixed space they occupy . In line with this , Van Pelt et al . [43] demonstrated that the geometry of guinea pig Purkinje cells can be replicated using a dendritic growth model that favours branching at distal locations . SO has advantages as well as disadvantages when compared to other branch ordering systems . Uylings et al . [13] reviewed different ordering methods for dendrite branching and concluded that the Strahler method should preferentially be used when studying branching patterns that are very asymmetric , or when studying tree structures with a very extensive branching pattern such as Purkinje cells , because the tree's Strahler number SN is not as high as the maximum branch order in the centrifugal system . A caveat of the method is its sensitivity especially to the addition or loss of terminal segments , as these can alter the order of many branches in the tree . It has furthermore been suggested that centripetal ordering schemes are superior when examining branch probabilities in distal regions of the dendrite , but that centrifugal ordering of branches is useful for branching structures near the soma or root of the tree [16] . The main usage of Strahler ordering applied to neuronal morphology in the literature so far is concerned with the distribution of the SO-sorted number of branches . It has been used for classification of branching complexity of Drosophila da neurons , as mentioned in the Introduction ( e . g . [37 , 38 , 40–42] ) , and various other studies used that distribution to ascertain differences in “branching complexity” in various cell types , mostly aforementioned da neurons or Purkinje cells , between different conditions such as wild-type vs . knock-out cells ( e . g . [38 , 40 , 57–60] ) . In all of these studies , the authors used the actual number of branches , which would have varied compared to the normalised number . However , since the normalised branch numbers distribution is on average very similar in different groups of trees ( dendritic or otherwise ) , it is quite redundant to compare the number of branches of different orders between cells because the slope of the curve is not likely to differ very much , as discussed above . In fact , in most of those studies , it would have been enough to compare just the number of terminal segments without using any branch ordering system ( or , perhaps , with the additional information of the SN ) : Where actual numbers were given in various publications [38 , 57–59 , 61 , 62] , we plotted the number of branches per SO and saw that they did indeed follow the characteristic exponential decay that was close to a 41-k slope for SO k if values were normalised to the total number of branches . In most of the publications surveyed , significant differences in branch numbers appeared only in SO 1 , i . e . the number of terminals . We argue that using SO only in this way is limiting and redundant , and that more interesting results might emerge if Strahler ordering were used more often in conjunction with metric measures such as total length per SO ( only seen in one publication pertaining to axonal morphology; [56] ) . Some studies , e . g . [60] , did investigate total length between two groups of cells , but there may be benefits to looking at the SO-sorted total length distribution as well as it might offer information regarding the dendritic locations where the length changes most significantly . Further metric SO-sorted measures such as mean branch and segment length might also be of use to quantify differences in morphology and branching complexity . Our study demonstrates that one has to take great care when interpreting the topology of trees using SO because of the many universal features that make such quantification potentially useless . This stresses the importance of using computational models to better interpret the results from quantitative measures that are commonly used in neuroscience . Finally , we observe that SO can be a useful tool to classify tree structures and their functional relevance when used in conjunction with adequate metric information .
In order to obtain the set of all possible binary trees of a given maximal size , we calculated all possible instances using a formal language defined in the following way: We started with the string ‘BTT’ representing a binary tree on 3 nodes , where ‘B’ stands for branch point and is followed by two subtrees and ‘T’ is a termination point . Recursively , all ‘T’ elements were then replaced by new branches ‘BTT’ , one by one resulting in as many next generation trees with each two additional nodes . After calculating all trees of a given generation , all exact duplicates were removed . This procedure was then continued until the target tree size was obtained . Notice that the number of binary trees of a given size grows exponentially with the number of nodes ( yielding 1 , 2 , 5 , 14 , 42 , 132 , 429 , 1 , 430 , etc . as the number of trees in each generation ) . For example there exist 9 , 694 , 845 binary trees on 31 nodes ( 16 ‘T’s ) , which was at the limit of the computing power available to us . We chose the set of all possible binary trees of degree 16 because we wanted to investigate a set that would include a complete binary tree . See Fig 2A for resulting sample binary trees . Note though that many of these trees were equivalent in terms of the topological structure since permutations of subtrees at every branch point are actually equivalent ( for example a tree ‘BBTTT’ is equivalent to ‘BTBTT’; see also green box in Fig 2A for two topologically equivalent binary trees ) . Apart from the unsorted set of trees described above ( i . e . , the set which allows multiple topologically equivalent binary trees with differing ‘B’-and-‘T’ strings ) , we therefore calculated the reduced ( sorted ) subset that contained only topologically unique trees . To determine this sorted subset , the sort_tree function from the TREES toolbox was used to arrange all trees of a newly generated generation such that heavy subtrees would always be represented first in the ‘B’-and-‘T’ strings , thus enabling us to exclude duplicates . A few remaining duplicates were identified by an exhaustive search comparing all permutations of all subtrees at each branch point in the remaining trees . In this way , we obtained all 10 , 905 [52 , 64] sorted binary trees on 31 nodes ( 16 ‘T’s ) . Finally , tree structures were generated from the resulting ‘B’-and-‘T’ strings using the TREES toolbox function BCT_tree . The resulting trees were then analysed further using the TREES toolbox . We generated random binary trees by using a critical Galton-Watson random branching process [44] . This growth process starts with one terminal node at generation 1 . For each successive generation , each terminal node of the previous generation is treated in one of the following two ways: ( 1 ) with probability Pst , growth stops there; ( 2 ) with probability Pbr , the node becomes a branch point , and edges are added with two new terminal nodes ( Fig 2F ) . Terminal growth was previously found to be compatible with the observed topologies in real dendrites [65] . A Galton-Watson process is called critical if Pst = 0 . 5 and Pbr = 0 . 5 . We used custom MATLAB code to generate 10 , 000 random topological trees , terminating each growth process in the cases when the tree size reached 800 nodes . Spatially embedded minimum spanning trees ( MST ) take into account optimal wiring considerations that are important for real neurons . MST models ( here we use the MST_tree function from the TREES toolbox ) were previously used successfully to model a large palette of dendrites [7 , 46 , 47 , 66–68] and axons [69] . These models generate tree structures that connect a set of target nodes to minimise the total dendrite length as well as the cost for short paths from the target nodes to the root along the tree . Target nodes are given to the algorithm and may be chosen to be distributed inside specified two- or three-dimensional areas according to certain rules ( e . g . uniform distribution when coordinates for target nodes are generated as uniformly distributed random numbers on a specified interval ) , and will end up being the branch points , termination points , and continuation points of the tree . The cost for short paths from target nodes to the root is weighted with the balancing factor ( bf ) , with typical values between 0 and 0 . 9 in real dendrites . When bf is low , the total wiring cost is kept to a minimum and the resulting tree approaches a minimum spanning tree . When bf is high , direct paths from target points to the root are given more importance than the pure conservation of wiring . To study topological measures in MST models ( Fig 3 ) , we uniformly distributed a number of random target points ( 30 , 150 , 500 or 1 , 200 , in order to obtain as many trees as possible for SN 3 , 4 , 5 , and 6 , respectively ) in a two-dimensional circular area of 10 , 000 μm2 with a root node located in the centre . 1 , 000 MST-based model trees were generated for each combination of bf ( between 0 and 0 . 9 , in steps of 0 . 1 ) and target point number . Here , the MST_tree function was constrained to bifurcations ( option ‘-b’ ) , enforcing the generation of binary trees . The resulting trees were repaired using the repair_tree function , which assigns a number to every node in the tree according to a predefined standard , and all nodes from the root to the first branch point were deleted , forcing every tree to start with a branch point to best match the concept of binary trees . If nodes were deleted in the process , the repair_tree function was applied once again to update node indices accordingly . In order to investigate the source of the cell type-specific differences in SO-sorted metric measures of real dendrites ( Fig 5 ) , we modelled the SO-sorted distributions by finding the simplest MST model parameters necessary to approximate those distributions ( Fig 6 ) . The initial model conditions were similar to the model described above with simple two- or three-dimensional ( depending on the real cells ) round spanning fields and a root node located in its centre . The complexity of the hull , the root location and the statistics of the target point distributions were adjusted manually in a trial-and-error procedure in an attempt to best reproduce—with as few modifications as possible—all SO-sorted branching statistics as seen in the real dendrites . In all cases , the balancing factor and number of target points were varied to best match the real dendrite statistics and SN values . Specific parameters for each of the five models are described in Table 2 and Fig 6A ( bottom row ) . Binary synthetic trees were obtained in a similar manner as described above . 100 synthetic trees were generated for each of the models . Reconstructions of real dendritic morphologies ( examples see Fig 4A ) were taken from the NeuroMorpho . Org database ( accessed on 26/11/2015 ) with the exception of the blowfly LPTCs [66] , which were taken directly from the set of sample cells in the TREES toolbox ( see Table 3 for details ) . A preselection of neurons was conducted according to metadata filtering on the NeuroMorpho . Org website ( Table 4 ) . In brief , we restricted the dataset to neurons with complete dendrites that were part of the control conditions in any given experiment . All preselected neurons were manually inspected in three-dimensional view . Since the metadata is self-reported by the contributing labs , the quality of “complete” reconstructions may differ from dataset to dataset . Many reconstructions exhibited sudden step-like jumps in depth , a common problem in three-dimensional reconstructions . We excluded such dendrite reconstructions with insufficient quality by visual inspection but no objective criteria to appropriately quantify the quality of the tracings were used . Reconstructions of typically three-dimensional neurons ( e . g . granule cells , pyramidal cells ) that did not or did only slightly extend into the third dimension were also excluded from the analysis . The number of suitable cells left for each cell type can be found in Table 3 . Despite the fact that our NeuroMorpho . Org metasearch required diameter information , we found that some of the remaining cells had poorly reconstructed diameter values ( i . e . , nearly constant diameter for all nodes ) . These cells were still used for most analyses in this study but were excluded from the SO-sorted branch diameter computation , which was therefore performed on a lesser number of dendritic trees per cell type ( see Table 3 ) . We then deleted all cell regions that were not labelled “dendrite” ( i . e . , axon and soma regions ) . Deletion of a single cell's soma resulted in multiple dendritic trees ( Table 3 ) if there were several primary dendrites emerging from the soma . We pooled data for all dendritic trees of a cell type for analysis , with the exception of pyramidal cells , where we analysed apical and basal trees as separate groups due to their very different morphologies . All dendritic trees were then repaired with the TREES toolbox function repair_tree , replacing branch points with more than two daughters with multiple consecutive bifurcations to restrict ourselves to binary trees ( no multifurcations allowed ) . Furthermore , we identified the first branch point following the root ( if it was not the root node already ) and deleted all previous nodes . A deletion was followed by another application of the repair_tree function . This deletion step was performed to ensure that all analysed dendritic trees were binary trees that started with a branch point . However , it must be noted that this is an alteration of the original morphology and leads to exclusion of data concerning the length and presence of small branches of higher Strahler orders ( e . g . dendrites that emerge from the soma as a single branch before they first bifurcate ) . Our morphometric analysis distinguishes between dendrite segments and branches . A segment is defined as a piece of dendrite connecting two consecutive topological nodes in the tree ( BP—BP or BP—TP ) . Consecutive segments ( moving from terminals towards the root ) of the same SO form one branch of that order . A branch may consist of only one segment ( e . g . , all terminal segments are also terminal branches ) , but often consists of multiple segments , especially for higher orders ( Fig 1B , the tree contains three SO 2 segments , but only two SO 2 branches , one of which is composed of two segments ) . We additionally distinguish between node and segment SO to determine the highest order in a tree , its Strahler number ( SN ) . We call the highest SO assigned to a segment in a tree its segment Strahler number . The highest SO of any node in a tree is its node Strahler number . In most cases , these two are interchangeable . However , when two segments of the same order meet at the root node of the tree , they are different ( e . g . in Fig 1A: segment SN = 2 , but node SN = 3 ) . For node-based measures ( subtree size , branch diameter , local voltage response ) , we forced functions to consider the root node’s SO as equal to the tree’s segment SN in the few cases where node and segment SN differed . This step did not significantly alter the resulting SO-sorted measures but was performed to ensure that all trees sharing a common segment SN would also display a common number of data points ( from SO 1 to the order corresponding to the segment SN ) that were averaged for visualisation in the figures . The topological measures we analysed are the number of segments , number of branches , branch bifurcation ratio , and the size of topological subtrees . These measures do not require any metric information and therefore they enable us to compare these distributions across not only reconstructed neurons and synthetic MST morphologies , but also Galton-Watson random branching model trees as well as the set of all possible binary trees of degree 16 . Except for Fig 2B and 2C , SO-sorted distributions of number of segments and branches were normalised ( to the total number of segments and branches in the tree , respectively ) to be able to compare distributions of trees of different sizes . The branch bifurcation ratio was obtained by visualising the number of branches of any SO k with the number of branches at SO k + 1 . When bifurcation ratios between all consecutive orders in a tree are similar , the tree is said to be topologically self-similar . Hence , the bifurcation ratio provides information about the fractal degree of a structure . We calculated overall bifurcation ratios by performing a linear regression on the number of branches of SO k against the number of branches of SO k +1 for all trees of a dendrite type . Topological subtree sizes counting the number of BPs and TPs for any BP in the tree should intuitively increase for centripetal branch ordering schemes such as SO . Topological subtree sizes were also normalised ( to the total number of topological nodes in the tree ) and used for Figs 2 , 3 and 4 . The following metric measures were determined as a function of SO for reconstructions of real neurons and for their respective MST models: total dendritic length , mean branch length , and mean segment length . Also , branch diameters were investigated in the reconstructed morphologies where diameter values were available . Normalised total lengths per SO express the proportion of total dendritic length in each SO . Normalised mean branch and segment lengths per SO were obtained by dividing the total length value for a given SO by the total number of branches or segments respectively for that given SO value . These values were further divided by the sum of the average branch or segment length values of all SO ( integral under the curve is then 1 in all cases ) to keep the resulting distributions in the same range . Mean branch diameters per SO were calculated by taking the sum of the diameters of all nodes with a given SO and dividing that by the number of nodes of that given SO . Normalised relative values between 0 and 1 were obtained by setting the lowest mean diameter value for any order ( this was always SO 1 ) to 0 and the highest mean diameter value ( this was always the order corresponding to the tree’s SN ) to 1 . Electrotonic measures in passive dendritic trees were calculated on a slightly differently pre-processed dataset because we took values for Ri and Rm from the literature that described whole cells instead of dendritic trees that were once part of a bigger dendritic field . We therefore took all neurons with reasonable diameter information ( see Table 3 , “Number , with diameter” ) , removed soma and axon regions in such a way that the dendrite would stay connected and not result in multiple dendritic trees , and repaired the dendrite with the repair_tree function , which may result in a small change of morphology and topology . To simulate the average local voltage response to an injection of 10 pA into a topological node of SO k , the dendritic tree’s electrotonic signature given its specific membrane conductance Gm = 1/Rm and specific internal resistivity Ri was determined using the sse_tree function . Rm and Ri for the different cell types were taken from the literature [70–73] for Fig 8B . The diagonal of the resulting matrix contained the local input resistances in MΩ of every node in the tree . These values were averaged between all topological nodes that shared the same SO . In order to simulate the local voltage response to a small steady-state synaptic current injection of 10 pA , the values were divided by 100 and the unit became mV . For normalisation , all values were divided by the average value for the terminal nodes ( SO 1 ) . Three motoneurons ( ‘Alvarez-Control-Cell-1 . CNG’ , ‘Alvarez-Control-Cell-2 . CNG’ , and ‘Alvarez-Control-Cell-3 . CNG’ ) had to be excluded from this simulation because of their high number of nodes . All figures of SO-sorted distributions show averages of trees that share the same segment SN . In this way , patterns in the data are not skewed by averaging over model trees or real dendrites in a sample that have different SN values . For reconstructed morphologies , we chose the most abundant SN value for each cell type for visualisation , hence only the subset of the data where all trees share that SN value was plotted ( e . g . see Fig 4B: for granule cells ( in red ) , there were 59 dendritic trees analysed , but the graph shows only the average of those 53 trees in the subset of all granule cell dendritic trees that had segment SN 3 ) .
|
Similarly to river beds , dendritic trees of nerve cells form elaborate networks that branch out to cover extensive areas . In the 1940s , ecologist Robert E . Horton developed an ordering system for branches in river networks that was refined in the 1950s by geoscientist Arthur N . Strahler , the Horton-Strahler order ( SO ) . Branches at the tips start with order 1 and increase their order in a systematic way when encountering new branches on the way to the root . SO relationships have recently become popular for quantifying dendritic morphologies . Various branching statistics can be studied as a function of SO . Here we describe that topological measures such as the number of branches , the branch bifurcation ratio and the size of subtrees exhibit stereotypical relations with SO in dendritic trees independently of cell type , mirroring universal features of binary trees . Other functionally more relevant features such as mean branch lengths , local diameters and simulated voltage responses to synaptic inputs directly correlate with SO in a cell type-specific manner , indicating the importance of SO for understanding dendrite growth as well as neural computation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"granule",
"cells",
"cellular",
"neuroscience",
"dendritic",
"structure",
"ganglion",
"cells",
"cell",
"biology",
"animal",
"cells",
"axons",
"pyramidal",
"cells",
"neuronal",
"morphology",
"neurons",
"nerve",
"fibers",
"biology",
"and",
"life",
"sciences",
"cellular",
"types",
"neuronal",
"dendrites",
"neuroscience",
"purkinje",
"cells"
] |
2017
|
Universal features of dendrites through centripetal branch ordering
|
The primary role of the innate immune response is to limit the spread of infectious pathogens , with activation of Toll-like receptor ( TLR ) and RIG-like receptor ( RLR ) pathways resulting in a pro-inflammatory response required to combat infection . Limiting the activation of these signaling pathways is likewise essential to prevent tissue injury in the host . Triad3A is an E3 ubiquitin ligase that interacts with several components of TLR signaling and modulates TLR activity . In the present study , we demonstrate that Triad3A negatively regulates the RIG-I RNA sensing pathway through Lys48-linked , ubiquitin-mediated degradation of the tumor necrosis factor receptor-associated factor 3 ( TRAF3 ) adapter . Triad3A was induced following dsRNA exposure or virus infection and decreased TRAF3 levels in a dose-dependent manner; moreover , Triad3A expression blocked IRF-3 activation by Ser-396 phosphorylation and inhibited the expression of type 1 interferon and antiviral genes . Lys48-linked ubiquitination of TRAF3 by Triad3A increased TRAF3 turnover , whereas reduction of Triad3A expression by stable shRNA expression correlated with an increase in TRAF3 protein expression and enhancement of the antiviral response following VSV or Sendai virus infection . Triad3A and TRAF3 physically interacted together , and TRAF3 residues Y440 and Q442—previously shown to be important for association with the MAVS adapter—were also critical for Triad3A . Point mutation of the TRAF-Interacting-Motif ( TIM ) of Triad3A abrogated its ability to interact with TRAF3 and modulate RIG-I signaling . TRAF3 appears to undergo sequential ubiquitin “immuno-editing” following virus infection that is crucial for regulation of RIG-I-dependent signaling to the antiviral response . Thus , Triad3A represents a versatile E3 ubiquitin ligase that negatively regulates RIG-like receptor signaling by targeting TRAF3 for degradation following RNA virus infection .
Upon recognition of specific molecular components of viruses , the host cell activates multiple signaling cascades that stimulate an innate antiviral response , resulting in the disruption of viral replication , and the mobilization of the adaptive arm of the immune system . Central to the host antiviral response is the production of type 1 interferons ( IFNs ) , a large family of multifunctional immunoregulatory proteins . Multiple Toll like receptor ( TLR ) -dependent ( TLR-3 , -4 , -7 and 9 ) and RIG-I-like receptor ( RLR ) pathways are involved in the cell specific regulation of Type I IFNs , with accumulating evidence that cooperation between different pathways is required to ensure a robust and controlled activation of antiviral response [1] , [2] , [3] . RIG-I-like receptors ( RLRs ) - the retinoic acid-inducible gene-I ( RIG-I ) and melanoma differentiation-associated gene-5 ( MDA-5 ) - are novel cytoplasmic RNA helicases that recognize viral RNA present within the cytoplasm . Although both TLR7 and TLR9 are critical for recognition of viral nucleic acids in the endosomes of plasmacytoid dendritic cells ( pDCs ) , most other cell types recognize viral RNA intermediates through the RLR arm of the innate immune response [4] , [5] , [6] . Structurally , RIG-I contains two caspase activation and recruitment domains ( CARD ) at its N-terminus and RNA helicase activity in the C-terminal portion of the molecule [4] . The C-terminal regulatory domain ( CTD ) ( aa 792–925 ) of RIG-I binds viral RNA in a 5′-triphosphate-dependent manner and activates RIG-I ATPase inducing RNA-dependent dimerization and structural alterations that enable the CARD domain to interact with other downstream adapter protein ( s ) leading to the transcription of antiviral genes [7] , [8] , [9] . RIG-I-dependent signaling to the IKKα/β complex and to TBK1/IKKε is transmitted via a CARD domain containing adapter molecule – alternatively named mitochondrial antiviral signaling ( MAVS ) , interferon-β stimulator 1 ( IPS-1 ) , virus induced signaling adapter ( VISA ) , CARD adapter inducing IFN-β ( CARDIF ) [10] , [11] , [12] , [13] . MAVS localizes to the outer mitochondria membrane via a C-terminal mitochondrial transmembrane targeting domain ( TM ) , and its mitochondrial localization acts as a pivotal point for triggering the antiviral cascade via activation of NF-κB and IRF-3 [3] , [14] , [15] , [16] . Activation of TLRs and RLRs results in the dissemination of an antiviral and antimicrobial cascade necessary to combat invading pathogens [17] , [18] , [19] . Limiting the intensity and duration of TLR and RLR signaling is likewise essential to prevent this protective response from causing inflammatory or autoimmune injury to the host . Ubiquitination is a post-translational modification by which signaling is suppressed in many regulatory pathways [20] . Lys48-linked ubiquitination is one of the most common pathways to target proteins for 26S proteasomal degradation [21] , whereas Lys63-linked ubiquitination is involved in protein-protein interactions , recruitment , and assembly of signaling complexes [22] , [23] . It has become clear that ubiquitination of signaling adapters is an integral part of NF-κB and IFN signaling in response to virus pathogen associated molecular patterns ( PAMPs ) . Deubiquitinating enzymes that remove Lys63-linked ubiquitin are also emerging as key negative regulators of the IFN and NF-κB pathways [16] , [24] , [25] , [26] , [27] . For example , the deubiquitinating enzyme A ( DUBA ) , a novel OTU-domain DUB negatively regulates IFN signaling following RIG-I , MDA5 or TLR3 stimulation [28] . DUBA specifically removes Lys63-linked ubiquitin chains from TRAF3 , resulting in the disruption of interaction between TRAF3 and the downstream kinases IKKε and TBK1 and subsequent blockade of IRF-3 and IRF-7 phosphorylation [28] . The activation of RIG-I/MDA-5 ultimately leads to the TM-dependent dimerization of the MAVS N-terminal CARD domains , thereby providing an interface for direct binding to and activation of the tumor necrosis factor ( TNF ) receptor-associated factor ( TRAF ) family members that are involved in both the IFN and NF-κB arms of the innate immune response [29] , [30] . TRAF3 is an adapter molecule that is required for the induction of type I IFN and anti-inflammatory cytokine interleukin-10 ( IL-10 ) , but is dispensable for expression of pro-inflammatory cytokines in response to viral infection and TLR ligation in bone marrow-derived macrophages ( BMMs ) , plasmacytoid dendritic cells ( pDCs ) , and murine embryonic fibroblasts ( MEFs ) [31] , [32] . TRAF3 was the first TRAF demonstrated to directly associate with CD40 . Subsequently , it was shown that TRAF3 negatively regulates CD40 signaling by competing with TRAF2 for CD40 binding , thus impeding CD40-TRAF2 mediated JNK and NF-κB activation [33] . Crystal structure of the binding crevice of TRAF3 bound in complex with a 24-residue fragment of the cytoplasmic portion of BAFF receptor ( BAFF-R ) , revealed two amino acids in TRAF3 -Y440A and Q442- that are involved in BAFF-R interaction [34] . Interestingly , other TNFRs such as CD40 contain similar TRAF-interacting motifs ( TIMs ) , defined by the consensus sequence PxQx ( T/S ) , that interact with the same binding crevice on TRAF3 [35] , [36] . In addition , the TRAF family member–associated NF-κB activator ( TANK ) adapter and the viral oncogene LMP1 of the Epstein Barr Virus also bind to the same structural crevice of TRAF3 [37] , [38] . MAVS regulation of type I IFN induction is achieved by direct and specific interaction with the TIM of TRAF3; interestingly point-mutation of the TIM domain completely abrogates TRAF3-mediated IFN-α production in response to Sendai virus infection [39] . Triad3A is a RING finger type E3 ubiquitin-protein ligase that promotes Lys48-linked ubiquitination and proteolytic degradation of TLR4 and TLR9 and negatively regulates their activation by lipopolysaccharide and CpG-DNA , respectively [40] . Triad3A is the most abundant alternatively spliced form of the Triad family . In addition , Triad3A interacts and promotes down-regulation of two TIR domain containing adapter molecules , TIR-domain-containing adapter-inducing IFN-β ( TRIF ) and TRIF-related adapter molecule ( TIRAP ) . Moreover , Triad3A acts as a negative regulator of TNF-α signaling by interacting with the TIR homologous ( TIRH ) domain containing protein receptor-interacting protein 1 ( RIP1 ) [41] . This interaction effectively disrupts RIP1 binding to the TNF-R1 complex and impedes RIP-1-mediated NF-κB activation [41] . The identification of a TIM sequence in the N-terminus of Triad3A -using a program written in python language ( http://www . biopython . org ) - as well as the previously characterized function of Triad3A in TLR signaling , prompted us to investigate the role of Triad3A in the regulation of the RIG-I/MAVS signaling via TRAF3 . In the present study , we demonstrate that Triad3A negatively regulates the RIG-I signaling pathway through Lys48-linked ubiquitin-mediated degradation of TRAF3 , resulting in the inhibition of the type I IFN response .
The identification of a TIM domain in Triad3A prompted us to examine the ability of Triad3A to inhibit RIG-I mediated activation of IFNB gene transcription; a constitutively active form of RIG-I ( aa 1-229 , ΔRIG-I ) , the MAVS adapter or IKKε , were co-expressed together with Triad3A in 293T cells , together with an IFNB promoter luciferase reporter . A low basal activity of the IFNB promoter was not affected by Triad3A expression ( Figure 1A ) , while co-expression of ΔRIG-I , MAVS , or IKKε resulted in 196 , 132 , 61-fold stimulation of the IFNB promoter , respectively ( Figure 1A ) . Co-expression of Triad3A with ΔRIG-I or MAVS resulted in a complete inhibition of IFNB promoter activity , whereas IKKε mediated activation of the IFNB promoter remained unchanged ( Figure 1A ) . Similar results were also obtained with the NF-κB response ( Figure 1B ) ; expression of ΔRIG-I , MAVS or IKKε , ( co-expressed together with IRF-7 ) activated IFNA4 promoter activity 34 , 18 , 49-fold , respectively , while co-expression of Triad3A blocked IFNA4 activation ( Figure 1C ) . Furthermore , Triad3A blocked interferon stimulated response element ( ISRE ) activation following Sendai virus infection ( Figure 1D ) . A dose-response curve was performed using the ISRE promoter with increasing amounts of Triad3A and ΔRIG-I , MAVS , TRIF , or TBK1 expression plasmids; ΔRIG-I resulted in 893-fold induction of the ISRE promoter , and Triad3A co-expression diminished activation in a dose dependent manner ( Figure S1A ) . Similarly , MAVS or TRIF adapters activated the ISRE by 785- and 863-fold , respectively; Triad3A again dramatically reduced ISRE activation ( Figure S1B , S1C ) . In contrast , Triad3A did not significantly decrease TBK1-mediated ISRE activation ( Figure S1D ) . Triad3A co-expression with MDA5 or an active form of TLR3 fused to CD4 ( CD4-TLR3 ) resulted in a complete inhibition of IFNB promoter activity ( Figure S2A ) . Triad3A inhibited MDA5-induced NF-κB promoter activity; however Triad3A inhibition of CD4-TLR3 mediated NF-κB promoter activity was less pronounced ( Figure S2B ) . These experiments suggested that Triad3A was a strong inhibitor of RIG-I signaling to IRF-3 , IRF-7 and NF-κB and suggested that Triad3A may target an adapter molecule common to both the TLR and RLR signaling pathways . As a measure of activation of the IFN signaling pathway , the phosphorylation state of IRF-3 was evaluated by immunoblot in the presence of Triad3A using the phosphospecific Ser-396 IRF-3 antibody [42] . ΔRIG-I co-expression induced Ser-396 IRF-3 phosphorylation ( Figure 2 , lane 3 ) , while co-expression of Triad3A completely blocked IRF-3 phosphorylation ( Figure 2 , lane 4 ) . MAVS expression likewise induced Ser-396 IRF-3 phosphorylation ( Figure 2 , lanes 3–5 ) ; that was abrogated by Triad3A ( Figure 2 , lanes 4–6 ) . In contrast , TBK1 co-expression in the presence or absence of Triad3A did not alter the IRF-3 phosphorylation state ( Figure 2 , lanes 7–8 ) . Complementing the phosphorylation status , Triad3A also inhibited ΔRIG-I and MAVS-induced dimerization of endogenous IRF-3 ( Figure 2 , lanes 4–6 ) , but did not affect TBK1-induced IRF-3 dimer formation ( Figure 2 , lanes 7–8 ) , indicating that Triad3A targets RLR signaling upstream of TBK1 . Previous studies demonstrated that the E3 ligase RNF125−a negative regulator of RIG-I− was induced following IFN-α and poly ( I∶C ) treatment [43] . Endogenous Triad3A protein was induced in human bronchial epithelial A549 cells following dsRNA treatment for 6h , vesicular stomatitis virus ( VSV ) , or Sendai virus ( SeV ) infection for 16h; correlating with the degradation of TRAF3 protein ( Figure 3A ) . Moreover , Triad3A protein expression is induced following IFN-α/β treatment ( data not shown ) . In addition , it was determined by time-course analysis that 6h dsRNA treatment and 16h virus infection resulted in maximal TRAF3 degradation ( Figure S3 ) . Expression of increasing amounts of Triad3A decreased TRAF3 levels in a dose-dependent manner ( Figure 3B ) . Additionally , SeV-mediated degradation of TRAF3 in A549 cells was blocked by the proteasome inhibitors lactacystin and Mg132 , but not by the lysosomal protease inhibitor E64 ( Figure 3C ) . To further confirm the involvement of Triad3A in regulating TRAF3 turnover , two shRNA expression vectors - shRNA1 and shRNA2 that target Triad3A nucleotide sequences 1 , 532–1 , 551 and 1 , 195–1 , 214 , respectively – were used to stably knock-down Triad3A in A549 cells . Knock-down of Triad3A resulted in a 5-fold increase in TRAF3 protein levels ( Figure 4A ) . Interference with endogenous Triad3A also modulated the ISRE promoter; ISRE activity was 3-fold higher in Triad3A knock-down cells infected with SeV , compared to cells expressing scrambled shRNA ( Figure 4B ) . [43] . To investigate the physiological effects of Triad3A inhibition on downstream IFN-stimulated target genes , expression of multiple ISGs were examined by quantitative PCR in A549-Triad3A knock-down cells . SeV infection ( 40 hemagglutination units/ml ( HAU ) ) in Triad3A knockdown cells were led to a 3–4 fold increase in IFN-β and IFN-α2 mRNA expression 12h post-infection ( p . i . ) compared to control cells ( Figure 4C ) . Similarly , IP-10 ISG56 , IS15 transcripts were increased 3–4 fold at 12h p . i . ( Figure 4C ) , while STAT1 levels remained relatively constant ( Figure 4C ) . In addition , levels of IFN-α and IFN-β released in the supernatant monitored by ELISA increased 2-fold following SeV infection ( Figure 4D ) . Finally , in VSV infected A549 cells , VSV proteins ( nucleocapsid ( N ) , surface glycoprotein ( G ) , and matrix ( M ) ) were detected at 8h p . i . , whereas in Triad3A knock-down cells , VSV protein expression was delayed , with viral proteins detected only at 16h post-infection ( Figure 4E ) . Notably , in A549 control cells TRAF3 protein levels decreased over time following virus infection , whereas in Triad3A knock-down cells TRAF3 protein levels remained constant ( Figure 4E ) . These results indicate the involvement of Triad3A in regulating IFN and NF-κB dependent gene expression following RNA virus infection . The functional specificity of TRAFs is dictated by their ability to recognize and bind distinct structural motifs , termed the TRAF-interacting motif ( TIM ) , with the consensus sequence PxQx ( T/S ) . This motif contacts TRAF proteins within a structurally conserved binding crevice within the C-terminal TRAF domain ( Figure 5A ) . Using multiple sequence alignment , we identified an N-terminal motif in Triad3A - amino acid residues 316 -PMQES- 320 - with substantial homology to the consensus TIM that is also found on the adapter molecule MAVS – amino acid residues 143-PVQDT-147 ( Figure 5A ) . Previously , it has been reported that the TIM domain of MAVS interacts with amino acid residues Y440 and Q442 within the TRAF domain of TRAF3 . As a result , co-immunoprecipitation experiments were performed to detect an association of Triad3A and TRAF3; following immunoprecipitation of Flag-tagged TRAF3 , immunoblot analysis revealed that TRAF3 and Triad3A co-precipitate together ( Figure 5B , lane 4 ) . Co-immunoprecipitation of TRAF3 ( Y440A/Q442A ) and Triad3A revealed that this interaction was impaired , demonstrating that the hydrophobic residues in the TRAF3 binding crevice are important for binding to Triad3A ( Figure 5B , lane 5 ) . In the reciprocal experiment , Triad3A S320D was unable to bind TRAF3 in co-immunoprecipitation experiments ( Figure 5C , lane 6 ) and increasing amounts of Triad3A S320D failed to promote TRAF3 degradation ( Figure S4 ) . Furthermore , Triad3A S320D no longer inhibited ΔRIG-I-mediated activation of the NF-κB and IFNβ gene transcription but readily inhibited TRIF-mediated activation ( Figure 5D , E ) , thus indicating the specificity of the TIM domain of Triad3A for TRAF3 . To test whether Triad3A-mediated degradation of TRAF3 was promoted by Lys48-linked ubiquitination , an in vivo ubiquitination assay was performed with Flag-tagged TRAF3 , HA-tagged wild type or ( Lys48 and Lys63 ) Ub products ( Figure 6A ) , and sub-optimal levels of myc-tagged Triad3A and Triad3A S320D to limit TRAF3 degradation . Following immunoprecipitation of Flag-tagged TRAF3 , immunoblot analysis revealed that Triad3A mediated TRAF3 polyubiquitination ( Figure 6B , lane 8 ) , with polyubiquitination increasing in the presence of Triad3A and Mg132 ( Figure 6B , lane 10 ) , compared to TRAF3 and ubiquitin alone ( Figure 6B , lane 7 ) . In contrast , Triad3A S320D did not polyubiquitinate TRAF3 ( Figure 6B , lane 9 ) ; furthermore , Triad3A promoted Lys48-linked polyubiquitination of TRAF3 ( Figure 6B , lane 13 ) but not Lys63-linked polyubiquitination ( Figure 6B , lane 14 ) . Cells expressing optimal levels of Triad3A readily degraded TRAF3 ( Figure 6C , lane 2 ) , whereas Triad3A was unable to degrade TRAF3 in the presence of K48R and KO Ub mutants ( Figure 6C , lane 3 , 5 ) . As both MAVS and Triad3A contain well-characterized TIM domains , the interaction between endogenous TRAF3 and Triad3A was next examined in SeV-infected A549 cells . Following co-immunoprecipitation with anti-TRAF3 antibody , a MAVS-TRAF3 complex was detected at 8h p . i . , whereas at 16h , Triad3A disrupted this interaction by associating directly with TRAF3 , suggesting that both Triad3A and MAVS compete for the same binding residues on TRAF3 ( Figure 7A ) . Importantly , a kinetic analysis of in vivo TRAF3 ubiquitination demonstrated that endogenous TRAF3 was subject to differential biphasic polyubiquitination; using Lys48 and Lys63 specific Ub antibodies [44] , early Lys63-linked polyubiquitination was detected at 4h and 8h p . i . ( Figure 7B ) , whereas a late phase Lys48-linked polyubiquitination of TRAF3 was detected at 12h and 16h p . i . ( Figure 7B ) . Thus , TRAF3- mediated antiviral signaling appears to be regulated by recruitment of TRAF3 to the MAVS TIM , followed by Triad3A competition for the same binding crevice of TRAF3 ( Figure 8 ) .
The present study demonstrates that the E3 ubiquitin ligase Triad3A blocks RIG-I-mediated signaling to NF-κB and IRF pathways by targeting the TRAF3 adapter for degradation via Lys48-linked ubiquitinination . Several observations support this conclusion: 1 ) co-expression of Triad3A blocked ΔRIG-I dependent IRF-3 phosphorylation and dimerization; 2 ) Triad3A expression decreased TRAF3 protein levels in a dose-dependent manner; 3 ) knock-down of Triad3A by shRNA increased endogenous TRAF3 protein levels , increased ISG mRNA levels following virus infection , and inhibited VSV replication; 4 ) Lys48-linked ubiquitination of TRAF3 by Triad3A increased TRAF3 turnover; and 5 ) Triad3A and TRAF3 physically interacted together , an interaction that was impaired by mutation of TRAF3 ( Y440A/Q442A ) , or reciprocally by point mutation of the TIM domain in Triad3A ( S320D ) . TRAF3 appears to undergo a biphasic ubiquitination following virus infection that is crucial for regulation of RIG-I dependent signaling to the antiviral response . Early Lys63-linked polyubiquitination of TRAF3 leads to the recruitment of TBK1/IKKε and subsequent activation of the antiviral response [28] , while late phase Lys48-linked polyubiquitination by Triad3A ultimately degrades TRAF3 and leads to shut-down of the antiviral response ( Figure 8 ) . Recent studies have highlighted the importance of ubiquitination in modulating the innate immune response to invading pathogens via both the TLR and RLR pathways . For example , the RIG-I cytoplasmic RNA sensor undergoes both Lys48-linked and Lys63-linked ubiquitination [43] , [45]: the second CARD domain undergoes TRIM25α-mediated , Lys63-linked ubiquitination at Lys-172 , resulting in RIG-I/MAVS association and triggering of the antiviral response [45]; RIG-I also undergoes Lys48-linked ubiquitination , leading to RIG-I proteasomal degradation by RNF125 [43] . Additionally , RNF125 conjugates ubiquitin to MDA5 and MAVS , thus inhibiting the assembly of the downstream antiviral signaling complex [43] . Overall , multiple steps in the RLR pathway are regulated by ubiquitination to ensure a properly modulated antiviral cascade . In addition to the newly described role of Triad3A in the regulation of the RIG-I response , previous studies demonstrated that Triad3A negatively regulates both the TLR and TNF-α pathways by promoting Lys48-linked , ubiquitin-mediated degradation of TLR4 , TLR9 and TIR domain-containing adapters TRIF and TRAM [40] , [41] . Triad3A regulation of the TNF-α pathway is achieved via a proteolysis-independent mechanism that impedes RIP1 binding to the TNF-R1 [40] , [41] . Furthermore , Triad3A promotes ubiquitination and proteasomal degradation of RIP1 following disruption of the RIP-1-Hsp90 complex . Both Hsp90 and Triad3A form a complex that co-ordinates the homeostasis of RIP1; treatment of cells with geldanamycin to disrupt the Hsp90 complex leads to proteasomal degradation of RIP1 by Triad3A [40] . The present study further illustrates the versatility of Triad3A as a negative regulator of innate signaling pathways . Both TLR and RLR pathways converge upon TRAF3 in the activation of the antiviral cascade . TRAF3 was originally described as a cytoplasmic adapter that interacted with CD40 and LMP1 and modulated the adaptive immune response [46] , [47] . The generation of TRAF3 −/− bone marrow-derived macrophages established TRAF3 as a key molecule in signaling to the production of type I IFNs that functioned as a bridge between MAVS and the downstream kinases TBK1/IKKε [32] , [39] . Triad3A mediated degradation of TRAF3 results not only in the inhibition of RIG-I signaling , but also inhibition of MDA5 and TLR3 signaling ( Figure S2A , B ) . The TIM sequence of MAVS ( aa 143-PVQDT-147 ) binds to the hydrophobic C-terminal crevice of TRAF3 ( TRAF domain ) located between amino acids Y440 and Q442 [39] . The TIM motif represents a binding interface that recognizes different TRAFs with varying degrees of specificity . The binding cleft in TRAF3 has structurally adaptive “hot spots” that can recognize motifs that are divergent from the consensus TIM [36] . Interestingly , Triad3A interaction with TRAF3 was impaired by mutation of residues within the binding crevice ( Y440A/Q442A ) ( Figure 6B ) . Furthermore , Triad3A disrupts the interaction between MAVS and TRAF3 ( Figure 7A ) , thus highlighting the importance of the TIM domain of Triad3A in regulating TRAF3 interactions by competitive binding . In contrast to its positive role in the production of type I IFN , TRAF3 negatively regulates noncanonical p100/p52 NF-κB activation through degradation of the NF-κB inducing kinase NIK [48] , [49] . In the present study , co-expression of Triad3A decreased IFNB , IFNA4 , and NF-κB promoter activity by targeting TRAF3 for degradation . Although it was expected that Triad3A driven TRAF3 degradation would enhance NF-κB promoter activity , the observed decrease in NF-κB activity suggests that Triad3A may disrupt other TRAF family members such as TRAF2 and TRAF6 , prevent their association with MAVS , and thus disrupt NF-κB activation . However , it has been previously demonstrated that Triad3A does not target TRAF2 or TRAF6 for proteasomal degradation [41] . It is also possible that some components of the p100/p52 pathway may be engaged downstream of RIG-I; this idea is strengthened by the recent report that TNFR1-associated death domain protein ( TRADD ) is essential for RIG-I/MAVS signaling , forms a complex with TRAF3/TANK/FADD/RIP1 , and leads to activation of IRF-3 and NF-κB [50] . Furthermore , the effect of Triad3A on NF-κB activation was shown to be independent of RIP1 proteolytic degradation [41] , thus strengthening the possibility that another TRAF family member associates with the TIM domain of Triad3A . Previous studies demonstrated that TRAF3 signaling was tightly regulated by the de-ubiquitinase A ( DUBA ) which removed Lys63 linked Ub residues from TRAF3 and disrupted recruitment of TBK1/IKKε and downstream IFN activation [28] . Dual regulation of TRAF3 by DUBA and Triad3A represents a pivotal point in the control of RLR signaling . The present results suggest a biphasic regulation or “immune-editing” , whereby TRAF3 is Lys63 polyubiquitinated early after virus infection to bridge protein-protein interactions between MAVS and TBK1/IKKε . Later , Lys63 polyubiquitin is removed by DUBA to disrupt TRAF3-TBK1/IKKε interactions [28]; TRAF3 then undergoes a late phase Lys48-linked polyubiquitination by Triad3A , leading to proteasomal degradation ( Figure 8 ) . Such a multi-level regulation of TRAF3 underscores its key role in modulating positive and negative antiviral signaling . Furthermore , the complementary functions of DUBA and Triad3A with respect to inhibition of TRAF3 activity and turnover may be subject to stimuli- and tissue-specific regulation , a topic that warrants further investigation . In conclusion , Triad3A acts as a multi-targeting E3 ubiquitin ligase that negatively regulates the TLR , TNF-α and RLR pathways; in the RLR pathway , Triad3A targets TRAF3 for Lys48-linked polyubiquitination , leading to proteasome-dependent degradation , as part of the host-specific mechanism that limits the antiviral response .
Plasmids encoding ΔRIG-I , MAVS , IKKε , TBK1 , NF-κB/pGL3 , IFNB/pGL3 , IFNA4/pGL3 , ISRE-luc reporter , and pRLTK were described previously [14] , [24] , [51] , [52] . HA-ubiquitin and other HA-Ubiquitin constructs ( HA-Ub-K48 , HA-Ub-K63 , HA-Ub-K48R , HA-Ub-K63R , and HA-Ub-KO ) were kind gifts from Dr . Zhijian Chen ( Department of Molecular Biology , University of Texas Southwestern Medical Center , Dallas Texas ) . MDA5 and CD4-TLR3 were kind gifts from Dr . Stephen Goodbourn ( Division of Basic Medical Sciences , St George's , University of London , England ) and Dr . Luke A . J . O'Neill ( School of Biochemistry and Immunology , Trinity College , Dublin , Ireland ) respectively . Human Triad3A cDNA was amplified from pKR5 Flag-Triad3A expression plasmid and cloned into Flag and myc pcDNA3 . 1/Zeo . The Triad3A point mutant S320D was introduced by Quickchange Kit according to the manufacturer's instructions ( Stratagene ) . DNA sequencing was performed to confirm the mutation . Triad3A shRNA1 targeting nucleotide sequence ( 1 , 532–1 , 551 ) 5′-GAGCAGGAGTTCTATGAGCA-3′ , shRNA2 targeting nucleotide sequence ( 1 , 195–1 , 214 ) 5′-GGACACTATGCAATCACCCG-3′ and shRNA control have been previously described [40] . Human TRAF3 cDNA was amplified from pKR5 Flag-TRAF3 and pKR5 Flag-TRAF3 Y440A/Q442A expression plasmids provided by Dr . Genhong Cheng ( UCLA , USA ) and were cloned into Flag pcDNA3 . 1/Zeo . Mg132 , lactacystin and E64 were purchased from Calbiochem . dsRNA was purchased from Invivogen . A549 cells were infected with Sendai virus ( 40 HAU/ml ) for 16h and were treated with either Mg132 ( 10µM ) , lactacystin ( 5µM ) or E64 ( 5µM ) 6h p . i . Transfections for Luciferase assay were carried out in 293T cells grown in Dulbecco's modified Eagle's medium ( Invitrogen ) supplemented with 10% fetal bovine serum and antibiotics . Subconfluent 293T cells were transfected with 100 ng of pRLTK reporter ( Renilla luciferase for internal control ) , 200 ng of pGL-3 reporter ( firefly luciferase , experimental reporter ) , 200 ng of ΔRIG-I , MDA5 , CD4-TLR3 , MAVS , TRIF , IKKε , or TBK1 expression plasmids , 200 ng of pcDNA3 or Flag Triad3A/Flag Triad3A S320D pcDNA3 , and 100ng of IRF-7 plasmid as indicated by calcium phosphate co-precipitation method . The reporter plasmids were: IFNB pGL3 , ISRE-luc , NF-κB pGL3 , and IFNA4 pGL-3 reporter genes; the transfection procedures were previously described [53] . At 24h after transfection , the reporter gene activities were measured by Dual-Luciferase Reporter Assay , according to manufacturer's instructions ( Promega ) . Where indicated , cells were treated with Sendai virus ( 40 HAU/ml ) for the indicated time or 16h for luciferase assays . Human A549 cells were cultured in F12K medium ( Wisent Inc . ) supplemented with 10% fetal bovine serum , glutamine and antibiotics . A549 cells were transfected either with dsRNA ( 20µg/ml ) for 6h or infected with VSV-AV1 ( multiplicity of infection of 1 ( MOI ) ) for 16h or Sendai virus ( 40 HAU/ml ) for 16h . shRNA1 Triad3A and shRNA Control were transfected into A549 cells by using the Fugene 6 transfection reagent ( Roche Applied Sciences ) . Cells were selected beginning at 48h post-transfection for 3 weeks in Dulbecco's modified Eagle's medium containing 10% heat-inactivated calf serum , glutamine , antibiotics , and 2 µg/ml G418 ( Invitrogen ) ; individual clones were screened for maximal knockdown of Triad3A by immunoblot . 293T cells were transiently transfected with 2 . 5 µg Flag-TRAF3 , 250 ng myc-Triad3A , 250 ng myc-Triad3A S320D and 1 µg HA-Ubiquitin expression plasmids . At 6h post-transfection , cells were treated with 10 µM of Mg132 where indicated . Samples were harvested 24h post-transfection , lysed using a 1% NP-40 lysis buffer ( 50 mM Tris-HCL ph 7 . 5 , 150 mM NaCl , 5mM EDTA , 50 mM NaF , 1% NP-40 , 10% glycerol , 30 mMβ-glycerophosphate , 1mM orthovanadate ( Na3VO4 ) , 1 mM phenyl-methyl-sulfonyl fluoride ( PMSF ) ) supplemented with 0 . 1% protease inhibitor cocktail ( Sigma-Aldrich , Oakville , Ont . ) and the deubiquitinase inhibitor N-ethylmaleimide ( NEM , 10 mM , Sigma-Aldrich , Oakville , Ont ) . Samples were boiled for 10 minutes in 1% SDS and diluted 10 times in lysis buffer . 250 µg of proteins were then immunoprecipitated overnight at 4°C with constant agitation with 0 . 5 µg of anti-Flag ( M2; Sigma-Aldrich ) crosslinked to 30 µl of protein A/G PLUS-Agarose ( Santa Cruz Biotechnology ) . Immunoprecipitated protein was washed 4 times with supplemented lysis buffer , denatured in 2% SDS-loading dye , and loaded onto a 7 . 5% acrylamide gel for SDS-PAGE analysis followed by transfer to nitrocellulose membrane . Polyubiquitination was detected by immunoblotting with a monoclonal anti-HA antibody ( Sigma-Aldrich , Oakville , Canada ) . A549 cells were infected with Sendai virus ( 40 HAU/ml ) in the presence of 5 µM of lactacystin and samples were collected every 4h p . i . Samples were lysed as previously described and samples were boiled for 10 minutes in 1% SDS and diluted 10 times in lysis buffer . 500 µg of proteins were then immunoprecipitated overnight at 4°C with constant agitation with 0 . 5 µg of anti-TRAF3 ( sc-6933 Santa Cruz , USA ) crosslinked to 30 µl of protein A/G PLUS-Agarose ( Santa Cruz Biotechnology ) . Immunoprecipitated protein was washed 4 times with supplemented lysis buffer , denatured in 2% SDS-loading dye , and loaded onto a 7 . 5% acrylamide gel for SDS-PAGE analysis followed by transfer to nitrocellulose membrane . Polyubiquitination was detected by immunoblotting with polyclonal Lys48 and Lys63 anti-ubiquitin specific antibodies ( Millipore , USA ) . Cells were lysed in lysis buffer ( 50 mM Tris-HCl , pH 7 . 5 , 250 mM NaCl , 0 . 5% NP-40 ) supplemented with 0 . 1% protease inhibitor cocktail ( Sigma-Aldrich , Oakville , Canada ) . 250 µg of proteins were then immunoprecipitated overnight at 4°C with constant agitation with either 0 . 5 µg of anti-myc ( 9E10; Sigma-Aldrich ) or 0 . 5 µg of anti-Flag ( M2; Sigma-Aldrich ) or 0 . 5 ug of anti-TRAF3 crosslinked to 30 µl of protein A/G PLUS-Agarose ( Santa Cruz Biotechnology ) . After extensive washing with lysis buffer , the immunocomplexes were analyzed by immunoblotting as described . Whole cell extracts ( 20–40 µg ) were separated in 7 . 5–12% acrylamide gel by SDS-PAGE and were transferred to a nitrocellulose membrane ( BioRad , Mississauga , Canada ) at 4°C for 1h at 100 V in a buffer containing 30 mM Tris , 200 mM glycine and 20% ( vol/vol ) methanol . Membranes were blocked for 1h at room temperature in 5% ( vol/vol ) dried milk in PBS and 0 . 1% ( vol/vol ) Tween-20 and then were probed with primary antibodies . Anti-Flag ( M2 ) , anti-Hemagglutinin HA ( H7 ) , or anti-myc ( 9E10 ) each at a concentration of 1 µg/ml were purchased from Sigma-Aldrich ( Sigma-Aldrich , Oakville , Canada ) ; anti-MAVS ( 1∶1000 , in-house previously described [14] ) were prepared in blocking solution plus 0 . 02% sodium azide . Anti-IRF-3 ( 1∶5000 , IBL , Japan ) , anti-β-Actin ( 1∶5000 , MAB1501 Millipore , USA ) , anti-Triad3A ( 1∶1000 , ProSci Inc . USA ) , anti-RIG-I ( 1∶1000 , rabbit polyclonal Ab , previously described [14] ) , anti-VSV ( 1∶3000 , rabbit polyclonal Ab raised against VSV proteins G , N , and M ) , anti-ISG56 ( 1∶1000 , gift from Dr . Ganes Sen , Cleveland Clinic ) , anti-TRAF3 ( 1 µg/ml , sc-6933 Santa Cruz , Cal , USA ) , anti-IRF-3 Ser 396 ( 1∶1000 , rabbit anti-peptide Ab , previously described [54] ) , and Lys48 and Lys63 anti-ubiquitin specific antibody ( 1∶1000 , Millipore , USA ) were prepared in 3% BSA/PBS/0 . 03% sodium azide . Whole cell extracts were prepared in Nonidet P-40 lysis buffer ( 50 mM Tris , pH 7 . 4 , 150 mM NaCl , 30 mM NaF , 5 mM EDTA , 10% glycerol , 1 . 0 mM Na3VO4 , 40 mM β-glycerophosphate , 0 . 1 mM phenylmethylsulfonyl fluoride , 5 µg/ml of each leupeptin , pepstatin , and aprotinin , and 1% Nonidet P-40 ) , and then were subjected to electrophoresis on 7 . 5% native acrylamide gels , which were pre-run for 30 min at 4°C . The electrophoresis buffers were composed of an upper chamber buffer ( 25 mM Tris , pH 8 . 4 , 192 mM glycine , and 1% sodium deoxycholate ) and a lower chamber buffer ( 25 mM Tris , pH 8 . 4 , 192 mM glycine ) . Gels were soaked in SDS running buffer ( 25 mM Tris , pH 8 . 4 , 250 mM glycine , 0 . 1% SDS ) for 30 min at 25°C and were then electrophoretically transferred on Hybond-C nitrocellulose membranes ( Amersham Biosciences ) in 25 mM Tris , pH 8 . 4 , 192 mM glycine , and 20% methanol for 1 h at 4°C . Membranes were blocked in phosphate-buffered saline containing 5% ( vol/vol ) nonfat dry milk and 0 . 05% ( vol/vol ) Tween 20 for 1 h at 25°C and then were blotted with an antibody against IRF-3 ( 1 µg/ml ) in blocking solution for 1 h at 25°C . After washing the membranes five times in phosphate-buffered saline/0 . 05% Tween , they were incubated for 1 h with horseradish peroxidase-conjugated goat anti-rabbit IgG ( 1∶4000 ) in blocking solution . Immunoreactive bands were visualized by enhanced chemiluminescence ( Amersham Biosciences ) . Quantitative PCR assays were performed in triplicate using the AB 7500 Real-time PCR System ( Applied Biosystems ) . The primers used were as follows: IFN-ß , 5′-TTGTGCTTCTCCACTACAGC-3′ ( forward ) and 5′-CTGTAAGTCTGTTAATGAAG-3′ ( reverse ) ; IFN-α2 , 5′-CCTGATGAAGGAGGACTCCATT-3′ ( forward ) and 5′-AAAAAGGTGAGCTGGCATACG-3′ ( reverse ) ; ISG15 , 5′-AGCTCCATGTCGGTGTCAG-3′ ( forward ) and 5′-GAAGGTCAGCCAGAACAGGT-3′ ( reverse ) ; ISG56 5′-CAACCAAGCAAATGTGAGGA-3′ ( forward ) and 5′-AGGGGAAGCAAAGAAAATGG-3′ ( reverse ) ; CXCL10 5′-TTCCTGCAAGCCAATTTTGTC-3′ ( forward ) and 5′-TCTTCTCACCCTTCTTTTTCATTGT-3′ ( reverse ) ; STAT1 5′-CCTGCTGCGGTTCAGTGA-3′ ( forward ) and 5′-TCCACCCATGTGAATGTGATG-3′ ( reverse ) ; ß-Actin , 5′-CCTTCCTGGGCATGGAGTCCT-3′ ( forward ) and 5′-AATCTCATCTTGTTTTCTGCG-3′ ( reverse ) . All data are presented as a relative quantification with efficiency correction based on the relative expression of target genes versus ß-Actin as reference gene . Standard curves and PCR efficiencies were obtained using serial dilutions of pooled cDNA prepared from stable shRNA1 Triad3A and shRNA control A549 cells infected with Sendai virus ( 40 HAU/ml ) for 12h . Data were then collected using the AB 7500 Real-time PCR System ( Applied Biosystems ) and analyzed by comparative CT method using the SDS version 1 . 3 . 1 Relative Quantification software . The supernatants from stable shRNA Triad3A and shRNA Control cells infected with Sendai virus ( 40 HAU/ml ) were collected at 12h p . i . The concentrations of IFN-β and IFN-α in the supernatants were measured using ELISA kits ( PBL Biomedical Laboratories , Piscataway , NJ ) .
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RNA virus infection is detected through TLR-dependent and TLR-independent mechanisms . Early viral replicative intermediates are detected by two recently characterized cystolic viral RNA receptors , RIG-I and MDA-5 , leading to the production of pro-inflammatory cytokines and type I interferons ( IFNs ) . Dysfunctional responses , either failure to respond or hyper-responsiveness , may lead to both acute and chronic immunodeficiency and inflammatory diseases . Thus , the intensity and duration of RLR signaling must be tightly controlled . One general mechanism by which innate immune receptors and their downstream adapters are regulated involves protein degradation mediated by the ubiquitination pathway . Our study demonstrates that the E3 ubiquitin ligase Triad3A negatively regulates the RIG-I-like receptor pathway by targeting the adapter molecule TRAF3 for proteasomal degradation through Lys48-linked ubiquitin-mediated degradation . Thus , Triad3A represents a key molecule involved in the negative regulation of the host antiviral response triggered by RNA virus infection .
|
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2009
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The E3 Ubiquitin Ligase Triad3A Negatively Regulates the RIG-I/MAVS Signaling Pathway by Targeting TRAF3 for Degradation
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Varicella zoster virus ( VZV ) , a human alphaherpesvirus , causes varicella during primary infection . VZV reactivation from neuronal latency may cause herpes zoster , post herpetic neuralgia ( PHN ) and other neurologic syndromes . To investigate VZV neuropathogenesis , we developed a model using human dorsal root ganglia ( DRG ) xenografts in immunodeficient ( SCID ) mice . The SCID DRG model provides an opportunity to examine characteristics of VZV infection that occur in the context of the specialized architecture of DRG , in which nerve cell bodies are ensheathed by satellite glial cells ( SGC ) which support neuronal homeostasis . We hypothesized that VZV exhibits neuron-subtype specific tropism and that VZV tropism for SGC contributes to VZV-related ganglionopathy . Based on quantitative analyses of viral and cell protein expression in DRG tissue sections , we demonstrated that , whereas DRG neurons had an immature neuronal phenotype prior to implantation , subtype heterogeneity was observed within 20 weeks and SGC retained the capacity to maintain neuronal homeostasis longterm . Profiling VZV protein expression in DRG neurons showed that VZV enters peripherin+ nociceptive and RT97+ mechanoreceptive neurons by both axonal transport and contiguous spread from SGC , but replication in RT97+ neurons is blocked . Restriction occurs even when the SGC surrounding the neuronal cell body were infected and after entry and ORF61 expression , but before IE62 or IE63 protein expression . Notably , although contiguous VZV spread with loss of SGC support would be predicted to affect survival of both nociceptive and mechanoreceptive neurons , RT97+ neurons showed selective loss relative to peripherin+ neurons at later times in DRG infection . Profiling cell factors that were upregulated in VZV-infected DRG indicated that VZV infection induced marked pro-inflammatory responses , as well as proteins of the interferon pathway and neuroprotective responses . These neuropathologic changes observed in sensory ganglia infected with VZV may help to explain the neurologic sequelae often associated with zoster and PHN .
Varicella-zoster virus ( VZV ) , a human alphaherpesvirus , causes varicella , characterized by a T cell-mediated viremia and a generalized vesicular rash [1] . During varicella infection , virions gain access to nerve cell bodies and establish latency , persisting for the life of the host . VZV reactivation from neuronal latency may cause herpes zoster , with pain and rash corresponding to the affected dermatome , and may be complicated by post herpetic neuraliga [2] . VZV reactivation can also produce chronic radicular pain without skin lesions ( zoster sine herpete ) , cranial nerve palsies and other neurologic syndromes [2] . Investigating VZV neuropathogenesis is difficult because of its marked restriction for its natural human host . While VZV readily infects and replicates in neurons derived from embryonic stem cells and neuronal cell lines , these systems do not model the in vivo heterogeneity of DRG neuronal subpopulations and their associated satellite glial cells ( SGC ) . DRG neurons derive from successive waves of migrating neural crest cells which differentiate into the two principal morphologic subtypes , which are “large , light” and “small , dark” neurons . Large light neurons comprise 30–40% of adult differentiated DRG neurons and have myelinated A beta-fibers with specialized mechanoreceptive termini in skin [3] . Small dark neurons with unmyelinated C-fibers or thinly myelinated A delta-fibers have “pain sensing” nociceptive free nerve endings in skin and comprise 40–60% of DRG neurons [4 , 5] . DRG are comprised of a structured tissue architecture in which individual ganglionic neurons are ensheathed by a single layer of SGC forming a neuron-satellite cell complex ( NSC ) , which is a single functional unit in which SGC support neuronal homeostasis [6–8] . The neuronal surface has membrane protrusions that extend between laminar SGC [9] , which are separated from the neuronal plasma membrane by a gap of 15–20 nm [8] . SGC participate in neuronal signaling , as well as pathological degeneration and regeneration of axons [8] . To examine VZV replication and spread within an intact ganglionic architecture , we developed a model using human dorsal root ganglion ( DRG ) xenografts in mice with severe combined immune deficiency ( SCID ) [10] . Intact DRG xenografts are maintained without rejection under the renal capsule of SCID mice ( reviewed in ref . [11] ) . DRG xenografts contain clusters of heterogeneous nerve cell bodies , ensheathed by SGC , as well as axonal projections within their typical tissue microenvironments . This model provides an opportunity to examine viral determinants of VZV neurotropism , susceptibility of neuronal subtypes to infection and the characteristics of VZV-related polykaryon formation and spread between neurons and satellite cells during VZV replication in sensory ganglia in vivo , in the absence of VZV-specific adaptive immunity . These conditions could occur for a limited period during primary infection and may account for the occasional appearance of a zoster-like rash during varicella in the healthy host , and could also occur during the few days following reactivation , or perhaps longer in elderly and immunocompromised patients who have low frequencies of VZV-specific responder T cells and a slow expansion and mobilization of an effective adaptive immune response to the affected ganglion . Our previous work using the DRG model established that even though both VZV and herpes simplex virus ( HSV ) -1 infect sensory ganglia , VZV replicates in SGC and can induce cell-cell fusion between SGC and neurons in neuron-satellite cell complexes ( SCC ) [12] , whereas HSV-1 does not [13] . Neuron-satellite cell fusion is also observed in ganglia from patients with zoster at the time of death , indicating that SGC tropism is a component of VZV neurovirulence [14] . To further investigate VZV neuropathogenesis , we hypothesized that VZV would exhibit specificity for neuronal subtypes and that the capacity to infect SGC would facilitate VZV spread in DRG and contribute to VZV-related ganglionopathy . Here , we further characterized the differentiation of neurons in DRG xenografts and show that VZV replication is restricted in RT97-immunoreactive mechanoreceptive neurons compared to peripherin-positive nociceptive neurons , based on patterns of VZV protein expression and intracellular localization . In addition , the susceptibility of SGC to VZV replication is implicated as a factor in neuronal cell loss . Finally , we document changes in the DRG tissue milieu due to the induction of cellular factors with antiviral and neuroprotective functions as well as marked upregulation of proinflammatory proteins associated with neuronal damage . Our observations identify neuropathologic changes in sensory ganglia due to VZV infection that help to account for the long lasting neurologic sequelae often associated with herpes zoster or zoster sine herpete .
To investigate the subtype specificity of VZV neurotropism , we first evaluated neuronal differentiation in DRG xenografts before transplantation , at 18 gestational weeks , and at 20 weeks after transplantation . At 18 weeks gestation , by which time major events in human sensory neurogenesis are complete , fetal DRG were densely packed with sensory neurons and nerve fibers extending from the dorsal root ( Fig 1A , black arrow ) . All DRG neurons expressed the pan-neuronal cell markers , neural cell adhesion molecule ( N-CAM ) and synaptophysin ( Fig 1B ) in their expected membrane and cytoplasmic patterns , respectively . Whereas both mature and immature nociceptive neurons express the cytoplasmic neurofilament subunit peripherin [15] , differentiated mechanoreceptive neurons acquire cytoplasmic expression of the 200 kDa neurofilament ( NF200 ) subunit , which has a phosphoepitope recognized by the RT97 antibody [16]; this marker is present in all neuronal nuclei during growth phase [17] . Prior to DRG implantation , RT97 immunoreactivity was restricted to neuronal nuclei and cytoplasmic immunoreactivity was absent , indicating an immature neuronal immunophenotype ( Fig 1C ) ; however , by 20 weeks after implantation , mature mechanoreceptive neurons ( Fig 1D , yellow arrow ) were readily identified by cytoplasmic RT97 immunoreactivity . As expected , the neurofilament subunit peripherin was detected in the cytoplasm of small-diameter neurons only ( Fig 1D , white arrow ) . Quantitative neuronal immunophenotyping demonstrated that 38 . 9% of neurons were nociceptive ( peripherin-positive ) and 26 . 7% were mechanoreceptive neurons ( cytoplasmic RT97-positive ) at 20 weeks after implantation ( Fig 1E ) . 22 . 7% of DRG neurons were dual RT97-peripherin positive ( Fig 1D , orange arrow ) and 10 . 3% did not express either marker ( Fig 1E ) . Of note , adult ganglia have subpopulations of dual RT97+/peripherin+ neurons [3 , 4] . Thus , continued neuronal differentiation in DRG xenografts resulted in proportions of neuronal subtypes found in postnatal and adult human ganglia [5 , 18 , 19] . The typical DRG tissue architecture was confirmed at 20 weeks after implantation by the presence of neuronal structures such as the axon hillock , the junction between the nerve cell body and the projecting axon ( Fig 2A , white arrow ) , and nerve bundles containing both mechanoreceptive ( RT97+ ) and nociceptive ( peripherin+ ) nerve fibers extending throughout the DRG xenograft ( Fig 2B ) as well as into the murine renal tubule network ( Fig 2C , white arrow ) . The survival of neurons and axons within the xenografts and extensions into the murine kidney indicated that the growth properties of differentiated DRG neurons were intact despite absence of orthotopic synaptic partners . These properties also indicated that the capacity of SGC to maintain neuronal homeostasis by producing neurotrophins , including NGF and other factors , was preserved [20] . Neurotrophins secreted in murine nephrons may act as axon guidance cues [21 , 22] . The presence of thick myelin-wrapped nerve fibers was demonstrated by transmission electron microscopy ( Fig 2D , black arrow ) . DRG xenografts maintained a mature DRG architecture for at least 80 weeks after implantation , with comparative proportions of RT97 and peripherin positive neurons as observed at 20 weeks after transplantation , and including physical features such as a visible dorsal root ( Fig 2E , black arrow ) , axon bundles and clusters of small , dark-appearing ( Fig 2F , inset , white arrow ) and large , light-appearing ( Fig 2F , inset , yellow arrow ) nerve cell bodies . In previous work , we demonstrated efficient replication of VZV ( recombinant parent Oka strain ) in DRG xenografts at 4–12 weeks after implantation , peaking at 14 days after inoculation [10 , 23] . To assess VZV infection during the earliest stages of spread in differentiated neurons , we examined DRG xenografts inoculated at 25 weeks with recombinant parent Oka strain VZV-infected fibroblasts exhibiting high cytopathic effect which results in low titer ( 330 PFU/implant; 10 microliters ) . DRG xenografts were recovered at 3 , 7 , and 10 days as well as at 14 days after infection [10 , 23] . Patterns of spread were identified by analyzing IE63 expression and VZV genomic DNA in sequential tissue sections containing clusters of nerve cell bodies that exhibited cytopathic effects . No VZV protein or viral genomes were detected in either neurons or SGC at three days after inoculation and the DRG tissue architecture showed no disruption , indicating that inoculum cells are not identified in the DRG and that an eclipse phase occurs during which secondary replication remains below the threshold of detection . At day 7 , IE63 was detected within nerve fibers ( Fig 3A , black arrow ) , along the nerve root , and in regions containing neuronal cell bodies ( Fig 3B , black arrow ) . In some regions , IE63 expression was observed in neurons but not in their surrounding SGC ( Fig 3B and 3C , orange arrow ) , or in non-neuronal supportive cells , showing that neuronal infection was not due to contiguous spread . Staining of adjacent tissue sections did not reveal any IE63 expression in neighboring SGC , indicating that initial VZV spread to neuronal cell bodies may occur axonally following virion entry at axon terminal sites within DRG xenografts . Neurons expressing IE63 were also observed with IE63 staining in the SGC encapsulating the neuron ( Fig 3C , black arrow ) . In addition , IE63 positive SGC were observed surrounding IE63 negative neurons ( Fig 3B , yellow arrow ) , indicating that VZV may spread between contiguous NSC by infection of SGC . Examination of VZV DNA localization showed the same patterns as IE63 expression ( Fig 3D and 3E ) , providing further evidence for both axonal transfer and contiguous spread from SGG into neurons . Notably , VZV DNA-positive neurons exhibited characteristics of axonal neuropathy , such as chromatolysis ( Fig 3E and 3F , arrow ) , a cell body reaction that indicates activation of axonal repair processes [24] . By day 14 after infection , neuronal and SGC cytopathic effects were extensive ( Fig 3G ) . SGC infection allows secondary infection of SGC in the adjacent NSC , enabling viral access to another neuronal cell body within the ganglion . Because some neurons with large diameter morphology did not exhibit cytopathic changes ( Fig 3G , black arrow ) or express IE63 ( Fig 3H , black arrow ) , even where DRG infection was widespread , we next analyzed expression of VZV proteins in sections stained for peripherin and the RT97 marker ( Fig 4A and 4B ) . When using an anti-VZV human polyclonal antibody , peripherin/VZV dual positive neurons were readily identified ( Fig 4B , white arrows ) . We then examined IE63 protein expression in neurons that were positive or negative for the RT97 marker of mature mechanoreceptive neurons . More than 250 neurons were examined in tissue sections from three DRG recovered 7–14 days after infection; a representative image is shown ( Fig 4C ) . Overall , 41 . 3% of all neurons were RT97 positive and 36 . 5% were IE63 positive . Of the IE63 positive neurons , only 16 . 9% were RT97 positive , whereas 83 . 1% were RT97 negative ( Fig 4E , p<0 . 0001 , t test ) . The proportion of neurons expressing RT97 in infected and uninfected DRG was equivalent , indicating that the difference did not reflect down regulation of the RT97 marker by VZV . These results indicated that RT97+ neurons have a restricted capacity to support lytic VZV infection . Notably , neurons that were IE63 negative despite being encapsulated by IE63 positive SGC consistently belonged to the RT97 subpopulation ( Fig 4D ) . During primary infection , VZV reaches ganglia by retrograde axonal transport from nerve endings in skin lesions and hematogenously through transport by infected T cells ( reviewed in ref . [11] ) . Unlike cell-cell fusion and syncytia formation observed in cultured cells and skin , VZV-infected T cells release virus particles but do not undergo fusion [25] . To determine if the characteristics of VZV spread and subtype specific restriction might be an artifact of some capacity of infected fibroblasts to initiate VZV transfer by cell-cell fusion , which would not occur during natural infection , DRG xenografts were inoculated with VZV-infected T cells ( 1067 PFU/implant ) and examined at 14 days after infection . The same patterns of axonal and contiguous VZV spread were observed ( Fig 4F ) and again infection was restricted within the RT97 positive subpopulation after T cell transfer ( Fig 4G ) . Expression of the ORF23 capsid protein and the ORF61 and IE62 viral regulatory proteins , which are made first and before IE63 in newly infected cells in vitro [26] , was used to define the block of VZV infection in RT97+ neurons . ORF23 capsid protein expression in nuclear puncta marks the incoming virions in cell culture [26] . In DRG , ORF23 appeared in rare clusters of neurons at 7 days after infection as discrete dim puncta at the nuclear rim , shown by co-staining for nuclear lamins ( Fig 5A , white arrow ) . ORF23 puncta formed a nearly complete ring in some neurons , without IE62 ( Fig 5B , white arrows ) or IE63 ( Fig 5C , white arrow ) . In other neurons , ORF23 expression was intense along a crenellated nuclear rim , often accompanied by reorganization of promyelocytic leukemia protein ( PML ) nuclear bodies ( Fig 5D , white arrow ) at 7–10 days . PML nuclear bodies are first reorganized and later dispersed as VZV infection progresses ( Fig 5D , yellow arrow ) [26 , 27] . Crenelated nuclear rim expression and ORF23 expression in globular domains was accompanied by IE63 expression ( Fig 5A and 5C , yellow arrows ) . Both of these patterns indicate later stages of VZV infection . Controls including infected DRG tested with preimmune rabbit anti-ORF23 serum ( Fig 5E ) and uninfected DRG tested with anti-ORF23 were negative ( Fig 5F ) . ORF23 nuclear rim staining did not differ in neurons in relation to their expression of the RT97 marker , showing entry had occurred . In the representative example shown ( Fig 5G and 5H ) , discrete ORF23 nuclear rim staining was observed in both IE63+/RT97 negative ( Fig 5G and 5H , inset box G1 ) and IE63-/RT97+ neurons ( Fig 5G and 5H , inset box G2 ) . ORF61 is critical to disrupt PML nuclear bodies in skin in vivo [27] . In DRG , ORF61 was localized to neuronal nuclei , as occurs shortly after VZV entry ( Fig 6A ) [26] and limited ORF61 expression was associated with dim and diffuse PML detection in neurons ( Fig 6A , white arrows ) . In contrast , PML nuclear bodies were dispersed when ORF61 expression was increased and present in both the nuclei and cytoplasm of infected neurons ( Fig 6A , yellow arrow ) . PML nuclear bodies were also dim and diffuse in the nuclei of uninfected neurons within VZV-infected DRG ( Fig 6A , orange arrow and Fig 6F , white arrow ) . When ORF61 expression was evaluated along with the RT97 marker , 37 . 4% of ORF61 positive neurons were RT97 positive and 62 . 6% were RT97 negative ( p = ns , t test ) ( Fig 6B: representative image ) . However , ORF61 was predominantly nuclear in RT97 positive neurons ( Fig 6B , white arrow ) whereas RT97 negative neurons had cytoplasmic ORF61 expression ( Fig 6B , yellow arrows ) . IE62 is the major viral transactivator and functions to block the interferon ( IFN ) pathway in VZV-infected cells [28 , 29] . At 7–10 days after infection , IE62 appeared in discrete puncta along the nuclear rim ( Fig 6D , yellow arrow and box D1 on right ) , in the absence of IE63 . IE62 expression was more intense within larger intranuclear domains in DRG neurons when diffuse and faint IE63 nuclear expression became detectable , indicating progression of infection ( Fig 6D , orange arrow and box D2 on right ) . The formation of IE62-positive intranuclear domains was associated with reorganized PML although IE62 did not completely co-localize with PML nuclear bodies ( Fig 6E , white arrow ) , consistent with observations in vitro . PML were reorganized prior to IE63 expression ( Fig 6G , white arrow ) . Cytoplasmic IE62 was extensive in neurons with markers of late infection , including plasma membrane dissolution and fusion of neurons and their encapsulating SGC ( Fig 6D , white arrow ) , and the presence of large PML nuclear bodies that sequester VZV nucleocapsids and inhibit viral replication ( Fig 6F , yellow arrow ) [30] . Notably , only 17 . 1% of the IE62 positive neurons were RT97 positive and 82 . 9% were RT97 negative ( p<0 . 0002 , t test ) ( Fig 6H; representative image ) . When IE62 expression was observed in RT97 positive neurons , it was predominantly nuclear; IE62 cytoplasmic expression was rare in this subpopulation ( Fig 6H , yellow arrows ) . Thus , although ORF61 was produced regardless of neuronal subtype , the restriction of VZV replication in RT97+ neurons was associated with low or no IE62 expression , which would impair progression to lytic replication . By 70 days after infection , VZV proteins and infectious virions are no longer produced in DRG xenografts but low copies of viral genomes persist , similar to latently infected human cadaver ganglia [10] . Whereas uninfected DRG retained a normal tissue architecture over this period ( Fig 2E ) , VZV-infected DRG exhibited fibrotic areas and clusters of SGC proliferations , referred to as Nageotte nodules , which mark sites of neuronal disappearance ( Fig 3I , black arrow ) [24] . Notably , even though VZV infection was restricted in RT97+ neurons , most neurons present at this late stage were peripherin positive while RT97+ neurons were almost entirely absent ( Fig 7A ) , and Nageotte nodules were abundant ( Fig 7A , white arrows ) . Only 3% of neurons were RT97 positive while 79% were peripherin-positive , demonstrating a significant loss of the mechanoreceptive subtype . The remainder expressed both peripherin and RT97 or neither marker , indicating a non-mechanoreceptive phenotype . Two VZV mutants , rOka-delta_gI , with a complete gI deletion , and rOka-gE/deltaCys , with a mutation blocking gE/gI heterodimer formation , infect SGC but are deficient for VZV-induced SGC-neuron membrane fusion and had little spread in DRG , as previously described [23] . Thus , infecting DRG with these mutants made it possible to evaluate effects on infection limited primarily to the contributions of SGC to neuronal survival . DRG infected with rOka-gE/deltaCys showed restricted IE63 expression in RT97 positive neurons at 28 days ( Fig 7B ) with selective loss of neurons of the RT97 subtype at day 56 , and the appearance of Nageotte nodules ( Fig 7C , white arrow ) . Similarly , IE63 was primarily limited to SGC and non-neuronal cells in rOka-delta_gI infected DRG ( Fig 7D , white arrow ) . Neuronal cell loss was observed and was selective for RT97+ neurons , further indicating that SGC infection leads to neuronal loss and the RT97+ neurons are more susceptible to the neuropathic effects of ganglionic infection . Cellular factors produced by SGC regulate homeostasis as well as having macrophage-like functions [8] and neurons have intrinsic responses to stress . In these experiments , proteins made by DRG resident cells were profiled using multiplex arrays to test lysates from four VZV-infected DRG recovered at peak replication , 14 days after infection , and from two mock-infected xenografts ( injected with an equal number of uninfected fibroblasts ) . Concentrations of 18 human cell proteins were significantly increased in VZV-infected DRG lysates , one was significantly decreased , and 33 human proteins were unchanged at 14 days ( Fig 8 and S1 Fig and S2 Fig ) . IFN-alpha , IFN-gamma and IFN-induced proteins IP10/CXCL10 and monocyte-chemoattracting protein MCP-1/CCL2 were significantly increased ( 2 . 5 , 2 . 8 20 . 0 and 7 . 7-fold , respectively ) in VZV-infected DRG . These cytokines are upregulated in peripheral neuroinflammatory responses and in rodent models of neuropathic pain [31 , 32] . IL-1-alpha , IL-6 and IL-8 and RANTES were also significantly increased ( 13 . 1 , 7 . 9 , 16 . 2 and 11 . 3-fold , respectively ) ; these pro-inflammatory cytokines contribute to inflammatory hypernocicepetion [33–35] . Conversely , TGF-beta , a potent anti-inflammatory cytokine with pleotropic regulatory effects , was also increased ( 4 . 4-fold ) . TGF-beta negatively regulates hepatocyte-growth factor ( HGF ) which was decreased 2 . 9 fold , and positively regulates the prosurvival cytokines IL-2 [36] and NGF [20] . Overall , VZV infection elicited dramatic changes in the DRG cytokine milieu , inducing proteins that damage neurons along with some neuroprotective factors , in the absence of adaptive T cell immunity , which is lacking in SCID mice .
These observations demonstrating neuronal subtype specificity of VZV replication and the role of SGC in viral spread within ganglia provide new insights about mechanisms of VZV neuropathogenesis and zoster-related neuropathology , as modeled in Fig 9 . In the human host , primary VZV infection begins in respiratory epithelial cells , followed by viral transfer into T cells in tonsils and other local lymph nodes ( Fig 9A ) and trafficking of the infected T cells to the target cells in skin or spinal ganglia that support viral replication ( Fig 9B ) [10 , 37] . VZV replication in skin allows virions to enter the termini of neuronal axons with free nerve endings , which are extensive around hair follicles ( Fig 9C ) and epidermal stem cells lining the follicles are highly permissive for VZV [37] . By analogy with other alphaherpesviruses , the retrograde axonal transport machinery is presumed to move VZ virions to the cell bodies of sensory neurons where lytic infection or latency ensues ( Fig 9D ) . In contrast , when VZV is transported into DRG and released from infected T cells , the architecture of the neuron-satellite cell complex means that infection is most likely initiated in SGC prior to VZV reaching the neuron cell body ( Fig 9E and 9F ) . In the natural host , tight control of ganglion infection is predicted during primary VZV infection or when VZV reactivates from latency through mechanisms of gene silencing and intrinsic antiviral responses of neurons and SGC [8 , 38] . In the healthy individual , innate inhibition is reinforced by VZV-specific T cells , that are detected ~72 hours after varicella onset [39] and expand to high frequencies during herpes zoster [1] . However , if neuronal replication is not controlled , viral particles may cross the small gap between neuronal and SGC cell membranes , initiating infection of encapsulating SGC . Since NSC are closely packed within sensory ganglia , VZV can then spread to SGC that surround adjacent neurons ( Fig 9F ) . The potential for productive infection of neurons and neuron-SGC spread during primary VZV infection is supported by clinical observations that individuals with varicella may also have a dermatomal zosteriform rash . During VZV reactivation , contiguous NSC-NSC spread with viral transfer into new neuronal cell bodies has the potential to amplify VZV delivery to skin sites of replication , thereby increasing the extent of the dermatomal rash and enhancing transmission to susceptible individuals . At the same time , virus produced in new skin lesions generates opportunities for virion entry into other axons , allowing the virus to ‘colonize’ more neurons by retrograde transport during reactivation . Profiling VZV protein expression in DRG neurons showed that VZV reaches RT97+ neuronal cell bodies within DRG xenografts but productive replication was restricted . Neurons expressing this marker were resistant to the virus even when encapsulating SGC were infected . Importantly , this discovery was possible using DRG maintained longterm in SCID mice because neuronal differentiation occurred , subtype heterogeneity was established with the proportions of the two major neuronal subtypes being equivalent to those found in adult human ganglia [5] and SGC retained the capacity to support neurons . Since SGC are critical for maintaining neuronal homeostasis , loss of SGC function as a consequence of VZV infection would be predicted to affect the survival of both nociceptive and mechanoreceptive neurons . Notably , even though RT97+ neurons had the capacity to restrict VZV replication , neurons expressing this marker showed selective loss relative to peripherin+ neurons at later times in DRG infection when contiguous spread was extensive . Quantitative studies demonstrate that NSC of large-diameter neurons have more SGC , suggesting they are more dependent on SGC-mediated metabolic support than small diameter neurons [40 , 41] . Small diameter neurons also exhibit a higher resistance to toxins , such as mercury [42] . Alternatively , loss of RT97+ neurons could be a consequence of abortive VZV infection . VZV IE63 expression , which is blocked in RT97+ neurons , has been shown to suppress apoptosis in VZV-infected neuronal cultures [43] . Neuronal destruction is associated with SGC-mediated neuronophagia , which refers to the scavenging by SGC of cell debris resulting from neuronal cell death , and is detected by formation of Nageotte nodules or SGC hypertrophy where neuronal cell loss has occurred [44] . These structures were observed in VZV-infected DRG at late stages of infection , when RT97+ neurons were largely absent ( Fig 9G ) . We propose that the cytopathic response to abortive infection in mechanoreceptive neurons , loss of SGC function or both may explain some sequelae often associated with herpes zoster and PHN , such as mechanical allodynia . As a correlate , clinical studies have demonstrated decreased cutaneous nerve innervation density in biopsies of allodynic skin from PHN patients , indicating axonal loss [45 , 46] , keeping in mind that peripheral nerve degeneration is only one of the pathological features of PHN . The restriction of VZV replication in RT97+ neurons was incomplete , in that 16 . 9% of IE63 expressing neurons express the RT97 marker , suggesting that some RT97+ neurons may be more permissive than others . Of interest , HSV-1 and HSV-2 have been found to have subtype specificity in murine ganglia with HSV-1 exhibiting restriction in large diameter neurons immunoreactive for the rodent-specific A5 antibody [46] . Cutaneous RT97+ mechanoreceptive neurons can be further subclassified by the nature of their axonal projections to the spinal cord and specialized terminations in the skin , which transmit information to the CNS about touch , pressure , vibration and tension through Meissner’s , Pacinian , Merkel and Ruffini-type receptors , respectively . At present , classification of neuronal subtypes using established makers is difficult because the staining signal from the reagents overlaps in ganglion sections [5 , 47] , and inability to distinguish functional aspects and the transcriptional state of the neuron . A more precise identification of the non-permissive neuronal subtype ( s ) may be possible with alternate methods , such as single-cell RNA sequencing of neurons [48] . Despite the entry of VZV particles into the RT97+ subtype , VZV gene expression was blocked after nuclear expression of ORF61 and IE62 and before IE63 production . Newly synthesized ORF61 and IE62 are detected before viral DNA synthesis and IE63 is expressed several hours after IE62 and ORF61 , at the same time as nascent viral DNA synthesis [26] . Notably , VZV replication was blocked in RT97+ neurons even though IE62 is the major viral transactivator [28] and IE62 and ORF61 both have potent functions in inhibiting IFN-dependent innate defenses [27 , 29 , 49] . In addition to anti-apoptotic functions , IE63 contributes to the capacity of VZV to overcome IFN-alpha mediated innate immune responses [50] . While observations in VZV-infected DRG suggest that these IE63 functions are not required to interfere with infection in RT97+ neurons , they may be important in peripherin+ neurons . Profiling the cell factors that were upregulated in VZV-infected DRG and analyzing these responses in the context of their known functions indicated that VZV infection induced marked pro-inflammatory responses , as well as proteins of the IFN pathway and neuroprotective responses . The induction of MCP-1/CCL2 , IL-1alpha and RANTES and other factors associated with prolonged and sensitized nociception , suggest a link between SGC and neuronal responses to VZV infection and inflammatory sensitization . While inflammatory cytokines were increased , DRG infection was also associated with increased TGF-beta and TGF-beta-related cytokines . Low TGF-beta secretion is associated with healthy neurons [51] and intrathecal infusion of TGF-beta attenuates nerve injury-induced neuropathic pain in rodent models [51 , 52] . Induction of IP10/CXCL10 in DRG was consistent with IP10 expression in ganglion neurons of zoster patients [53] . It should be noted that , in addition to neurons on SGC , DRG xenografts also contain Schwann cells and fibroblasts and other supportive cells which may release cell factors detected using human-specific antibodies . Recently , the capacity of the human enkephalin protein to modulate nocifensive behaviors in the rat model of VZV neuropathic pain was shown , suggesting that effects of some human neurotoxic and neuroprotective cell factors identified in the DRG model could be explored with this approach [54] . These findings in the DRG model of VZV neuropathogenesis are medically relevant for an improved understanding of herpes zoster and PHN . The pathophysiology of zoster-related neuropathic pain has been attributed to various mechanisms including central sensitization , inflammatory sensitization and biochemical changes in neurons [55 , 56] . Our experiments suggest that without an early and robust host response to herpes zoster , a VZV-induced gliopathic component mediated by the SGC response to VZV infection and a possible neuron-subtype specific component triggered by nonproductive infection of mechanoreceptive neurons , may contribute to changes associated with PHN . Pathological changes observed in the DRG model reproduce those reported in human cadaver DRG from patients with PHN , including fibrotic changes , axonal degeneration , and loss of large myelinated nerve fibers [57] . Future studies in this model are warranted to determine the molecular mechanism ( s ) underlying restricted tropism for RT97+ mechanoreceptive neurons and may open avenues to developing improved therapeutic approaches to VZV-related neuropathic pain .
NIH guidelines for housing and care of laboratory animals were followed ( Animal Welfare Assurance #A3213-01 ) , and Institutional Animal Care and Use Committee ( IACUC ) review of research involving animals was performed , and procedures were approved by the Stanford University Administrative Panel on Laboratory Animal Care ( Protocol ID#11130 ) . Use of fetal material has been reviewed by the Stanford University Administrative Panel on Human Subjects in Medical Research and the scope of use does not meet the criteria for research involving human subjects . Anonymized fetal material is provided by the non-profit tissue supply organization Advanced Bioscience Resources , Inc . ( ABR ) in accordance with applicable federal and state regulations . A single human DRG , gestational age 18–22 weeks ( ~1–2 mm3 ) with attached dorsal root was inserted under the left renal capsule of a sedated six-week old male C . B . -17 scid/scid mouse ( Taconic Farms , Germantown , NY ) . DRG were surgically exposed and inoculated by a single direct injection of 10 microliters containing VZV-infected fibroblasts or VZV-infected tonsil T-cells ( recombinant parent Oka strain ) into the DRG xenograft using a 30-gauge needle . DRG xenografts were recovered at designated timepoints from euthanized mice , fixed with 4% paraformaldehyde , and processed for histological analysis . T cells were isolated from dissociated tonsil tissues obtained via elective tonsillectomy , the T cell fraction was enriched using a nylon wool column , infected by co-culture with a VZV-infected adherent cell monolayer for 72 hours [37] , and then 10 microliters of 8x104 VZV-infected T cells ( 1067 PFU ) , injected into DRG xenografts engrafted for 8 months , and recovered at 14 and 21 days after infection . Inoculum titers were determined as previously described [10] . 3–5 infected DRG xenografts were recovered at each time point , paraffin embedded , and the tissue block was serially sectioned ( 10 micron thickness ) to generating ~150 slides/2 sections per slide . Every 20th slide was stained with hematoxylin and eosin ( H&E ) to assess cytopathology and locate zones containing clusters of nerve cell bodies . Sequential tissue sections that exhibited cytopathic effect were examined by immunostaining with antibodies to VZV or cellular proteins or VZV DNA in situ hybridization ( ISH ) . For each staining condition , slides prepared without the primary antibody and with sections from an uninfected DRG and a known positive DRG were examined in parallel . Enzyme immunohistochemistry and VZV DNA in situ hybridization was performed as previously described [10] . For confocal analysis , slides were examined using an AxioPlan 2 LSM 510 microscope ( Zeiss , New York , NY ) . Images were scanned at 1024 x 1024 pixels , 8-frame averaging minimum , and a pinhole size of 1 airy unit . Some images were cropped in Adobe Photoshop . All non-linear adjustments are described in the figure legends . Staining experiments were performed on multiple tissues sections ( 6–10 sections ) for each DRG . For assessment of VZV protein localization and quantitative analysis of neuronal subtype , at least 20 fields , each with a minimum of 50 neurons were examined . Only neurons in which the neuronal nucleus was clearly visible were included in the quantitation for ORF61 and IE62 , which are predominantly nuclear proteins . The primary VZV antibodies were anti-VZV human polyclonal antibody ( 1:500 dilution , Ig purified GK serum ) , rabbit polyclonal antibodies against IE62 ( 1:200 dilution; provided by Paul Kinchington , University of Pittsburgh ) , IE63 ( 1:400 dilution provided by William Ruyechan , University of Buffalo ) , ORF61 ( 1:50 dilution , provided by Saul Silverstein , Columbia University ) and ORF23 ( 1:400 dilution ) , generated in the Arvin laboratory and mouse anti-IE63 ( 1:800 dilution , provided by Catherine Sadzot-Delvaux , University of Liège ) . Anti-VZV gE ( 1:400 dilution ) and anti-VZV IE62 ( 1:400 dilution ) are available from Invitrogen , Temecula , CA , and anti-PML ( 1:400 ) is available from Santa Cruz Biotechnology , Santa Cruz , CA . Neuronal antibodies included anti-RT97 ( 1:200 , Abcam #178589 ) , anti-peripherin ( 1:400 , Abcam #ab4666 ) , anti-NCAM ( 1:400 , Invitrogen #07–5603 ) , anti-synaptophysin ( 1:100 , Dako #A0010 ) , anti-PML ( 1:200 , Abcam #96051 ) . Antigen retrieval using the citrate buffer/pressure cooker method was performed prior to staining . Secondary antibodies for confocal analysis were Alexa-Fluor 488 ( green staining ) and Alexa-Fluor 594 ( red staining ) ( Invitrogen , Temecula , CA ) . Multiplex immunoassay to measure cytokine levels was performed on whole tissue lysates from 2 mock infected and 4 VZV-infected DRG xenografts recovered at 14 days after infection ( rOka strain , 1000 PFU ) . DRG were homogenized in 300 microliteres cold lysis buffer ( Procarta Lysis Buffer ) , clarified by centrifugation ( 14000 RPM , 10 min . , 4°C ) , normalized for protein concentration ( Biorad DC Protein Assay ) , and frozen at -80°C until the assay was performed . Each DRG yielded ~30–35 mg of tissue . Lysates contained both intracellular and extracellular ( secreted ) cytokines . 25 microliters of lysates were added to wells in a multiplex 50-bead array in duplicate wells . Lysis buffer alone established background levels; normal serum was run as a control . Cytokine levels in pg/ml were determined using the Luminex 200 IS System array reader ( Luminex ) and analyzed using software provided by the manufacturer . Recombinant cytokines were used to establish standard curves , maximize sensitivity and establish the dynamic range of the assay . The read-out is based on sample incubation with fluorescent microspheres conjugated with monoclonal antibodies specific to target proteins . Statistical analyses were performed using GraphPad Prism version 6 . 0 . Reads below the standard curve were assigned the lowest readable value . Values in duplicate wells were averaged , outliers were expunged based on Grubb’s criteria ( p <0 . 05 ) , and T tests determined significance at p <0 . 05 .
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Varicella zoster virus ( VZV ) causes varicella; herpes zoster results from VZV reactivation and is associated with post herpetic neuralgia ( PHN ) . We hypothesized that VZV exhibits neuron-subtype specific tropism and that VZV tropism for satellite glial cells ( SGC ) results in loss of SGC functions that support neurons and contributes to VZV-related ganglionopathy . Using human DRG xenografts in SCID mice , we demonstrated that initial VZV access to neuronal cell bodies occurs by the axonal route , followed by axonal and contiguous spread between neuron-satellite cell complexes . VZV replication is restricted in mechanoreceptive neurons compared to nociceptive neurons . Despite restricted infection , mechanoreceptive neurons were selectively depleted in association with SGC loss following acute DRG infection . VZV infection of DRG triggers release of pro-inflammatory cytokines that cause neuronal damage . These observations may help to explain the neurologic sequelae often associated with herpes zoster and PHN .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[] |
2015
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Neuronal Subtype and Satellite Cell Tropism Are Determinants of Varicella-Zoster Virus Virulence in Human Dorsal Root Ganglia Xenografts In Vivo
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The bladder exstrophy-epispadias complex ( BEEC ) represents the severe end of the uro-rectal malformation spectrum , and is thought to result from aberrant embryonic morphogenesis of the cloacal membrane and the urorectal septum . The most common form of BEEC is isolated classic bladder exstrophy ( CBE ) . To identify susceptibility loci for CBE , we performed a genome-wide association study ( GWAS ) of 110 CBE patients and 1 , 177 controls of European origin . Here , an association was found with a region of approximately 220kb on chromosome 5q11 . 1 . This region harbors the ISL1 ( ISL LIM homeobox 1 ) gene . Multiple markers in this region showed evidence for association with CBE , including 84 markers with genome-wide significance . We then performed a meta-analysis using data from a previous GWAS by our group of 98 CBE patients and 526 controls of European origin . This meta-analysis also implicated the 5q11 . 1 locus in CBE risk . A total of 138 markers at this locus reached genome-wide significance in the meta-analysis , and the most significant marker ( rs9291768 ) achieved a P value of 2 . 13 × 10−12 . No other locus in the meta-analysis achieved genome-wide significance . We then performed murine expression analyses to follow up this finding . Here , Isl1 expression was detected in the genital region within the critical time frame for human CBE development . Genital regions with Isl1 expression included the peri-cloacal mesenchyme and the urorectal septum . The present study identified the first genome-wide significant locus for CBE at chromosomal region 5q11 . 1 , and provides strong evidence for the hypothesis that ISL1 is the responsible candidate gene in this region .
The bladder exstrophy-epispadias complex ( BEEC; OMIM %600057 ) is the most severe of all human congenital anomalies of the kidney and urinary tract ( CAKUT ) , and involves the abdominal wall , pelvis , all of the urinary tract , the genitalia , and occasionally the spine and anus . The severity-spectrum of the BEEC comprises the mildest form , epispadias ( E ) ; the intermediate form , classic bladder exstrophy ( CBE ) ; and the most severe form , exstrophy of the cloaca ( CE ) [1 , 2] . Despite advances in surgical techniques and improved understanding of the underlying anatomical defects , in later life many male and female patients experience chronic upper and lower urinary tract infections , sexual dysfunction , and urinary- , or in the case of cloacal exstrophies , urinary and fecal incontinence [3 , 4] . The estimated overall birth prevalence for the complete BEEC spectrum in children of European descent is 1 in 10 000 [5] . Birth prevalence , as assessed with the inclusion of terminated pregnancies , differs between subtypes . Estimated rates are: 1 in 117 , 000 in males and 1 in 484 , 000 in females for E [6]; 1 in 37 , 000 for CBE [6]; and 1 in 200 , 000 to 1 in 400 , 000 for CE [7] . According to the Birth Defects Monitoring Program of the Centers for Disease Control and Prevention , the birth prevalence of CBE among North American ethnic groups varies , with the highest birth prevalence being observed among Native Americans ( 8 in 100 , 000 ) , and the lowest among Asians ( 1 in 100 , 000 ) [8] . Although BEEC can occur as part of a complex malformation syndrome , approximately 98 . 5% of cases are classified as isolated [9] . The reported recurrence risk for CBE among siblings in families with non-consanguineous and non-affected parents ranges between 0 . 3–2 . 3% , whereas the reported recurrence risk for the offspring of affected patients is 1 . 4% [10–12] . Hence , the recurrence risk for the offspring of CBE patients shows an approximate 400-fold increase compared to that observed in the general population [10] . Identification of genetic risk factors for the BEEC has been the subject of extensive recent research , and several lines of evidence support the hypothesis that genetic factors are implicated . These include reports of BEEC-associated chromosomal aberrations [13]; reports of at least 30 families with multiple affected members [13 , 14]; and observations of high concordance rates in monozygotic twins [5] . Array-based molecular karyotyping and regional association studies have implicated micro-duplications on chromosome 22q11 . 21 and polymorphisms in the TP63 ( Tumor protein p63 ) gene [15–19] . However , in the vast majority of cases , the genetic contribution to the BEEC remains elusive , and the molecular basis of the disruption of the respective developmental processes is poorly understood . The aim of the present study was to identify susceptibility loci for CBE . Firstly , we conducted a genome-wide association study ( GWAS ) of 110 isolated CBE patients and 1 , 177 controls of European descent . Secondly , we performed a meta-analysis using the data from step 1 and data from our previous GWAS of 98 CBE patients and 526 controls [20] . Thirdly , we followed up our main finding by: ( i ) re-sequencing ISL-1 ( ISL LIM homeobox 1 ) , the main candidate gene within the region of genome wide significance on chromosome 5q11 . 1 , in all patients; and ( ii ) performing murine expression analyses .
In the subsequent text , our previous GWAS [20] is termed GWAS1 and the present GWAS is termed GWAS2 . The post quality control data set of GWAS2 comprised 110 CBE patients and 1 , 177 controls . The GWAS2 analyses identified a region of approximately 220 kb on chromosome 5q11 . 1 . This region harbors the gene ISL1 . Multiple markers in this region showed evidence for association with CBE ( S1 Table ) . The most significant marker , rs6874700 , showed a P value of 6 . 27 x 10−11 . The significance of this marker was supported by the presence of 172 surrounding markers with P values of < 10−5 . A total of 84 markers at this locus , including rs6874700 , reached genome-wide significance , i . e . P < 5 x 10−8 . No other locus in the GWAS2 analyses achieved this level of significance . Next , we combined the effect estimates of GWAS1 and GWAS2 in a fixed effect meta-analysis . This meta-analysis also implicated the 220 kb region on chromosome 5q11 . 1 . In the meta-analysis , multiple markers in this region showed evidence for association with CBE ( Fig . 1 ) . The most significant marker , rs9291768 , had a P value of 2 . 13 x 10−12 . The possible relevance of rs9291768 in CBE was supported by the presence of 137 surrounding markers with P values of < 5 x 10−8 . No other locus in the meta-analysis achieved this level of significance ( Fig . 2 ) . All markers with P values of < 10−5 are listed in S2 Table . The genotype-specific relative risks ( RRs ) for allele T of rs9291768 were: ( i ) RR_het = 2 . 00 for heterozygotes ( 95%-CI = 1 . 33–3 . 02 ) ; and ( ii ) RR_hom = 4 . 77 ( 95%-CI = 3 . 06–7 . 45 ) for homozygotes . This is compatible with neither a recessive ( P = 3 . 9 x 10−5 ) , nor a dominant mode of inheritance ( P = 1 . 6 x 10−4 ) . According to the genotype data from Ensembl release 74—December 2013© , the frequency of the CBE allele T at rs9291768 is highest in African populations ( 0 . 534 ) , intermediate in European populations ( 0 . 425 ) , and lowest in Asian populations ( 0 . 083 ) . Our previous study [20] failed to identify the possible relevance of both marker rs9291768 and the region comprising ISL1 . In that report , rs9291768 obtained a P value of 1 . 1 x 10−3 , which is not considered worthy of note in the context of a GWAS . In the present meta-analysis , the estimated relative risk for this SNP was 2 . 18 ( see Table 1 ) . The GWAS1 sample comprised 98 cases and 526 controls , and the power to achieve genome-wide significance ( i . e . < 5 x 10−8 ) for a SNP with RR = 2 . 18 was only 31% under the assumption of a multiplicative model and a minor allele frequency of 0 . 377 . For GWAS2 , which comprised 110 cases and 1177 controls , the power was higher at 53% . However , the combination of GWAS1 and GWAS2 provides a power of 98% . This substantial increase in power is the central motivation for conducting meta-analyses . We therefore assume that the non-identification of rs9291768 in GWAS1 was attributable to the issues of power and random sample variation . The marker rs9291768 is a non-coding variant , which is located 27 . 2 kb downstream of the ISL1 gene . The associated 220 kb haplotype block contains the gene ISL1 . The only other transcript encoded in the regions flanking rs9291768 ( 500 kb on either side ) is LOC642366 , which also resides within the associated haplotype block . LOC642366 encodes an uncharacterized non-coding RNA , which has no ortholog in mouse , zebrafish , drosophila , C . elegans , or S . cerevisiae . The second most proximal gene to rs9291768 is Homo sapiens poly ( ADP-ribose ) polymerase family , member 8 ( PARP8 ) , which is located 575 kb proximal to rs9291768 . The third and fourth genes are Homo sapiens pelota homolog ( Drosophila ) ( PELO ) , and the integrin , alpha 1 subunit of integrin receptors ( ITGA1 ) , which are both located ∼1 . 4 Mb distal to rs9291768 . According to Mouse Genome Informatics ( http://www . informatics . jax . org/ ) , neither PARP8 nor ITGA1 is expressed in the genital tubercle or the cloacal membrane during the CBE critical time frame in mouse embryos . Furthermore , mice with complete invalidation of PARP8 or ITGA1 display neither CBE features nor CBE-related phenotypes . Studies of the Drosophila pelota gene have implicated dPelo in spermatogenesis , mitotic division , and patterning . Homozygous Pelo-null embryos fail to develop beyond embryonic day 7 . 5 , and exhibit no early CBE-related features , such as diastases of the symphysis . Whether rs9291768 per se , or a variant in linkage disequilibrium with it , confers the functional effect underlying the association remains unclear . The rs9291768 marker shows no association with any predicted regulatory sequence ( according to ENCODE , TFSEARCH , or FAS-ESS ) , or splicing motif . Of the other 136 markers at this chromosome 5 locus , only one ( rs2303751 ) is located in a coding region , and none affect a splice site . Marker rs2303751 is in linkage disequilibrium ( r2 = 0 . 932 ) with the most significant marker rs9291768 , and represents a synonymous A/G substitution in exon four of ISL1 . Furthermore , none of the public eQTL ( expression quantitative trait loci ) databases contains evidence to suggest that rs9291768 , or a SNP in perfect linkage disequilibrium with it , would affect gene expression levels ( RegulomeDB , http://regulome . stanford . edu; eQTL browser , eqtl . uchicago . edu ) . The present meta-analysis generated no evidence in support of the ( non-genome-wide significant ) association between CBE and an intergenic region on chromosome 17q21 . 31-q21 . 32 identified in GWAS1 [20] . This region is located between the genes WNT3 ( wingless-type MMTV integration site family , member 3 ) and WNT9b ( wingless-type MMTV integration site family , member 9b ) . Since the CBE-associated region harbors the gene ISL1 , we performed ISL1 re-sequencing in 207 CBE patients included in the present meta-analysis . As well as allowing mutation detection , this approach should provide genotype data for polymorphisms in the exons and exon-flanking regions of ISL1 . Using the results of Sanger sequencing , we compared genotype information from four SNPs with the imputed data . We calculated the allelic accuracy , i . e . the aggregate difference between the actual number of alleles observed and the number of imputed alleles [21] . This yielded accuracy values of 96 . 9% ( rs150104955 ) ; 97 . 3% ( rs2288468 ) ; 97 . 3% ( rs2303751 ) ; and 99 . 5% ( rs3917084 ) . Two of these SNPs ( rs2288468 , rs2303751 ) achieved genome-wide significance in the meta-analysis Although sequencing identified no nonsense or probably pathogenic ISL1 variant , the following variants were all detected in a heterozygote state in single patients: intron 3 , rs2303750; synonymous in exon 5 , rs41268419 ( p . Ser275 = ) ; non-synonymous in exon 4 , rs200209474 ( p . Thr181Ser ) ; unreported variants in intron 4 , +21delG , -19delT , and -64A>G . Pathogenicity prediction using several publicly available algorithms ( SNPs&Go , MutPred , SIFT ) predicted that the p . Thr181Ser variant is neutral . Only PolyPhen-2 estimated it as possibly damaging . Furthermore , all of the observed intronic variants can be assumed to be benign . Hence , our patient sample size may have been too small to detect rare causal mutational events . We cannot exclude the possibility that some mutations were overlooked , i . e . mutations located in the promoter region , in as-yet-unknown regulatory sequences , or in non-coding regions that were not present within the covered sequence . ISL1 encodes the insulin gene enhancer protein ISL1 , a LIM zinc-binding/homeobox-domain transcription factor which was initially identified as a regulator of insulin expression [22] . Research in rodents suggests that Isl1 plays a fundamental role in the embryogenesis of multiple tissue types: Isl1 affects cell differentiation and survival , cell fate determination , the generation of cell diversity , and segmental patterning during mouse development [23] . Isl1 binds and regulates the promoters of the glucagon and somatostatin genes , and activates insulin gene transcription in pancreatic beta cells in synergy with NEUROD1 ( neuronal differentiation 1 ) [24] . A previous study found an association between a heterozygous ISL1 premature termination mutation ( p . Gln310* ) and diabetes type II in a large Japanese kindred [25] . Furthermore , in a classic linkage analysis of 186 Swedish multiplex families with diabetes type I , linkage was observed with chromosomal region 5q11-q13 , which harbors ISL1 [26] . This finding supports the hypothesis that ISL1 is implicated in pancreatic function and development , as reported in Isl1 knockout mice [27] . In the mouse , research at E ( embryonic day ) 8 . 5 to E9 . 5 has shown that ISL1 acts upstream of the sonic hedgehog ( Shh ) signaling pathway [28] , which may be involved in other processes besides the coordination of heart and lung co-development [29] . Interestingly , a recent report by Matsumaru et al . [30] showed that SHH is also important for ventral body wall formation , and that ectopic SHH signaling induces omphalocele , a feature which is associated with CE , the severest form of the BEEC . A previous study in mice also showed that a homozygous Isl1 null mutation ( Isl1-/- ) induced growth retardation at E9 . 5 and severe cardiac malformations at E10 . 5 [31] . Embryos exhibiting these severe cardiac malformations at E10 . 5 died at E11 . 5 due to the developmental arrest of spinal motor neurons [32] . Research has demonstrated a further role for Isl1 in mice at E11 . 5 , i . e . in hindlimb-specific patterning and growth in combination with both SHH and the helix-loop-helix transcription factor HAND2 ( heart and neural crest derivatives expressed 2 ) [33] . This interplay is also necessary for normal cardiac development in mice [23] . Recently , Jurberg et al . reported that specific activity of mouse Isl1 in the progenitors of the ventral lateral mesoderm promotes formation of the cloaca-associated mesoderm as the most posterior derivatives of lateral mesoderm progenitors [34] . This observation provides independent evidence that ISL1 is a promising candidate gene for human CBE . In a recent mouse study , Kaku et al . induced conditional Isl1 deletion in the lateral mesoderm using a Hoxb6-Cre driver , and demonstrated that this caused kidney agenesis or hydroureter [35] . The authors observed transient Isl1 expression between E10 . 5—E14 . 5 . At early stages , this was observed in the mesenchyme surrounding the ureteric stalk and cloaca . At later stages , expression occurred along the nephric duct , at the base of the ureteric stalk , and in the genital tubercle . This suggests that Isl1 may be implicated in kidney , ureter , and bladder development . These mice show a variable phenotype , which can include agenesis of the genital tubercle ( R . Nishinakamura , personal communication ) . The variability of this defect is probably due to mosaicism , which arises as a result of the Hoxb6-Cre driver [33] . Kaku et al . also reported that conditional loss of Isl1 resulted in a concomitant reduction in the expression of bone morphogenetic protein 4 ( Bmp4 ) [35] . Using mouse Isl1Cre;Bmp4flox/flox mutants , Suzuki et al . showed that BMP4 signaling in the caudal Isl1 expression domain was required for formation of the anterior peri-cloacal mesenchyme ( aPCM ) at E10 . 5 [36] . Rather than decreasing Isl1 function , loss of this signal caused defective pelvic and urogenital organ formation , including kidney and bladder agenesis , with abnormal development of the lower limbs and pelvis . Moreover , tissue lineage analyses suggested that Isl1-expressing cells are an essential cell population in terms of caudal body formation , including the pelvic/urogenital organs and hindlimb [36] . In the present mouse analyses , Isl1 was expressed during the critical timeframe for development of tissues involved in CBE , and strong Isl1 expression was detected in the developing genital region ( Fig . 3 ) . From E9 . 5 , a broad Isl1 domain was detected in the cloacal region . This was maintained in the outgrowing genital tubercle ( including the urorectal septum ) until at least E14 . 5 . Three groups have recently elucidated the molecular basis of the Danforth’s short tail ( Sd ) mouse . They reported the insertion of a retrotransposon in the 5’ regulatory domain of the murine Ptf1a gene , which encodes pancreas specific transcription factor 1A [37–39] . As a consequence , and in contrast to their wildtype littermates , Sd mice showed ectopic Ptf1a expression in the notochord and hindgut at E8 . 5 to E9 . 5 , which extended to the cloaca and mesonephros at E10 . 5 and to the pancreatic bud at E10 . 5 and E11 . 5 [38] . The resultant phenotype of this Sd mutation mirrors the phenotype observed in human caudal malformation syndromes , a phenotype that is also observed in Isl1 transgenic mice [40] . Moreover , the BEEC related human Currarino syndrome ( MIM: #176450 ) , which comprises hemisacrum , anorectal malformations , and a presacral mass , is caused by mutations of the transcription factor MNX1/HLXB9 ( Motor neuron and pancreas homeobox protein 1 ) . The genes Ptf1a , Isl1 , and Mnx1 have been implicated in pancreas development , and MNX1 has been identified as a direct target of PTF1a [41] . Coordinated development of caudal body structures is necessary for the formation of the bladder , rectum , and the external genitalia [42 , 43] . These organs are derived from the transient embryonic cloaca and the PCM , an infra-umbilical mesenchyme [44] , as well as the anterior PCM [36 , 42] . SHH- , ISL1- , and BMP4-expressing cells contribute to both the PCM and the anterior PCM [36 , 42 , 45] . Perturbation of this morphoregulatory network may thus lead to malformation of caudal structures , including the bladder , rectum , and external genitalia . In summary , the present report describes a novel association between ISL1 and human CBE . While previous conventional linkage- and candidate gene studies in humans have suggested the involvement of ISL1 in diabetes type I and II and in congenital heart defects , to our knowledge , the present study is the first to implicate ISL1 in the formation of human urogenital malformations . The observed variation in CBE birth prevalence across populations is consistent with the cross-population frequencies of the rs9291768 T-allele , thus supporting our finding . The importance of Pft1a and Isl1 in the formation of murine genital development and caudal regression phenotypes , the involvement of MNX1 in the BEEC related human Currarino syndrome , and the role of all three genes in pancreatic development suggest that these genes are involved in a common pathway . However , the present data do not exclude the possibility that the association between CBE and the region surrounding ISL1 is attributable to long-range functional interactions with other regions in the human genome . Future studies are warranted to identify the mechanisms through which genetic variation at ISL1 contributes to CBE development .
The initial GWAS2 sample comprised 123 isolated CBE patients and 1 , 320 controls of European descent . Prior to inclusion , written informed consent was obtained from all subjects , or from their proxies in the case of legal minors . For patients and controls , demographic information was collected using a structured questionnaire . This study was approved by the institutional ethics committee of each participating center , and was conducted in accordance with the principles of the Declaration of Helsinki . All CBE patients were recruited in person by experienced physicians trained in the diagnosis of the BEEC . Details of the recruitment process for patients and controls are provided in Reutter et al . [20] . For the 123 isolated CBE patients in GWAS2 , genotyping was performed using the Illumina BeadChip HumanOmniExpress ( San Diego , California , USA ) , and DNA was extracted from blood or saliva using standard procedures . Case-control comparisons were made using the genotypes of 1 , 320 population-based controls , which had been processed using the same array [46] . Genome-wide genotyping of 730 , 525 markers was conducted using the Infinium HD Ultra Assay from Illumina ( Illumina , San Diego , California , USA ) . Markers were excluded from the analysis if: ( i ) the minor allele frequency was <1% or the call rate was <95% in either cases or controls; or ( ii ) the test for Hardy-Weinberg equilibrium resulted in P<10−4 in the control sample or P<10−6 in the case sample . A total of 616 , 799 autosomal markers fulfilled these quality criteria . Individuals were excluded if their call rate was <99% , or if they were outliers in a multidimensional scaling ( MDS ) analysis . Relatedness of individuals within GWAS2 , and between GWAS1 and GWAS2 , was evaluated using both the KING program [47] , and an identity-by-state-based in-house program . The post quality control data set of GWAS2 comprised 110 CBE patients and 1 , 177 controls . GWAS1 and GWAS2 were imputed separately to the 1000 Genomes Project and HapMap 3 reference panels using IMPUTE2 [48] . For each of the three data sets , variants were excluded if: ( i ) the imputation info score was <0 . 4; ( ii ) the dosage of the minor allele was <1% in either cases or controls; ( iii ) the test for Hardy-Weinberg equilibrium ( calculated on the basis of the 80% best-guess genotypes ) resulted in P<10−4 in the control sample; or ( iv ) the 80% best-guess genotypes were only available for <80% of cases or controls . In total , 7 , 261 , 187 SNPs were analyzed in at least one data set . Single-marker analysis was performed using logistic regression . The allele dosage and the first five components obtained from MDS were used as independent variables for the variants in the three data sets . The effect estimates for the data sets were then combined in an inverse variance-weighted fixed-effects meta-analysis . The genomic inflation factor in this meta-analysis was 1 . 0196 . Power was calculated to enable detection of genome-wide significance ( P <5 x 10−8 ) in the combined analysis of the GWAS1 and GWAS2 samples . Under the assumption of a multiplicative model , this was 80% for an allele frequency of 0 . 35 ( 0 . 20 ) and a RR of 1 . 94 ( 2 . 05 ) . This is within the range of RRs observed for other multifactorial , nonsyndromic human malformations . For example , the power of the present study to detect a locus with an effect-strength similar to that of the most strongly associated locus in nonsyndromic cleft lip with or without cleft palate was 99 . 2% [49] . Sequence analysis of the complete ISL-1 coding regions and their splice consensus motifs was performed in 207 of our 208 CBE patients using standard techniques . Primers are listed in S3 Table . For the remaining patient , no additional DNA sample was available . During this analysis , we also obtained information for several SNPs deposited in dbSNP Build142 ( rs3917084 , rs150104955 , rs2288468 , rs2303750 , rs2303751 , rs200209474 , and rs41268419 ) . The expression of Isl1 was analyzed using in situ hybridization , standard procedures , and a ∼450bp antisense probe spanning exons 2 and 3 from XM_006517533 . 1 . Details of the in situ hybridization methods are provided elsewhere [50] .
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The etiology of classic exstrophy of the bladder ( CBE ) remains unclear . The present genome-wide association study and meta-analysis identified an association between CBE and a region on chromosome 5q11 . 1 . This region contains the gene encoding insulin gene enhancer protein , ISL-1 . In this region , 138 single nucleotide polymorphisms ( SNPs ) reached genome-wide significance , with the SNP rs9291768 showing the lowest P value ( p = 2 . 13 x 10−12 ) . Our findings , as supported by expression analyses in murine models , suggest that ISL1 is a susceptibility gene for CBE .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Methods"
] |
[] |
2015
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Genome-wide Association Study and Meta-Analysis Identify ISL1 as Genome-wide Significant Susceptibility Gene for Bladder Exstrophy
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Functional diversification of motor neurons has occurred in order to selectively control the movements of different body parts including head , trunk and limbs . Here we report that transcription of Isl1 , a major gene necessary for motor neuron identity , is controlled by two enhancers , CREST1 ( E1 ) and CREST2 ( E2 ) that allow selective gene expression of Isl1 in motor neurons . Introduction of GFP reporters into the chick neural tube revealed that E1 is active in hindbrain motor neurons and spinal cord motor neurons , whereas E2 is active in the lateral motor column ( LMC ) of the spinal cord , which controls the limb muscles . Genome-wide ChIP-Seq analysis combined with reporter assays showed that Phox2 and the Isl1-Lhx3 complex bind to E1 and drive hindbrain and spinal cord-specific expression of Isl1 , respectively . Interestingly , Lhx3 alone was sufficient to activate E1 , and this may contribute to the initiation of Isl1 expression when progenitors have just developed into motor neurons . E2 was induced by onecut 1 ( OC-1 ) factor that permits Isl1 expression in LMCm neurons . Interestingly , the core region of E1 has been conserved in evolution , even in the lamprey , a jawless vertebrate with primitive motor neurons . All E1 sequences from lamprey to mouse responded equally well to Phox2a and the Isl1-Lhx3 complex . Conversely , E2 , the enhancer for limb-innervating motor neurons , was only found in tetrapod animals . This suggests that evolutionarily-conserved enhancers permit the diversification of motor neurons .
Motor neurons are composed of multiple units called motor columns and motor pools specialized to innervate particular peripheral muscles [1] . Motor neurons in the hindbrain innervate and control the movement of head and neck , while somatic motor ( sm ) neurons in the spinal cord control body muscles . Limbs and body walls are innervated by separate motor columns occupying different mediolateral positions in the ventral spinal cord; thus lateral motor column ( LMC ) neurons control limbs , preganglionic column ( PGC ) neurons control sympathetic ganglia , medial motor column ( MMC ) and hypaxial motor column ( HMC , formerly known as MMCl ) neurons control the body walls . The diversification of motor neurons is achieved by combinations of transcription factors restricted to particular motor columns: Phox2 factors specify cranial motor neurons and the LIM-homeodomain ( HD ) factors Isl1 and Lxh3 specify sm neurons [2–5] . Naturally , the interplay between cis-regulatory elements ( i . e . , promoters and enhancers ) and trans-regulatory elements ( i . e . , transcription factors ) is critical for selective gene expression in individual motor neuron subsets . Furthermore , although studies in Hox clusters revealed that signals of body patterning initiate motor neuron diversification , motor neuron-specific transcription control of downstream players in action is not still fully understood [6–8] . Isl1 is a member of the LIM-homeodomain ( HD ) transcription factor family present in somatic and visceral motor ( vm ) neurons once they are postmitotic [9] . Genetic and biochemical studies have demonstrated that Isl1 is critical for assigning sm neuron identity , and forms a hexamer complex with Lhx3 [5 , 9] . Once their pan-motor neuronal identity is acquired via the Isl1-Lhx3 complex , motor neurons further diverge to create multiple motor columns . Motor neurons that retain the Isl1-Lhx3 complex become MMC neurons , while the expression of Foxp1 defines LMC and PGC neurons [10 , 11] . Isl1 continues to be expressed in most somatic and vm neurons , raising the possibility that dynamic transcriptional control of Isl1 is achieved by differences in the cellular environment of the individual motor neuron subsets . Searches for Isl1 enhancers by comparative functional genomics have revealed multiple cis-regulatory elements ( CREs ) specific for motor neurons , such as CREST1 and CREST2 identified in zebrafish [12 , 13] . However , the trans-regulating elements ( TREs ) that interact with them and the strategy used to achieve accurate spatiotemporal control of subtype-specific enhancer complexes remain unclear . Interestingly , Isl1 is found in the motor neurons of many animal species , including primitive aquatic animals such as lampreys and ascidians [14 , 15] . This led us to reason that evolutionary diversification of motor neurons may have occurred along with the transcriptional control of Isl1 activity in newly-defined motor neuronal subsets . Indeed , chordate ascidians contain primitive vm neurons that share molecular characteristics of cranial motor neurons in the vertebrate CNS [14] . Aquatic agnatha ( jawless fish ) vertebrates such as the lamprey only have sm neurons that contact the body wall , and display traits of MMC and HMC neurons [16 , 17] . The LMC and PGC neurons arose only later when paired appendages such as limbs ( or lateral fins ) and a sympathetic nervous system evolved in fish and amphibians [16 , 18 , 19] . Thus , motor neurons have constantly developed to expand the repertoire of motor neuron subsets and control novel body parts while the transcriptional control of Isl1 diversified in parallel . In the present study , we asked whether transcription programs that diversify motor neurons are conserved or change during evolution and , if so , whether motor neurons build new programs when new paired appendages appear . We found that Isl1 expression in motor neurons was mainly controlled by two enhancers , CREST1 and CREST2 ( herein called E1 and E2 ) , with the help of the dedicated transcription factors Phox2 , Isl1 and Lhx3 , and onecut ( OC ) factor [12] . Chromatin Immunoprecipitation Sequencing ( ChIP-Seq ) analysis and reporter assays demonstrated that Phox2 , Isl1 and Lxh3 induce E1 activity in motor neurons in the hindbrain and the spinal cord , whereas OC-1 selectively induce E2 activity in limb-innervating motor neurons . Comparative genomic approaches showed that the core region of E1 was conserved from jawless fish to humans , whereas E2 was only found in animals with paired appendages . Together our findings demonstrate that motor neuron-specific expression of Isl1 has been conserved in evolution with the help of two major enhancers , and that new strategies were adopted to accommodate newly added paired appendages .
To understand the mechanism by which Isl1 becomes selectively expressed in certain neuronal subtypes , we chose to characterize two major Isl1 enhancers originally identified in the zebrafish [12] . To examine their functions in more detail , we generated GFP reporters under the control of the enhancers , and electroporated them into the chick neural tube , aiming at either the hindbrain or spinal cord . There are three different types of motor neurons in the developing hindbrain: branchiomotor ( bm ) , visceral motor ( vm ) and sm neurons [20] . When the E1::GFP reporter was introduced into the hindbrain , whole mount immunostaining showed that GFP was expressed in the peripheral projections of all types of cranial motor neurons ( Fig 1A ) . Transverse sectioning confirmed that the GFP signal co-distributed with Isl1 immunoreactivity in hindbrain motor neurons ( Fig 1B–1D ) . The mini CMV promoter or minimal Isl1 promoter produced very low level activity by themselves , confirming the specificity of the E1 enhancer ( S1A , S1B , S1D and S1E Fig ) . An E1 reporter with reverse orientation also showed motor neuron-specific activity , consistent with the orientation-independent character of enhancers ( S1C Fig ) . Conversely , the activity of the E2 GFP reporter was not detectable in motor neurons , but only weakly found in sensory ganglia of the hindbrain ( Fig 1E–1H ) . In the spinal cord , the distribution of GFP-labeled axons in wholemount immunostained embryos and transverse sections showed that the E1 enhancer was active in all motor columns but not in sensory neurons ( Fig 1I–1M ) . E2 enhancer activity was found in sensory neurons , and LMC and HMC neurons but not in MMC neurons ( Fig 1N–1R ) . 3D reconstruction of z-slice images clearly demonstrated that the E1 but not the E2 reporter was active in MMC neurons ( S1 and S2 Movies ) . Together these results show that E1 is active in motor neurons in both the hindbrain and spinal cord , while E2 activity is restricted to subsets of motor neurons in the spinal cord . To pinpoint the motor somata that were labeled by the E1 and E2 reporters , we constructed reporters for nuclear GFP ( nGFP ) , which becomes localized to cell bodies . Expression of Isl1 , Foxp1 , Lhx3 and GFP was assessed by quadruple-immunostaining of individual sections to locate individual motor columns . At brachial levels , MMC neurons express Isl1 and Lhx3 , while HMC neurons only express Isl1 . LMC neurons are divided into medial LMC ( LMCm ) and lateral LMC ( LMCl ) , which are Foxp1+Isl1+ and Foxp1+Isl1- , respectively [10 , 11] . At these levels , E1 was active in all motor neurons ( 42 . 0% in MMC neurons; 43 . 6% in HMC; 13 . 4% in LMCm; 9 . 0% in LMCl ) ( Fig 2A , 2B and 2Q ) . This pan-motor neuronal activity of E1 , with expression even in the LMCl neurons , which do not express Isl1 , led us to reason that stable expression of GFP may persist after the enhancer is no longer active . To monitor enhancer activity in situ , we constructed a reporter with destabilized nGFP ( ndGFP ) , whose half-life is less than 4 hours [21] . The majority of cells labeled by destabilized GFP under the control of the E1 enhancer were Lhx3+ MMC neurons ( 12 . 8% ) rather than LMC neurons ( 0 . 2% ) or HMC neurons ( 1 . 0% ) ( Fig 2E , 2F and 2R ) . ndGFP expression labeled a streak of cells next to the pMN domain; these were newborn migrating motor neurons ( Fig 2E ) . In contrast , E2::nGFP expression was mostly found in LMC ( 12 . 1% in LMCm; 3 . 9% in LMCl ) rather than MMC ( 0 . 3% ) neurons , and expression of destabilized GFP was mostly found in LMCm neurons ( 10 . 4% ) and in MMC neurons ( 1 . 9% ) but not in LMCl neurons , in good agreement with endogenous Isl1 expression in LMCm neurons [22] ( Fig 2I , 2J , 2M , 2N , 2S and 2T ) . Next we examined the enhancer activities at thoracic levels where Isl1+Lhx3+ MMC , Isl1+Lhx3- HMC and Isl1+Foxp1+PGC neurons are present [10] . The E1::nGFP reporter was detected in all motor columns ( 38 . 6% in MMC; 30 . 7% in PGC; 29 . 5% in HMC ) , whereas the destabilized E1::ndGFP reporter was restricted to MMCs and PGCs and was barely seen in HMCs ( Fig 2C , 2D , 2G , 2H , 2Q and 2R ) . E2::nGFP reporter activity was found in MMCs ( 8 . 0% ) , PGCs ( 11 . 9% ) and HMCs ( 1 . 3% ) , while the E2::ndGFP reporter was located in PGCs ( 1 . 0% ) and HMCs ( 1 . 6% ) ( Fig 2K , 2L , 2O , 2P , 2S and 2T ) . In summary , E1 activity persists in MMC and PGC neurons and E2 is mostly active in LMCm neurons . We next sought to identify transcription factors in motor neurons that bind to the Isl1 enhancer . When we looked for potential transcription factor binding sites using rVISTA ( http://rvista . dcode . org/ ) , we found multiple transcription factor binding motifs within the E1 enhancer , mostly motifs for homeodomain transcription factors . We then carried out luciferase assays using an E1::luciferase construct cotransduced with diverse homeodomain transcription factors and others that are present in motor neurons as follows: Phox2 , Isl1 , Lhx3 , Barx2 , Tbx20 , Isl2 , Nkx6 . 1 , Hb9 , Meis1 , Pbx1 , Otp , Shox2 , Hmx3 , Pax6 , Sip and OC-1 [23–29] . Of the various homeodomain transcription factors , only Phox2a/b and Lhx3 induced expression of the E1 reporter gene ( S2 Fig ) . Phox2a and Phox2b are two paralogous homeodomain transcription factors present in branchio-and visceromotor ( bm/vm ) neurons in the hindbrain [2–4] . Misexpression of Phox2 factors induces ectopic expression of Isl1 when electroporated into the spinal cord , indicating that Phox2 factors may activate Isl1 enhancers [2 , 30] . We first explored ChIP-Seq data for Phox2 genomic binding sites in iNIP cells , an inducible embryonic stem cell line with bm/vm neuronal properties [31] ( Fig 3A and S3 Fig ) . Remarkably , the highest Phox2 ChIP-Seq peak between 620 kb downstream and 540 kb upstream of the Isl1 locus was in E1 , around 220 kb downstream of the Isl1 transcription start site . To further define Phox2 binding sites within E1 , a series of deletions and point mutations was introduced into E1 ( Fig 3B and S5A Fig ) . In luciferase assays , Phox2a induced E1 activity by 4 . 13-fold but did not induce E2 , suggesting its specificity to E1 ( S2B Fig ) . A fragment containing nt 320–479 of E1 proved to be sufficient for activation by Phox2a , whereas the mutE1-3 and mutE1-4 sites abolished activation ( Fig 3B and S5A Fig ) . We and others previously showed that overexpression of Phox2 factors induced ectopic expression of Isl1 within the chick spinal cord , and that the ectopic Isl1+ cells had bm/vm characteristics determined by their expression of the bm/vm marker Tbx20 ( S4F–S4H and S4K–S4M Fig ) [2 , 30] . The Isl1+ cells induced by Phox2a , however , did not express markers for other neuronal classes such as Brn3a ( for dI3 neurons ) and MNR2 ( for sm neurons ) ( S4I , S4J , S4N and S4O Fig ) . Thus , we decided to use Isl1+ as a phenotypic readout for the ability to induce hindbrain motor neuron identity . When deletions and point mutations were introduced in E1 , GFP expression in the spinal cord was not changed except in the cases of nt320-470 E1 and mutE1-3 ( S4P–S4V and S4Y Fig ) . Nt320-470E1 was not active in spinal cord motor neurons because the Isl1-Lhx3 binding motif was partially deleted ( S4Q and S5A Figs ) . Nevertheless it remained active in the hindbrain , implying that the fragment is involved specifically in bm/vm neuron expression ( S4X Fig ) . When Phox2a was electroporated , dorsal expansion of GFP reporter activity was found in nt 320–479 E1 , mutE1-1 and mutE1-2 , but not in mutE1-3 and mutE1-4 ( Fig 3G–3K and S5A Fig ) . MutE1-3 GFP expression was entirely lost in the neural tube , indicating that the mutE1-3 site is also essential in spinal cord sm neurons ( S5A Fig ) . On the other hand , mutE1-4 only lost its activity in the dorsal spinal cord , in which bm marker Tbx20 but not Brn3a or MNR2 was induced , but its GFP expression was intact in sm neurons ( Fig 3K and S4K–S4O Fig ) . This implies that Phox2 binding to the mutE1-4 motif turns on Isl1 selectively in hindbrain motor neurons ( mostly branchiomotor/visceral ) but not in spinal cord motor neurons ( mostly somatic ) . Axonal projection in wholemount and transverse sections of chick embryos also confirmed the restricted activity of mutE1-4 in hindbrain sm neurons ( S6A–S6H’ Fig ) . We also demonstrated specific binding of Phox2 at the E1-4 site by gel shift assays and chromatin IP ( Fig 3M and 3N ) . We next tested whether Phox2 factor is necessary for inducing E1 activity in vivo . When we knocked down chick Phox2b by siRNA , E1 activity was diminished in bm neurons ( Fig 3O–3Q and S7A Fig ) . Together , our results suggest that Phox2 factor is necessary and sufficient to induce E1 in hindbrain bm neurons . Next we generated stable transgenic embryos carrying E1 and mutE1-4 GFP reporters . GFP-labeled peripheral projections were found in the hindbrain and spinal cord of wholemount E1::GFP embryos ( Fig 4A–4B’ ) . In transverse sections of these embryos GFP expression was found in Isl1+Phox2b+ facial motor neurons of rhombomere ( r ) 4 , indicating that E1::GFP is active in bm/vm neurons ( Fig 4C , 4C’ , 4E and 4E’ ) . Sm neurons in the caudal hindbrain also expressed E1::GFP ( S6E , S6G and S6G’ Fig ) . Wholemount GFP staining of mutE1-4::GFP showed that GFP was expressed in the peripheral projections of the spinal cord but not in the hindbrain ( Fig 4B and 4B’ ) . Transverse sections of the hindbrains of mutE1-4::GFP embryos also showed that GFP expression was absent from facial motor neurons and other bm/vm neurons ( Fig 4D , 4D’ , 4F , 4F’ , S6D and S6F Fig ) . However , the sm neurons in the caudal hindbrain expressed mutE1-4::GFP ( S6F , S6H and S6H’ Fig ) . In the spinal cord , GFP expression by both E1 and mutE1-4 reporters was found in sm neurons at brachial and thoracic levels ( Fig 4G–4J’ ) . Thus , Phox2-E1 interaction is required for specific expression of Isl1 in bm/vm neurons . Since the E1 enhancer is active in spinal motor neurons and Phox2 is not present in the spinal cord , transcription factors other than Phox2 presumably control its activity in the spinal cord . Our luciferase assays with diverse transcription factors showed that Lhx3 also activated the E1 enhancer ( See S2 Fig ) . Lhx3 is present in p2 and pMN domains and participates in producing V2a interneurons and motor neurons , respectively ( Fig 5A–5C ) [5] . Isl1 appears when pMN progenitors just become postmitotic , which assigns pan-motor neuron identity by forming a hexamer complex with Lhx3 ( Fig 5B and 5C ) [5 , 32] . When motor neurons further diverge into multiple motor columns , only MMC neurons co-express Isl1 and Lhx3 [1 , 33] . In line with this , we detected E1::ndGFP reporter activity in cells that co-expressed Isl1 and Lhx3 ( see Fig 2E , 2F and 2R ) . To test whether enhancer activity in the spinal cord was altered in the presence of Isl1 and Lhx3 , we electroporated cells with the E1::GFP reporter together with Isl1 and Lhx3 . When Isl1 alone was electroporated , E1 enhancer activity remained restricted to motor columns , as in the GFP controls ( Fig 5D ) . In contrast , when Lhx3 was electroporated , E1 enhancer activity was expanded into the dorsal column where ectopic Chx10+ V2a interneurons arose , although to a lesser degree than the group electroporated with Isl1 and Lhx3 ( Fig 5E and 5V ) . Co-electroporation of Isl1 and Lhx3 , or introduction of DDI1L3 , which mimics the Isl1-Lhx3 complex , also resulted in expansion of E1 activity in the dorsal spinal cord , in which ectopic MNR2+ motor neurons were induced ( Fig 5F–5H’ and 5V ) [5] . We also tested whether misexpression of LIM factors induced transcription of the endogenous Isl1 gene in the dorsal spinal cord where the GFP reporter was induced . Since our Isl1 antibody does not distinguish between chick and mouse Isl1 ( they are 99% similar ) , we used Isl2 instead of Isl1 , a paralogue of Isl1 with similar biological activity [34 , 35] . No E1 reporter activity was found in the presence of Isl2 alone ( Fig 5I and 5V ) . In contrast , when Isl2 and Lhx3 were introduced , ectopic Isl1 appeared in the dorsal spinal cord , consistent with the expansion of GFP expression driven by E1 ( Fig 5J–5L and 5V ) . To determine whether the effect of Lhx3 required the LIM domain , we functionally blocked that domain by co-electroporating ΔL-Lhx3 , LMO4 or the dimerized domain ( DD ) [5] . The induction of the E1 enhancer was blocked in all three conditions , indicating that LIM domain-based complex formation is required for Lhx3 to activate the E1 enhancer ( S8 Fig ) . Luciferase reporter assays also showed that E1 was induced by Lhx3 , Isl1+Lhx3 and DDI1L3 but not by Isl1 ( Fig 5W ) . Although Lhx3 is present in pMN progenitors and activates E1 , we did not observe E1 activity in the pMN region ( Fig 5A ) . Only a streak of migrating motor neuron progenitors that had just left the pMN domain expressed the E1::GFP reporter , and this coincided with the appearance of a low level of Isl1 protein ( Fig 5B–5B”‘ ) . Thus , some unknown repressor may suppress the initial expression of Isl1 in pMN progenitors and this repression may be released around the time when the progenitors become postmitotic motor neurons [9] . To test this hypothesis , we tested the effect of Olig2 on Lhx3 expression since Olig2 is present in the pMN domain , is required for motor neuron specification and is extinguished in postmitotic motor neurons [36 , 37] . In HH stage 23 embryos , differentiating progenitors at lateral region of the pMN domain co-expressed Olig2 and Lhx3 but lacked E1::GFP activity ( Fig 5A–5A”‘ ) . As expected , co-electroporation of Olig2 with Lhx3 suppressed the activity of the latter as an inducer of E1 ( Fig 5N , 5O and 5V ) . The induction of E1 luciferase reporter activity by Lhx3 was also inhibited by Olig2 ( Fig 5W ) . Conversely , Olig2 was not effective in reducing E1::GFP expression in endogenous motor neurons or E1 GFP activity driven by Isl1 and Lhx3 ( S5C Fig ) . Thus , Olig2 selectively blocks activity of Lhx3 complex . This was abolished when putative E-box sequence in E1 was mutated , indicating that Olig2 may bind to this site ( S5A and S5K–S5M Fig ) . Since Lhx3 is also present in the p2 domain where V2 interneurons arise , the E1 enhancer might also be expected to be active in the p2 domain and V2 interneurons . However , this was not observed in our experiments , raising the possibility that an unknown repressor suppresses E1 activity in the p2 domain . Therefore we tested the effect of two known repressors , Sox1 and Chx10 , present in the p2 domain and postmitotic V2a interneurons , respectively [38–40] . When electroporated , Sox1 and Chx10 were effective in repressing the ectopic induction of GFP reporter activity driven by Lhx3 ( Fig 5Q , 5R , 5T , 5U and 5V ) . There are two predicted Chx10-binding motifs in E1 but mutating them did not abolish the repressive activity of Chx10 ( S5A and S5N–S5S Fig ) . Since Chx10 binds to AT-rich nucleotides and is known to block hexameric Isl1-Lhx3 at the Hb9 promoter , we decided to test whether the Isl1-Lhx3 binding motif E1-3 that we had identified was required for repression by Chx10 [32] . Because mutating the E1-3 site abrogated E1 activity , we could not test the repressive activity of Chx10 using mutE1-3 . Instead , we used tandem repeats of the E1-3 site ( 6xE1-3 ) for GFP reporter and found that its induction by Lhx3 or Isl1-Lhx3 was blocked by Chx10 ( S5T–S5V , S5X and S5Y Fig ) . This appeared to require DNA binding since the Chx10 N51A point mutant defective in DNA binding failed to repress the induction of 6xE1-3 ( S5W Fig ) [41] . In the case of Sox1 , ΔNSox1 was still potent in its repression but C-Sox1 lacking the DNA binding domain was not ( S5G–S5J Fig ) [40] . Thus , DNA binding is also required for Sox1-mediated repression . The E1 reporter was still active in motor neurons in the presence of Sox1 or Chx10 , indicating that the repressors are only effective in non-motor neurons . Nevertheless , Chx10 but not Sox1 was able to inhibit the induction of E1::GFP reporter by exogenous Isl1 and Lhx3 ( S5D and S5E Fig ) . We conclude that E1 activity is repressed by Sox1 in p2 progenitors and by Chx10 in V2a interneurons . To search for Isl1-Lhx3-binding motifs in the E1 reporter , we examined the results of ChIP-Seq in NIL cells , inducible embryonic stem cells with sm neuronal traits [31] . Strong binding of Isl1 and Lhx3 occurred in E1 ( Fig 6A ) . Of the luciferase reporters with point mutations , all were induced by Isl1 and Lhx3 except mutE1-3 , and the activity of all the GFP reporters except mutE1-3 appeared ectopically in the dorsal spinal cord when Isl1 and Lhx3 were co-electroporated ( Fig 6B–6H and 6J–6L ) . E2 was not induced by Isl1 and Lhx3 , suggesting the specificity of E1 ( S2B Fig ) . GFP expression of mutE1-3 was completely lost even in the ventral spinal cord , indicating that E1-3 site activity relies on the endogenous Isl1 and Lhx3 present in motor neurons . MutE1-3 reporter activity was present in bm/vm neurons in the hindbrain when the reporter was introduced by electroporation , indicating that the E1-3 site is sm neuron-specific and its alteration by mutation does not affect basal transactivating ability ( S6I and S6J Fig ) . To test whether the E1-3 site was sufficient to drive sm-specific gene expression , we generated a GFP reporter with six tandem repeats of the E1-3 site ( 6xE1-3 ) . Expression of the 6xE1-3 reporter was selective in sm neurons by itself and expanded dorsally in the presence of Isl1 and Lhx3 , indicating that Isl1-Lhx3 binding to the E1-3 site is sufficient to drive motor neuron-specific gene expression ( Fig 6I , 6L and S4V Fig ) . Together our results suggest that Isl1-Lhx3 complex activates E1 in motor neurons . E2 sequences are conserved in mouse , chicken , zebrafish and fugu , but no E2 sequences were identifiable in the non-tetrapod chordate , lamprey and the cephalochordate amphioxus , at least in any currently available database [42–44] ( S9 Fig ) . This indicates that E2 might have appeared in genomes when limb structures arise in the early vertebrates . All the E2 sequences derived from mouse , chicken and zebrafish were active in motor columns of the ventral spinal cord ( Fig 7A–7C ) . We also generated putative E2 reporter from fugu and found that it was specific for motor neurons ( Fig 7D ) . To search for E2-binding transcription factors , we first examined ChIP-Seq data for Phox2 , Isl1 and Lhx3 binding in embryonic stem cell lines but found no significant peaks in the E2 region ( S9 Fig ) [31] . In a candidate approach , we decided to test the activity of OC factors , previously known to promote LMC identity and bind to E2 in ChIP assays [45] . When the OC-1 factor was co-electroporated , E2::GFP reporters became active in the entire spinal cord ( Fig 7H–7L and 7P ) . OC-1 did not induce E1::luciferase reporter as previously reported ( S2B Fig ) [45] . Using the UCSC genome browser , we searched for two putative OC factor-binding sites in the E2 enhancer that were highly conserved in fugu , stickleback , zebrafish , coelacanth , chicken , mouse and human ( Fig 7R ) . MutE2-1 and mutE2-2 retained their activity in motor neurons but only mutE2-1 responded to OC-1 ( Fig 7E , 7F , 7H , 7M , 7N and 7P ) . When both sites were mutated in mutE2-3 , the reporter was not induced by OC-1 ( Fig 7G , 7O and 7Q ) . Similar responses were observed in luciferase assays in that the induction of E2 activity by OC-1 was significantly downregulated in mutE2-3 ( Fig 7S ) . We also tested whether downregulation of OC factors affect E2 activity or not . When we knocked down OC-1 and OC-2 by siRNA , E2::GFP activity was significantly reduced ( Fig 7T–7V and S7B–S7D Fig ) . Similarly , when we misexpressed Hoxc9 that switchs the LMC identity to thoracic motor neurons as determined by reduced expression of Foxp1 and Raldh2 , E2 activity was also downregulated ( S7E–S7L Fig ) [46] . Together , our results suggest that OC factors are necessary and sufficient to induce the LMC-specific activity of the E2 enhancer . It has been shown that the E1 enhancer sequence is strongly conserved from fugu to human . We confirmed this , and found that the Phox2-binding and Isl1-Lhx3-binding motifs we identified were also highly conserved ( Fig 8A ) . To examine the vertebrate origin of motor neurons , we tested for the presence of the E1 enhancer in the lamprey , a living representative of the most ancient vertebrates [42 , 43] . Although there was generally little conservation of the entire E1 sequences , we found that the core region of E1 containing the Phox2 and Isl1-Lhx3 binding sites were relatively well conserved ( Fig 8B and 8C ) . To test whether enhancer activity was conserved , we generated GFP enhancers from the E1 sequences of mouse , chick , zebrafish and lamprey and electroporated them into the chick spinal cord . All the reporters showed bm neuron-specific GFP expression in the chick hindbrain ( Fig 8D , 8H , 8L and 8P ) . The mouse , chick and lamprey E1 enhancers were active in the motor neurons of the spinal cord , and expanded in the presence of Phox2 or Isl1-Lhx3 ( Fig 8E–8G , 8I–8K and 8Q–8S ) . However , zebrafish E1 was not active in the spinal cord motor neurons but nevertheless was induced by mPhox2 and zIsl1-zLhx4 in the dorsal spinal cord ( Fig 8L–8O ) . The same analysis was applied to the E2 enhancer sequence . In contrast to Uemura et al , we detected the E2 enhancer sequence with conserved OC binding motifs in fugu [12] . We were unable to retrieve any putative E2 sequence from the lamprey genome when we conducted a BLAST search using E2 sequences from human , mouse , chicken , coelacanth , zebrafish , stickleback , and fugu [42] . We also found no match in amphioxus genomic data [44] . To be sure of the absence of E2 in the lamprey genome , we also analyzed vertebrate basewise conservation scores ( phyloP ) using the newest version , mmc10 , which includes the lamprey genome ( S9 Fig ) . Together , we conclude that motor neuron-specific E1 activity in the CNS is well-conserved from lamprey to man , whereas E2 appeared first in fugu along with the origin of limb/fin structures .
Motor neurons consist of multiple motor columns that innervate distinct muscle targets . Each motor column expresses some combination of transcription factors that form the basis for diversification of motor neurons [1 , 33] . Naturally the interplay between cis-regulatory elements ( i . e . , promoters and enhancers ) and trans-regulatory elements ( i . e . , transcription factors ) is critical for selective gene expression in individual motor neuronal subsets . In the present study , we focused on transcriptional regulation of Islet1 , one of the representative markers of motor neurons that define motor neuron identity . Using stable and destabilized GFP reporters introduced into chick embryos , we demonstrated that E1 and E2 are differentially expressed in motor neuron subsets: E1 is active in all motor neurons and later becomes restricted to cranial motor neurons and MMC and PGC neurons in the spinal cord; E2 is more selective , being active in limb-innervating LMCm neurons that express Isl1 , in line with previous reports in the zebrafish [12] ( Fig 7W ) . In the present work we have further characterized the transcription factors that interact with enhancers and found that Phox2 binds to E1 and drives Isl1 expression in the hindbrain . Phox2a is necessary and sufficient to drive E1 activity since exogenous Phox2a induced E1 activity in embryos and cell lines , and knockdown of Phox2b by siRNA abrogated E1 activity . We designated as E1-4 the Phox2a binding site in E1 whose mutation abolished its activity in bm neurons but not in sm neurons . The mutE1-4 enhancer was not responsive to exogenous Phox2a but responded well to exogenous Isl1 and Lhx3 , all of which supports the existence of bm neuron-specific gene transcription mechanisms . Similarly , we have demonstrated that the Isl1-Lhx3 complex induces E1 in sm neurons via the E1-3 site . Mutations at the E1-3 site abolished expression in sm neurons and prevented induction by Isl1-Lhx3 . It is noteworthy that the mutE1-3 construct did not respond to exogenous Phox2a but was active in native bm neurons . Perhaps the cellular environment of the ectopic bm neurons was not as favorable as the native ones , and additional factors present in bona fide bm neurons may bind to this site and facilitate the action of Phox2a on E1 . A likely candidate for such a factor is Isl1; the idea that it synergises with Phox2a is suggested by the surprisingly extensive overlap between binding sites for Phox2a and for Isl1 in a genomewide ChIP-Seq analysis [31] . Alternatively , Phox2a may act together with bHLH factors , as has been suggested to occur in sympathetic neurons [47] . Previous studies by us and others have demonstrated that Isl1 switches the stoichiometry of the tetrameric Lhx3 complex to that of a hexameric Isl1-Lhx3 complex to induce motor neuron identity , and aberrant assembly of the Lhx3 complex in motor neurons is prevented by repressors such as LMO factors and Hb9 [5 , 32 , 35] . In this study , we unexpectedly found that the Lhx3 complex is capable of activating E1 , which may contribute to the initiation of Isl1 transcription when motor neurons are about to become postmitotic . Nevertheless , ectopic expression of Isl1 in Lhx3-expressing motor neuron progenitors and V2 interneurons was blocked by the repressors Olig2 , Sox1 and Chx10 . These repressors were thus effective in blocking the activation of E1 by Lhx3 . Interestingly , the ectopic formation of motor neurons and the E1 activity induced by Isl1-Lhx3 were also blocked by exogenous Chx10 but not by Olig2 and Sox1 , suggesting that the potencies of these repressors or their mechanisms of action were different; repression may require DNA binding or protein-protein interaction . For instance , Olig2 may act as a repressor by binding to the E-box element , or it may squelch other bHLH factors such as Ngn2 by protein-protein interaction; either way it suppresses motor neuron formation [48] . In our study , we mapped the E-box site in E1 and found that mutating it made E1 insensitive to Olig2 . Thus , DNA binding of Olig2 is important for its repressive action on E1 . In the case of Chx10 , mutating two consensus Chx10 binding sites had no effect . Interestingly , it is reported that the binding sites for Chx10 and hexameric Isl1-Lhx3 are similar and therefore Chx10 may inhibit Isl1-Lhx3 binding to the Hb9 promoter [32] . In agreement with this we showed that Chx10 inhibits the transcriptional activation of tandem repeats of the E1-3 site by Isl1 and Lhx3 . The point mutant Chx10 N51A deficient in DNA binding failed to inhibit the activity of E1-3 site , implying that Chx10 may bind to this site . What then would be the explanation for selective inhibition of Lhx3 complex activity by repressors ? Our results in chick embryos and cell lines showed that the Lhx3 complex is less potent than the Isl1-Lhx3 complex in activating E1 . This could be due to the lower DNA binding affinity of the Lhx3 complex demonstrated previously [32] . In addition , the binding elements for the Lhx3 and Isl1-Lhx3 complexes appear to be qualitatively different , and the different arrangements of multiple repeats and spacing between them should make the difference even greater , and may render the Lhx3 complex more susceptible to repressors [32] . It is noteworthy that Isl1 alone is not effective in inducing motor neuron identity or activating the E1 , unlike Lhx3 or Isl1-Lhx3 . Structure-function analysis suggests that NLI favors its binding to LIM domains of Lhx3 over Isl1 , indicating that Lhx3 could be more efficient in forming a tetrameric complex in vivo [49] . In addition , the Lhx3 binding domain ( LBD ) of Isl1 at the C-terminus binds to Lhx3 to form hexameric Isl1-Lhx3 complex , which makes tetrameric Lhx3 or Isl1 complexes less available [5] . Recently , it is reported that the LBD domain also interacts with the LIM domains of Isl1 [50 , 51] . The intramolecular interaction is weak but specific , preventing unnecessary DNA binding and facilitating cofactor exchange in the cell . Indeed , Isl1 is known to act in synergy with other nuclear factors in neurons and other tissues [52–54] . Together , more diverse choice of cofactors and its tendency to suppress its own binding to DNA may explain weak biological activity of Isl1 by itself in motor neurons . Considering the evolutionary emergence of transcription factors , it is noteworthy that Phox2 and Islet are found even in Ciona internalis in which Mnx-expressing somatic and Phox2-expressing visceral neurons are distinguishable [14 , 55] . Phox2 and Islet factors are also found in the lamprey and amphioxus , whose motor neurons are primitive , lacking motor columns and motor pools [56–58] . Thus , Phox2 and Isl1-Lhx3 were used in the motor neurons of ancient aquatic animals even before they diversified . In line with this , we identified Phox2 and Isl1-Lhx3 binding motifs in E1 enhancers from lamprey to man . Anatomical and genetic comparisons between species have suggested that the boundary between the hindbrain and spinal cord motor neurons is defined even in amphioxus ( cephalochordate ) and lamprey ( chordate ) [59–61] . Hence it appears that the motor neuron-specific activation of Isl1 with the help of Phox2 and Isl1-Lhx3 is evolutionarily conserved . In this study , zebrafish E1 was not active in chick spinal cord motor neurons nor was it activated by exogenous Isl1-Lhx3 factors from other species . Nevertheless , we found that it was induced by zebrafish Isl1-Lhx4 . There was only a one base difference between the Isl1-Lhx3 binding site in zE1 and the sites in mouse and chick . Substituting the binding site in mE1 for zE1 did not make it responsive to mIsl1 and mLhx3 . It is possible that species differences in LIM-HD factors account for the absence of zE1 activity in chick spinal cords . However , the LIM-HD factors of zebrafish and chick differ by only one or two amino acids . In fact substantial cross-species variation has been reported in protein-DNA interactions that cannot be simply explained by changes in protein or DNA sequences [62 , 63] . Since an additional whole genome duplication event occurred in ray-finned fish including zebrafish , it is possible that extensive rearrangements of multiple cis- and trans-elements may have contributed to the zebrafish-specific transcription program . We and others have shown that the E2 enhancer is selective for LMCm neurons in the limb-innervating motor columns that express Isl1 [12] . Our detailed fate mapping analysis showed that E2 enhancer activity is strong in LMCm neurons . We and others also showed that E2 responded to OC-1 factors , which are important for LMC-specific gene expression [45] . In mice deficient in OC factors there are fewer LMCm neurons and more LMCl and PGC neurons as a result of a reduced level of Isl1 protein [45] . In line with this , we demonstrated that knockdown of OC factors or disruption of LMC identity by manipulating the Hox code coincided with reduced E2 activity . Taken together , these findings suggest that OC factors and E2 activity are important for maintaining Isl1 expression in LMCm neurons . LMC neurons were added to motor columns when limb/fin structures appeared during evolution , and this coincided with the appearance of the Hox co-factor FoxP1 and loss of Lhx3 [16 , 19] . FoxP1 interacts with Hox proteins , which were altered in parallel with the emergence of paired fins/limbs [11 , 64] . Foxp1 also suppresses Lhx3 , and this suppression is a prerequisite for LMC identity [10 , 11] . Likewise , in the absence of Foxp1 , LMC neurons display HMC-like properties , reflecting their evolutionary origin [65] . Nevertheless , LMCm neurons maintain Isl1 expression in the absence of Lhx3 , and thus in the absence of the Isl1-Lhx3 complex . Hence it is likely that tetrapod animals adopted the alternative enhancer E2 together with OC factors to maintain Isl1 expression in LMCm neurons due to the absence of Lhx3 . We used two reporters , one expressing stable GFP and the other , transient destabilized GFP , to trace cells that had activated the reporter at least once during their development and cells that were currently activating the enhancer , respectively . In this way , we expected to see whether motor column identity was acquired progressively or not . We found that the stable E1::GFP reporter marked all motor neurons , starting from the initial E1 activity in newborn motor neurons that had just begun to express Isl1 . Thus , the transient assembly of Isl1 and Lhx3 in order to initially acquire motor neuron identity occurs in all motor neurons subsets , as previously suggested [5] . On the other hand , the destablized E1 reporter representing current E1 activity only labeled MMC and PGC . This suggests that E1 continues to be active in MMC and PGC , but that the initial activity of E1 disappears in the other motor columns . LMC neurons appear to initially use the E1 enhancer to obtain pan-motor neuron identity but later shut off E1 activity when they lose Lhx3 . In the case of E2 reporters , the stable and transient E2 GFP reporters were both expressed in motor neurons once they reached a lateral position , mostly in LMCm neurons . Thus , the latter may use E1 and E2 sequentially to drive Isl1 expression during their transition from pan-motor neurons to LMC neurons . LMCl neurons acquire their identity when they pass through the LMCm area , in which they are exposed to retinoic acid signaling [66 , 67] . This induces Lhx1 , which suppresses expression of Isl1 and specifies the LMCl fate . Thus , E2 may be initially active in all LMCs but later cease to be active in LMCl neurons when they migrate more laterally , with the help of Lhx1 and retinoids . Thus , gradual changes in the interactions between transcription factors and enhancers lead motor neurons to acquire their columnar identity progressively . We have seen that E1 has been evolutionarily conserved since the era of the lamprey , a jawless vertebrate which possesses primitive motor neuron [56] . Recent comparative genomic studies have demonstrated that the segmentation of hindbrain and spinal cord is conserved in the lamprey , and is under the control of patterning signals such as Hox clusters [60 , 64 , 68] . The hindbrain and spinal cord motor neuron-specific expression of Islet1 could be achieved by E1 in the lamprey as part of the patterning program . However , the E2 enhancer , which is restricted to limb-innervating motor neurons , appeared when animals such as fugu and tetrapods developed limbs . E2 evolved to cooperate with OC factors and drive Isl1 expression in LMC neurons . Thus , our observations demonstrate that evolutionary conserved enhancers drive motor column-specific gene expression during motor neuron development .
Isl1 enhancers were amplified by PCR with primers using genomic DNA from mouse , chick , zebrafish , fugu and lamprey ( S1 Table ) . PCR fragments were subcloned into the following reporter vectors: pCS2 mini CMV-GFP , pCS2 mini CMV-luciferase and tk-luciferase reporter vector [69] . pCS2 mini CMV-GFP/luciferase contains a 60 bp TATA box and the transcription initiation site of the cytomegalovirus ( CMV ) promoter ( GenBank accession no . X03922: nt 1090–1149 ) . The mini CMV promoter and eGFP sequences were obtained by PCR amplification from pEGFP-N1 ( Clontech ) . Mutations were introduced in E1 or Chx10 by PCR-based mutagenesis . Zebrafish and Fugu E2 DNAs were amplified from Dario rerio and Fugu rubripes , respectively . In ovo electroporation was performed as described previously [35] . In brief , about 1 μg/μl of DNA solution was electroporated into the chick spinal cord at Hamburger and Hamilton ( HH ) stages 12 and harvested at HH stages 23 to 29 . In the case of OC-1 , HH stage 14 embryos were used . For the hindbrain electroporation , DNA solution was injected into HH stage 8 to 10 embryonic neural tube anteriorward from the level of approximately the third somite as previously described [70] . Electroporation was performed with a condition of 5 times of pulses , 20–24 volts , 50 msec , 1 sec intervals . Immunohistochemistry was performed as described previously [35] . Following antibodies were used: mouse anti-Isl1 ( DSHB ) , mouse anti-Isl2 ( DSHB ) , rabbit anti-Isl1/2 [22] , mouse anti-MNR2 ( DSHB ) , rabbit anti-GFP ( Invitrogen ) , rabbit anti-Foxp1 ( Abcam ) , rabbit anti-Sox1 ( Cell signaling ) , guinea pig anti-Lhx3 [71] , guinea pig anti-Chx10 [71] , guinea pig anti-Olig2 [36] and mouse anti-Neurofilament ( DSHB ) . For wholemount immunostaining , Day 4 . 5 chick embryos electroporated at Day 2 were fixed and incubated with primary antibodies for 3 days and secondary antibodies for 1 day . For in situ hybridization , transverse sections were hybridized with digoxigenin-labeled probes specific for mouse Phox2a ( full CDS ) , mouse OC-1 ( partial CDS , 469–1263 bp ) . All images were captured with epifluorescent microscope or confocal microscope ( Zeiss ) . Cells in each quadrant of the ventral horn were counted on z-series of slice images using a confocal microscope and ZEN2009 imaging software ( Zeiss ) . At least 3 embryos were quantified from each group , and 3–4 images were collected from each spinal cords . %GFP/column was calculated as the percentage of the number of GFP-expressing cells among the motor neurons in each column . To quantify GFP intensity induced by exogenous transcription factors in the chick spinal cords after electroporation , 12 μm-thick transverse sections were immunolabeled with GFP . The background-subtracted pixel intensities of GFP in 120 x 240 μm2 areas in the dorsal spinal cord were measured using ImageJ . At least 10 sections from 4 embryos were analyzed for each group . Statistical significance was analyzed by unpaired Student’s t-test and the Kruskal-Wallis test for multiple comparisons . E1::GFP transgenic mice were generated in CL56BL6 background as described previously [72] . MutE1-4::GFP transgenes were prepared and linearized with the SalI/EcoRI for microinjection as described [73] . Transient transgenic embryos were generated by pronuclear injection into fertilized eggs . Animal experiments were performed under the guidelines of the Korea Ministry of Food and Drug Safety ( Act No . 9025 ) with approval of procedures by the Institutional Animal Care and Use Committee of Gwangju Institute of Science and Technology ( GIST-2010-12 ) . 293T cells were transiently transfected with reporters and transcription factors using Lipofectamine 2000 reagent ( Invitrogen ) . CMV-β-galactosidase plasmid was co-transfected to normalize transfection efficiency . After 2 days , cell extracts were assayed for luciferase assays and β-galactosidase assays . Data represent as means of triplicate values , repeated at least three times . Enhancer sequences from human , mouse , chicken , zebrafish , and fugu were retrieved from UCSC genome browser . Comparative analyses of the E1 and E2 sequences were done with mVISTA ( genome . lbl . gov/vista ) using the LAGAN alignment tool [74 , 75] . All E1 and E2 sequences from five species were searched against the lamprey genome using BLAST with “somewhat similar sequences ( blastn ) ” options and an E-value cut-off of 0 . 05 . Potential transcription factor binding sites in these conserved sequences were predicted using rVISTA [76] . A phylogenetic tree was constructed with MEGA version 6 maximum likelihood method with 1 , 000 bootstrap replications [77] . The sequences of sense and antisense oligonucleotide used in our EMSA were as follows: E1-S 5′- CCAATATAAAATGCAAATTAGGTTATTAAGTGGAGTGGCAGAC-3′ E1-AS 5′-GTCTGCCACTCCACTTAATAACCTAATTTGCATTTTATATTGG-3′ mutE1-4-S 5′-CCAATATAAAATGCAACGCGGGTTCGCGAGTGGAGTGGCAGAC-3′ mutE1-4- AS ′-GTCTGCCACTCCACTCGCGAACCCGCGTTGCATTTTATATTGG-3′ Biotin-labeled probe was incubated with nuclear extract of HEK 293T cells transfected with mouse Phox2a in binding buffer ( 10 mM Tris , pH 7 . 5 , 50 mM KCl , 5 mM MgCl2 , 1 mM dithiothreitol , 0 . 05% Nonidet P-40 , and 2 . 5% glycerol ) with poly ( dI-dC ) at RT . Competition reactions were performed by adding a 200-fold excess of unlabeled double-stranded probe . The reactions were resolved on non-denaturing 6% polyacrylamide gels and visualized by chemiluminescence ( Thermo Scientific ) . Embryonic mouse hindbrains were micro-dissected at E13 . 5 . Cells were lysed after cross-linking with 1% formaldehyde . Chromatin with a DNA fragment length of less than 500 bp was obtained by sonication and immunoprecipitated with rabbit anti-Phox2b [78] , rabbit anti-Histone H3 ( Millipore ) and rabbit IgG ( Vector Labs ) . The Phox2 binding motif in E1 was amplified by PCR in each sample . For ChIP-Seq analysis , previous results were retrieved and examined around the Isl1 locus [31] .
|
During evolution , motor neurons became specialized to control movements of different body parts including head , trunk and limbs . Here we report that two enhancers of Isl1 , E1 and E2 , are active together with transcription factors in motor neurons . Surprisingly , E1 and its response to transcription factors has been conserved in evolution from the lamprey to man , whereas E2 is only found in animals with limbs . Our study provides an evolutionary example of how functional diversification of motor neurons is achieved by a dynamic interplay between enhancers and transcription factors .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Functional Diversification of Motor Neuron-specific Isl1 Enhancers during Evolution
|
Melioidosis is a frequently fatal disease requiring specific treatment . The yield of Burkholderia pseudomallei from sites with a normal flora is increased by culture using selective , differential media such as Ashdown’s agar and selective broth . However , since melioidosis mainly affects people in resource-poor countries , the cost effectiveness of selective culture has been questioned . We therefore retrospectively evaluated this in two laboratories in southeast Asia . The results of all cultures in the microbiology laboratories of Mahosot Hospital , Vientiane , Laos and Angkor Hospital for Children , Siem Reap , Cambodia , in 2017 were reviewed . We identified patients with melioidosis who were only diagnosed as a result of culture of non-sterile sites and established the total number of such samples cultured using selective media and the associated costs in each laboratory . We then conducted a rudimentary cost-effectiveness analysis by determining the incremental cost-effectiveness ratio ( ICER ) per DALY averted and compared this against the 2017 GDP per capita in each country . Overall , 29 patients in Vientiane and 9 in Siem Reap ( 20% and 16 . 9% of all culture-positive patients respectively ) would not have been diagnosed without the use of selective media , the majority of whom ( 18 and 8 respectively ) were diagnosed by throat swab culture . The cost per additional patient detected by selective culture was approximately $100 in Vientiane and $39 in Siem Reap . Despite the different patient populations ( all ages in Vientiane vs . only children in Siem Reap ) and testing strategies ( all samples in Vientiane vs . based on clinical suspicion in Siem Reap ) , selective B . pseudomallei culture proved highly cost effective in both settings , with an ICER of ~$170 and ~$28 in Vientiane and Siem Reap , respectively . Selective culture for B . pseudomallei should be considered by all laboratories in melioidosis-endemic areas . However , the appropriate strategy for implementation should be decided locally .
Burkholderia pseudomallei is the causative agent of melioidosis , an important but under-recognised public health problem throughout the tropics [1] . It grows readily in clinical samples from normally sterile sites , such as blood cultures , aseptically aspirated pus from abscesses or body fluids . In sites with a normal flora , where it may be overgrown by other bacteria , the yield of culture can be improved by using selective differential media , such as Ashdown’s agar and broth , that suppress the growth of other organisms and encourage the formation of characteristic colonies [2 , 3] . We have used these media routinely in our laboratories in melioidosis-endemic areas for more than 30 years , and have shown that they increase the number of cases of melioidosis diagnosed [3–11] . However , we have been fortunate to have research funding to support the associated costs of additional media , which would not be available to the majority of laboratories in endemic areas that have to make difficult decisions about the allocation of more limited resources . Melioidosis is unevenly distributed across endemic areas and others have questioned whether the routine use of selective media is cost effective [12 , 13] . We therefore decided to review the cost-effectiveness of our current approach during 2017 in two different settings that used different strategies for the deployment of selective media for B . pseudomallei culture .
The testing strategies in the 2 hospitals were different . In Vientiane , all throat swabs , pus and wound swabs , sputum and endotracheal aspirates , and urine samples received were cultured using selective media for B . pseudomallei . Throat swabs , which were sent specifically for B . pseudomallei culture from patients in whom melioidosis was suspected , were routinely cultured using selective media alone ( one ASH plate and one SB ) since previous experience has shown us that B . pseudomallei is rarely present in large numbers in such samples and is difficult to detect amongst the large numbers of colonies of other species that are invariably present on non-selective media [3] . Pus and wound swabs , sputum and endotracheal aspirates were cultured on ASH and SB in addition to non-selective media . The centrifuged deposit of urine samples was cultured on half an ASH plate in addition to routine semi-quantitative culture on chromogenic agar . All SB were subcultured onto half an ASH plate . In Siem Reap , selective media were used only when the responsible clinician indicated a suspicion of melioidosis on the request form . Laboratory methods were similar to those used in Vientiane except that whole ASH plates were used for urine culture ( half for neat urine and half for the centrifuged deposit ) and SB subculture . The consumable costs per Ashdown’s plate and broth were calculated for the additional selective media based on the prices of the ingredients in Thailand , where both laboratories purchase consumables and which was considered representative of melioidosis-endemic areas in Asia . These equated to 10 baht ( approx . $0 . 31 ) per ASH and 8 baht ( approx . $0 . 25 ) per SB . In both laboratories , colonies suspected of being B . pseudomallei were screened by Gram stain , oxidase test and latex agglutination . Routine confirmation of identity was by API 20NE ( bioMérieux , Basingstoke , UK ) . We performed a rudimentary cost-effectiveness analysis as an indication as to whether the incremental costs of selective media would represent a judicious use of scarce resources in the two settings . The approach is similar to that used in a previous cost-effectiveness analysis of candidate melioidosis vaccines [14] . We considered the total additional costs for consumables for selective media and applied an additional 30 minutes of a microbiologist’s time per sample , costed at $2 . 90 per hour based on accounting records at the Cambodia site . We used an estimated 3% mortality rate in non-bacteraemic melioidosis patients when identified and treated , based on the literature [15] and our own data ( mortality in non-bacteraemic cases 3 . 95% in Vientiane and 0 . 7% in Siem Reap ) , as compared with a mortality rate of 9% when undetected , based on the reported mortality before the introduction of modern treatment regimens [16] . We assumed that each death averted was associated with 66 Disability-Adjusted Life Years ( DALYs ) in Siem Reap , a paediatric hospital where the mean patient age was 5 . 7 years , and 37 DALYs in Vientiane where the mean patient age was 38 . 5 years , using the country-specific estimated life expectancy of individuals at this age [17] . The incremental cost-effectiveness ratio ( ICER ) per DALY averted was calculated by dividing the incremental costs of consumables and labour divided by the total number of DALYs averted ( Eq 1 ) . The ICER was compared against the Laos and Cambodia 2017 GDP per capita ( $2 , 457 and $1 , 384 , respectively ) to determine whether the use of selective media would be cost-effective . All samples were submitted primarily for the purposes of routine diagnosis . In addition , many of the patients were included in studies of the aetiology of fever . In Cambodia the study was approved by the AHC Institutional Review Board ( AHC IRB , 979–14 ) and the Oxford Tropical Research Ethics Committee ( OxTREC 550–14 ) . In Laos the study was approved by the Oxford Tropical Research Ethics Committee ( OxTREC 006–07 ) and the Lao National Ethics Committee for Health Research ( 028–17 ) . For these studies , patients or their parents or guardians provided written informed consent .
During 2017 , 145 patients with culture-positive melioidosis were diagnosed in Vientiane , of whom 64 ( 44 . 1% ) were only diagnosed by culture of 82 non-sterile sites . In Siem Reap , there were 53 cases of culture-positive melioidosis of whom 45 ( 84 . 9% ) were only diagnosed by culture of 46 non-sterile sites ( one patient was positive in superficial swab specimens from two anatomical sites ) . The breakdown of the positive samples and the media which were positive is shown in Table 1 and full results for individual culture-positive patients are given in S1 Table . Eighteen patients in Vientiane and eight in Siem Reap were diagnosed by throat swab culture only , but most of these were positive on direct plating on ASH and only one positive throat swab in Vientiane and three in Siem Reap were detected by SB enrichment alone . The majority of pus samples and wound swabs were positive on non-selective media , with an additional four ( 9 . 1% of positives ) detected through the use of ASH in Vientiane ( with growth of small numbers of B . pseudomallei on ASH but no growth on non-selective plates ) and none in Siem Reap , but the only additional yield from the use of SB for pus and wound swabs was from a single specimen in Siem Reap . Two of the specimens positive on ASH but not on non-selective media were swabs rather than pus and one was taken after several weeks of treatment . The numbers of positive sputum and endotracheal aspirates and urine samples were small and confined to Vientiane . More than half of the positive respiratory samples were only positive using selective media . Two patients in Vientiane were only diagnosed with melioidosis as a result of culture of a centrifuged deposit of urine on ASH . Overall , in Vientiane 27 patients ( 18 . 6% of all culture-positive patients ) would not have been diagnosed without the use of ASH , the majority of whom were only positive on throat swab culture , and an additional two ( 1 . 4% ) would not have been diagnosed without the use of SB . In Siem Reap , five ( 9 . 4% ) would not have been diagnosed without the use of ASH and four ( 7 . 5% ) would not have been diagnosed without the use of SB . During 2017 the Vientiane laboratory processed 2 , 130 throat swabs , 1 , 796 urines , 728 pus or wound swabs , 350 deep pus , 346 sputum and 142 ET aspirates . Table 2 shows the estimated consumable costs of the selective media used in processing these samples and the cost of detecting an additional case of melioidosis by using either ASH or SB on each sample type . The total consumable cost of using these additional selective media throughout the year was $2 , 921 . 02 , meaning that the total consumables costs of each of the 29 additional cases detected using our current approach was almost exactly $100 . The cost per additional positive sample detected varied considerably , from approximately $25 for an ASH plate on a throat swab to nearly $200 or more for the use of SB on each sample type . In Siem Reap , 416 samples were cultured during the year using selective media on the basis of clinical request at a consumables cost of $349 . 60 , and this resulted in the diagnosis of nine cases of melioidosis that would not have been confirmed had selective media not been used , meaning that the consumable cost of selective culture per additional case detected was only approximately $39 . The cost per additional positive detected was approximately $7 . 60 for culture of a throat swab on ASH and ranged between approximately $23 and $150 for the additional use of SB . The additional 29 cases detected in Vientiane would corresponed with 64 . 4 DALYs averted , at a total cost of ~$10 , 966 including both consumables and labour , with an ICER of ~$170 per DALY averted . In Cambodia where only 416 samples were cultured with selective media the total cost was ~$903; the additional 9 detected cases would correspond with 31 . 9 DALYs averted and an ICER of ~$28; in both settings the use of selective media would therefore appear to be higly cost-effective , with an ICER well below the GDP per capita in their respective settings .
The additional yield from using selective media for culture of sites with a normal flora to detect patients with melioidosis is well established [3–9] . Overall the use of selective media in this study was responsible for the diagnosis of 20% of all the cases of melioidosis in Vientiane and 16 . 9% of the cases in Siem Reap , considerably more than in our previous study conducted in northeast Thailand nearly 30 years ago ( 3 . 5% ) [3] . Since selective media only were used for throat swabs , it is not possible to compare the relative yields of selective and non-selective media , although in our previous studies B . pseudomallei grew on non-selective media from only 9 of 118 culture-positive throat throat swabs [3] . However , the relative benefit of using selective media will depend on several factors such as the local incidence of melioidosis , local clinical practice , the laboratory testing strategy adopted , and the cost of the media themselves . Understanding the local costs and benefits of different approaches is clearly of importance to laboratory managers in melioidosis-endemic areas who have to make decisions about the most effective way to deploy scarce resources in order to bring about the greatest benefit to patients . This question came up repeatedly during a recent workshop on melioidosis in Cambodia [18] , prompting us to undertake the current analysis . While further context-specific analyses are advised , our findings from two different settings indicate that more extensive use of selective media than is commonly practiced in many endemic areas is likely to be highly cost-effective . There has been one previous attempt to estimate the cost-effectiveness of selective culture for melioidosis diagnosis [13] . This study , which took place in Kuala Lumpur , Malaysia , an area of relatively low melioidosis incidence , and predominantly entailed respiratory samples , estimated the costs to detect one additional culture and patient as $25 and $75 , respectively . Another study in Kampong Cham Provincial Hospital , Cambodia found that only one additional B . pseudomallei positive sample was identified amongst 241 sputum samples cultured using SB and ASH . Clearly the local incidence of melioidosis is likely to be one of the factors with the greatest impact on the cost effectiveness of selective culture . However , the testing strategy adopted ( e . g . using selective culture on all samples of particular types as opposed to culturing only those from patients in whom clinicians indicate a suspicion of melioidosis ) will also have a major impact on cost-effectiveness . Overall , in our study the costs of selective media per additional case detected varied considerably between the two laboratories as a result of the difference in screening strategy . In Vientiane , the cost of selective media using the current approach was approximately $380 per additional case diagnosed ( including both consumables and labour ) as opposed to only $100 in Siem Reap . The relative benefits of adding SB enrichment also varied between the sites , with only 2 of 39 samples that were positive by selective culture alone in Vientiane being detected through broth enrichment as opposed to 4 of 9 in Siem Reap . Clearly there are differences between the patient populations in the two centres , with patients in Vientiane being from all age groups whereas only children were included in Siem Reap , which might have affected the quality of the samples collected . While this emphasises the fact that decisions about the most appropriate culture strategy needs to be decided at a local level , the very low ICERs imply that more extensive use of selective media could cost-effectively yield additional gains . This is particularly likely in Cambodia , where the use of selective media was restricted to patients in whom the clinician suspected melioidosis . Assuming a willingness to pay $1 , 384 per DALY averted ( the Cambodia GDP per capita ) , spending up to $50 per patient on selective media cultures in other patients would remain cost-effective even if the prevalence of undetected cases in these patients was as low as 1% . In both sites , culture of a throat swab on ASH was confirmed as an effective strategy for detecting patients with melioidosis who were not diagnosed in other ways . In Vientiane , the majority of throat swabs are submitted specifically for the investigation of melioidosis . This does not reflect the presence of pharyngitis in most of these patients , but is likely mainly to represent contamination of the throat by lower respiratory tract secretions . It is not common practice in Laos for clinicians to send sputum for bacteriological culture . Had this been the case , the additional benefit from culture of throat swabs is likely to have been less . However , culture of sputum and ET aspirates on ASH was also relatively cost-effective in Vientiane . The additional benefit from using ASH for culture of pus/wound swabs and urine samples was less than that for throat swabs , and therefore correspondingly less cost-effective , but both methods did detect some patients with melioidosis who would not have been diagnosed in other ways . The use of ASH for culture of pus from previously undrained abscesses is unlikely to be worthwhile , as in melioidosis this is likely to grow pure B . pseudomallei , although occasional dual infections ( e . g . with Staphylococcus aureus ) can occur . However , the use of ASH is more likely to be of benefit in superficial wound swabs and abscesses that have already ruptured , as these may be colonised with a range of flora that could outgrow B . pseudomallei on non-selective media , or in patients on treatment . We consider that the culture of the centrifuged deposit of a urine sample on ASH is also worthwhile in all patients suspected of having melioidosis , as in some patients this may be the only positive sample , and the number of organisms present is often well below the threshold for ‘significant bacteriuria’ with other pathogens , even in patients with prostatic involvement [6] . There are several approaches that might be used to reduce the costs associated with selective culture to detect B . pseudomallei . These include the omission of SB enrichment for some or all samples , the use of half rather than whole plates , the use of cheaper media , and the testing of only selected specimens rather than all specimens of a particular type . Several other media have been recommended for the selective isolation of B . pseudomallei from clinical samples [7 , 19–23] . Our study has focused only on the use of ASH and SB , which were the media in use in our laboratories during 2017 . Studies comparing B . pseudomallei selective media on clinical samples are relatively rare and further comparative evaluations of different formulations would be useful , although it is unlikely that any other media would be significantly cheaper than ASH and SB . One issue of particular concern is that ASH relies on gentamicin to suppress Gram negative organisms and as the prevalence of antimicrobial resistance increases it may become less effective and new formulations may become necessary [23] . The use of half plates is worthy of consideration , although this can make colonies of B . pseudomallei more difficult to pick out from other local flora . In conclusion , this analysis has caused us to review our own approach to the use of selective media for the diagnosis of melioidosis . In any patients with suspected melioidosis we recommend that , in addition to blood culture , a throat swab , or a good quality sputum sample if available , should be sent specifically for culture on ASH and in SB , and a centrifuged deposit of urine should also be cultured on ASH . In areas of high melioidosis incidence , we also recommend the use of ASH and SB for any sputum and endotracheal aspirates received from patients with pneumonia . However , we do not consider that the routine use of selective media for culture of pus samples and wound swabs is warranted unless the request form specifically requests investigation for melioidosis . Others must decide on the appropriate way to deploy selective media according to their local epidemiology , clinical practice and available resources .
|
Melioidosis is a frequently fatal disease caused by a soil bacterium called Burkholderia pseudomallei , that is widespread in the rural tropics . Because staff are often not familiar with it and because it may be hidden if it is outgrown by other bacteria , special culture media can help laboratories diagnose the disease . However , this costs more money so it is not always done even in areas where the disease is known to be present . We have looked at the results of a year’s bacterial cultures in two different laboratories in southeast Asia to identify how many patients were only identified using these special culture techniques , how much it cost , and whether the investment was considered worthwhile in terms of the gain in healthy life years in these patients who might otherwise have died had the disease not been diagnosed . Even though the laboratories adopted very different strategies for using the special media and served very different populations , in both places the use of the special techniques was very cost effective in terms not just of lives saved , but on purely financial grounds when compared with the GDP of each country .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"death",
"rates",
"medicine",
"and",
"health",
"sciences",
"body",
"fluids",
"cost-effectiveness",
"analysis",
"pathology",
"and",
"laboratory",
"medicine",
"economic",
"analysis",
"melioidosis",
"pathogens",
"geographical",
"locations",
"microbiology",
"social",
"sciences",
"throat",
"urine",
"bacterial",
"diseases",
"population",
"biology",
"bacterial",
"pathogens",
"infectious",
"diseases",
"sputum",
"mucus",
"medical",
"microbiology",
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"cambodia",
"neck"
] |
2019
|
The cost-effectiveness of the use of selective media for the diagnosis of melioidosis in different settings
|
Recombination between homologous chromosomes of different parental origin ( homologs ) is necessary for their accurate segregation during meiosis . It has been suggested that meiotic inter-homolog recombination is promoted by a barrier to inter-sister-chromatid recombination , imposed by meiosis-specific components of the chromosome axis . Consistent with this , measures of Holliday junction–containing recombination intermediates ( joint molecules [JMs] ) show a strong bias towards inter-homolog and against inter-sister JMs . However , recombination between sister chromatids also has an important role in meiosis . The genomes of diploid organisms in natural populations are highly polymorphic for insertions and deletions , and meiotic double-strand breaks ( DSBs ) that form within such polymorphic regions must be repaired by inter-sister recombination . Efforts to study inter-sister recombination during meiosis , in particular to determine recombination frequencies and mechanisms , have been constrained by the inability to monitor the products of inter-sister recombination . We present here molecular-level studies of inter-sister recombination during budding yeast meiosis . We examined events initiated by DSBs in regions that lack corresponding sequences on the homolog , and show that these DSBs are efficiently repaired by inter-sister recombination . This occurs with the same timing as inter-homolog recombination , but with reduced ( 2- to 3-fold ) yields of JMs . Loss of the meiotic-chromosome-axis-associated kinase Mek1 accelerates inter-sister DSB repair and markedly increases inter-sister JM frequencies . Furthermore , inter-sister JMs formed in mek1Δ mutants are preferentially lost , while inter-homolog JMs are maintained . These findings indicate that inter-sister recombination occurs frequently during budding yeast meiosis , with the possibility that up to one-third of all recombination events occur between sister chromatids . We suggest that a Mek1-dependent reduction in the rate of inter-sister repair , combined with the destabilization of inter-sister JMs , promotes inter-homolog recombination while retaining the capacity for inter-sister recombination when inter-homolog recombination is not possible .
During meiosis , the diploid genome is reduced to produce haploid gametes through two successive rounds of nuclear division that follow a single round of DNA replication . Homologous parental chromosomes ( homologs ) pair and separate at the first meiotic division ( MI ) , while sister chromatids segregate during the second division . Crossover ( CO ) products of inter-homolog ( IH ) recombination , combined with sister chromatid cohesion , ensure proper chromosome disjunction at MI , and a failure to properly create these connections results in aneuploid progeny . Aneuploidy caused by MI non-disjunction is a leading cause of both miscarriage and congenital birth defects [1] . Meiotic recombination is initiated by double-strand breaks ( DSBs ) formed by the Spo11 protein [2] . DSBs are resected to form single strands that are substrates for strand invasion catalyzed by the meiosis-specific Dmc1 and the ubiquitous Rad51 proteins [3] . The choice of a target for strand invasion and subsequent repair during meiosis is distinct from that during the mitotic cell cycle . During the mitotic cell cycle , there is a strong bias to repair DSBs using the sister chromatid [4] , [5] . In contrast , the homolog is often used to repair DSBs during meiosis , with two possible outcomes . After initial repair synthesis , the invading strand can detach from the homolog and reanneal with the unresected strand of the second DSB end to form a noncrossover ( NCO ) product in a process called synthesis-dependent strand annealing [6] . Alternatively , if the second end of the DSB also associates with donor sequences , Holliday junction–containing intermediates , here called joint molecules ( JMs ) , are formed [7] . In budding yeast , these are mostly resolved as COs [8] , [9] . It is generally thought that IH recombination dominates during meiosis . In budding yeast , most JMs form between parental homologs , with only 13%–25% forming between sister chromatids [7] , [10]–[12] . dmc1 mutants fail to repair DSBs and do not form JMs during meiosis , but rapidly form inter-sister ( IS ) JMs , and not IH JMs , when returned to vegetative growth [10] . In haploid yeast undergoing meiosis , a large fraction of DSBs persist unrepaired , suggesting that IS DSB repair is inefficient [13] , [14] . These findings have been taken as evidence for a meiosis-specific barrier to sister chromatid recombination ( BSCR ) that prevents IS recombination and thus promotes IH recombination . The axial element is a structure that forms between sister chromatids early in meiotic prophase . It later becomes part of the synaptonemal complex , a tripartite structure with axes of each homolog closely juxtaposed by transverse filaments [15] . In budding yeast , axial element components Red1 and Hop1 , along with the axis-associated , meiosis-specific Mre4/Mek1 kinase ( hereafter Mek1 ) , have been suggested as mediating a BSCR [16] , [17] . Recent studies indicate that meiotic DSBs activate the Mec1 and Tel1 checkpoint kinases , which phosphorylate Hop1 [17] , [18] . Phosphorylated Hop1 binds and activates the Mek1 kinase , which phosphorylates targets that include the Rad51 accessory factors Rad54 and Rdh54 [19] , [20] . This prevents interactions between these factors and Rad51 and thus is thought to decrease IS recombination . Evidence consistent with this mechanism is provided by several findings . While DSBs accumulate to normal levels in DSB processing/repair-defective mek1 rad50S double mutants [21] , [22] , mek1 single mutants display reduced steady-state DSB levels and reduced IH COs [21] , [23] , as would be expected if DSBs were rapidly repaired by IS recombination in the absence of axis-mediated signaling . Consistent with this , both red1 and mek1 mutants display a marked excess of IS JMs over IH JMs [10] , [24] . Further support for the suggestion that loss of axis signaling allows rapid IS recombination comes from findings that the DSB repair defect of dmc1 mutants is suppressed by hop1 , red1 , or mek1 loss of function mutations [10] , [17] , [19]–[21] , [25] , and that mek1 suppresses the DSB repair defect seen in haploid yeast undergoing meiosis [14] . Additionally , the meiotic repair defect of dmc1 mutants is partially suppressed by overexpression of RAD51 [26] or RAD54 [25] , and more extensively by overexpression of a RAD54 allele that lacks a Mek1 phosphorylation site [20] . These findings , while consistent with a Mek1-dependent BSCR during meiosis , were obtained under circumstances where repair and recombination are altered genome-wide . In particular , abnormally high levels of unrepaired DSBs in dmc1 mutants and in haploid cells undergoing meiosis may result in altered repair mechanisms and outcomes . For example , the resection and repair of meiotic DSBs formed by the site-specific VDE endonuclease are altered in dmc1 mutants by the presence or absence of other hyper-resected Spo11-catalyzed DSBs [27] , [28] . While it is clear that IS recombination is less prevalent during meiosis than during vegetative growth , knowledge of the relative efficiency of IH and IS recombination during meiosis remains incomplete . Previous studies have inferred the relative frequency of IS and IH repair by comparing IS- and IH-containing JM intermediates . However , no study has directly measured the efficiency of all types of IS repair in normal diploids , partly because such measurements are hampered by the inability to detect many of the products of IS recombination . To address this issue , we monitored the fate of a DSB that could only be repaired by sister chromatid recombination , in cells where all other DSBs could be repaired by IH recombination . We show here that during normal diploid meiosis , such DSBs are efficiently repaired from the sister chromatid . This IS repair has many of the features of normal IH recombination , except that fewer JM intermediates are produced . Based on these and other observations , we suggest that repair from the sister occurs frequently during budding yeast meiosis , even when the homolog is present . We propose that the apparent BSCR is actually a kinetic impediment , imposed by the Mek1 kinase , that roughly equalizes rates of IS and IH recombination during meiosis , a process that would otherwise greatly favor IS events given the spatial proximity of the sister chromatid .
We examined DSBs at two hotspots on chromosome III: within a 3 . 5-kb recombination reporter construct containing URA3 and ARG4 sequences inserted at HIS4 ( his4::URA3-arg4; [29] ) and in the YCR047c promoter ( Figure 1A ) . Both DSB hotspots were examined in a hemizygous configuration , where the hotspot was present on one copy of chromosome III and a small deletion was present on the other homolog . This eliminates the possibility of repair of the hotspot DSB by IH recombination ( Figure 1B ) , but preserves normal homolog alignment , synapsis , and IH recombination in the genome as a whole . We also examined a strain hemizygous for a deletion that removes most of the chromosome III left arm , including sequences for about 45 kb to either side of the his4::URA3-arg4 insertion site ( Figure 1B ) . In most experiments , DSB dynamics were examined in the same strain at a hemizygous site and at a homozygous control site , to control for culture-to-culture variation in meiotic progression and the fraction of cells undergoing meiosis . It has been reported that heterozygosity for a small deletion covering a DSB site causes a modest reduction in DSB levels [30] , [31] . This is not the case for the loci and deletions used here . Cumulative DSB levels at both the his4::URA3-arg4 insert and YCR047c were measured in rad50S mutants , which form , but do not repair , DSBs [32] . DSBs accumulated to similar levels in deletion hemizygotes and in homozygous controls ( Figure 1D , right-hand axes ) . In RAD50 strains , similar DSB dynamics were seen when corresponding sequences were present on or absent from the homolog ( Figures 1D and S1 ) . Calculated DSB life spans ( Figure 1E; see Materials and Methods ) at both loci were similar in the presence or absence of homology on the homolog . To confirm that the absence of corresponding homology at one DSB site did not have a chromosome-wide effect on repair , DSB levels were also examined at a DSB site ( YFL021w ) on chromosome VI . Similar noncumulative DSB curves were observed at this site and at the tester sites on chromosome III ( Figure S1D; data not shown ) . A BSCR-induced delay in DSB repair at a hemizygous site might cause a DNA-damage-response-induced delay in the MI division . We did not observe a significant difference between his4::URA3-arg4 or YCR047c hemizygotes and fully homozygous controls for meiotic division timing or for the fraction of cells that transited meiotic divisions ( Figure 2A; data not shown ) . In addition , no loss of spore viability was observed in strains hemizygous for the his4::URA3-arg4 insert ( Figure 2B ) , as might be expected if an unrepaired DSB persisted through meiotic divisions and sporulation . While these findings are consistent with efficient repair of a DSB in hemizygous sequences by IS recombination , DSB end resection past the region of heterology and subsequent strand invasion of the homolog could also result in repair , by IH gene conversion , leading to loss of the hemizygous sequences . Given DSB frequencies at his4::URA3-arg4 ( about 20% of insert-bearing chromosomes ) , DSB repair by IH gene conversion would result in 36%–40% of tetrads showing 1∶3 segregation for the insert . However , only 1% of tetrads from a his4::URA3-arg4 hemizygote showed this segregation pattern ( Figure 2B ) . In summary , all available molecular , meiotic progression , and spore survival data indicate that , when no other homologous repair partners are available at a DSB site , the sister chromatid is used as efficiently for meiotic DSB repair as would be the homolog—at least in strains where most other DSB sites are homozygous and can be repaired by IH recombination . Synthesis-dependent strand annealing , which does not involve Holliday junction–containing intermediates , is thought to be the predominant mechanism of DSB repair during the S and G2 phases of the mitotic cell cycle [5] , [33] , [34] and for NCO formation during meiosis [8] , [35] , [36] . To test the possibility that synthesis-dependent strand annealing predominates during meiotic IS DSB repair , we asked whether meiotic JMs formed at a hemizygous locus . Such JMs must be IS recombination intermediates . We found that , while DSB repair timing is unchanged , JM levels are substantially reduced during IS repair . Maximum JM frequencies at his4::URA3-arg4 were reduced 2-fold in hemizygote or left arm deletion strains relative to homozygous controls ( 1 . 2%±0 . 2% versus 2 . 4%±0 . 2%; Figure 3A ) . Similarly , JMs at YCR047c were reduced about 4-fold in YCR047c hemizygotes as compared to homozygous controls ( 0 . 5%±0 . 1% versus 2 . 0%±0 . 1%; Figure 3A ) . Reduced steady-state levels of JMs can result either from reduced JM formation or from decreased JM life span . To distinguish between these possibilities , JM levels were measured in resolution-defective ndt80Δ strains . Cumulative JM frequencies at a hemizygous his4::URA3-arg4 insert were about 2-fold lower than in homozygous controls ( 4 . 6%±0 . 5% versus 8 . 8%±0 . 6%; Figure 3B and 3C ) , where repair can occur from either the sister or the homolog . JM frequencies at YCR047c were similarly reduced in ndt80Δ hemizygotes relative to homozygous controls ( 2 . 6%±0 . 6% versus 5 . 9%±1 . 2%; Figure 3B and 3C ) . The approximately 2-fold decrease in both cumulative and steady-state JM frequencies is consistent with the suggestion that JM formation , rather than life span , is reduced during the repair of DSBs that form in a region of short insertion/deletion heterology . This , in turn , indicates that meiotic DSB repair events by IS recombination , when the sister is the only template for repair , produces a lower fraction of JMs than DSB repair when both homolog and sister are present , and the majority of JMs form between homologs . These results suggest that previous estimates of the relative levels of IS and IH recombination , which were based on JM levels [7] , [10]–[12] , may have underestimated the fraction of recombination that occurs between sister chromatids ( see Discussion ) . In contrast , ndt80Δ strains hemizygous for the 90-kb left arm deletion accumulated JMs at his4::URA3-arg4 in two phases . At earlier times ( up to 4 . 5 h , when JMs begin to disappear with wild-type ) , JMs were present at frequencies similar to those in strains with the much shorter his4::URA3-arg4 heterology . At later time points , JMs accumulated much more rapidly , reaching JM levels seen in homozygous control strains ( Figure 3C ) . These results suggest that the outcome of IS recombination can be influenced by IH interactions in flanking chromosomal regions ( see Discussion ) . Several meiosis-specific proteins , collectively called the ZMM proteins , are required for wild-type levels of JMs and COs and normal synaptonemal complex formation , but not for normal NCO levels [37]–[39] . Two of these , Msh4 and Msh5 , form a heterodimer that is thought to promote JM formation by stabilizing early recombination intermediates [37] , [40] , [41] . IS and IH JM formation are reduced in msh5 strains [11] , [38] , but it has not been determined whether IH and IS JMs are equally affected . We therefore measured cumulative JM levels in msh4Δ ndt80Δ strains that were hemizygous or homozygous for the his4::URA3-arg4 insert . A 3-fold decrease in both IS and total JM frequencies was observed in both the hemizygous and homozygous msh4Δ ndt80Δ strains ( Figure 3D ) . Assuming that the majority of JMs in homozygous msh4Δ ndt80Δ strains are IH JMs , it can be concluded that IS and IH JMs are similarly MSH4-dependent . DSBs form at normal levels but are more rapidly repaired in strains lacking Mek1 kinase activity , as compared to wild-type [17] , [19] , [21]–[23] , [42] . A similar decrease in DSB life span is seen in cells with an unphosphorylatable Hop1 protein that does not activate the Mek1 kinase [18] . Because mek1 strains also show greatly reduced IH recombination [21] , [23] , [42] , [43] , it has been suggested that , in the absence of Mek1 activity , meiotic DSBs are rapidly repaired by IS recombination . We confirmed that , in mek1Δ strains , steady-state DSB levels are substantially reduced at a hemizygous his4::URA3-arg4 insert and at a homozygous YCR047c site , while cumulative DSB levels , measured in rad50S strains , are not affected ( Figure 4A ) . Thus , DSB life spans are substantially reduced in mek1Δ relative to wild-type ( by about 3-fold; data not shown ) . Because DSBs in hemizygous loci are repaired by IS recombination , this indicates that loss of Mek1 increases the rate of IS recombination by about a factor of three . In addition to accelerating IS recombination , loss of Mek1 alters the fraction of IS events that form JMs . In contrast to the 2-fold reduction in IS JMs observed at hemizygous loci in MEK1 ndt80Δ strains , IS JM levels at hemizygous loci in mek1Δ ndt80Δ strains were similar to those observed for homozygous loci in MEK1 ndt80Δ strains , where most JMs are IH ( Figure 4B , left panel ) . Thus , the Mek1 kinase decreases the rate and alters the outcome of IS recombination . In contrast , steady-state JM levels in mek1Δ NDT80 cells are about 2- to 2 . 5-fold reduced , relative to wild-type , at both hemizygous and homozygous loci ( Figure 4C ) . Since cumulative JM levels are unreduced in mek1Δ ndt80Δ cells , this indicates that JM life spans are shortened in mek1Δ . This may be due to accelerated meiotic progression caused by the early loss of DSB signal , since mek1Δ cells undergo the first meiotic nuclear division about 40 min earlier than do MEK1 cells ( Figure 4D; [42] ) , as do DSB-defective mutants [42] , [44]–[46] . This early MI division most likely results from early activation of the NDT80 transcriptional program [46] , which is also responsible for JM resolution [8] , [47] . Ndt80 is a target of the meiotic DNA damage response [48] , and reduced steady-state DSB levels in mek1Δ may , in turn , lead to reduced DNA damage signaling and thus premature activation of Ndt80 . IH recombination levels are markedly reduced in mek1 mutants [21] , [23] , [42] , [43] , suggesting that even when IH recombination is possible , IS repair predominates in mek1Δ mutants . To confirm this , we examined ndt80Δ strains where JMs formed by IS and IH recombination in the URA3-arg4 interval can be distinguished ( Figure 5A; [29] ) . In MEK1 ndt80Δ strains , the majority of JMs at this locus ( ∼80% ) formed between homologs , and the IH/IS JM ratio was relatively invariant over time ( Figure 5D and 5E; [12] , [47] ) . In mek1Δ ndt80Δ , JMs accumulated to levels approaching those seen in MEK1 ndt80Δ , but most of the JMs initially formed in mek1Δ ndt80Δ were between sister chromatids ( IS/IH JM ratio of ∼8∶1 for the time interval 3–5 h after transfer to sporulation medium; Figure 5B–5E ) . With continued incubation in the ndt80Δ-arrested state ( 6 h and later ) , IS JM levels decreased and IH JM levels increased . IH JMs roughly equaled IS JMs by 10–12 h after transfer to sporulation medium and became the majority class by 13 h ( Figure 5B and 5C ) , although maximum IH JM frequencies ( 2%–2 . 5% ) were much less than those seen in ndt80Δ MEK1 ( 6%–7% ) . Thus , in contrast to what is observed in the presence of Mek1 , IS recombination predominates during initial JM formation in the absence of Mek1 , a finding also reported by Kim and coworkers [24] . In addition , the differential loss of IS JMs at later times is consistent with the suggestion that IS JMs are less stable than are IH JMs [11] , [12] , [49] , [50] . Thus , while Mek1 plays a major role in regulating IS recombination during meiosis , other activities impact the outcome of IS recombination in the absence of Mek1 .
Most studies of meiotic recombination have focused on recombination between homologs , and less attention has been given to the potentially critical role for recombination between sister chromatids . For example , a substantial fraction of variation among human haplotypes consists of insertion/deletion polymorphisms that are greater than 500 nucleotides in length [51] , [52] . One way to ensure the timely repair of DSBs that form in regions of heterozygosity for such insertion/deletions would be to have both the homolog and sister chromatid available as potential partners . Our genetic and molecular data indicate that the sister chromatid can be used as efficiently as the homolog in the repair of meiotic DSBs . DSBs that form at hemizygous loci are repaired with the same efficiency and timing as DSBs formed at homozygous loci ( Figures 1 and 6A ) . While these DSBs could , in theory , be repaired by IH gene conversion of the entire region of heterology , such events are relatively rare ( Figure 2 ) . We therefore conclude that the majority of DSBs that form at hemizygous loci are repaired by recombination between sister chromatids . Furthermore , the efficient repair of DSBs that form opposite deletions of an entire chromosome arm ( Figure 1 ) indicates that nearby IH interactions are not required for IS recombination to occur . While repair in hemizygous strains occurs exclusively from the sister chromatid , Hunter and colleagues have suggested that multiple templates , including the sister chromatid , are frequently used in the repair of DSBs when both parental homologs are present [11] . JMs containing three and four chromatids form in wild-type cells , and are abundant in strains lacking the Sgs1 helicase [11] . This supports the suggestions that multiple repair templates are often used during meiotic recombination , that recombination is a dynamic process , and that Sgs1 acts to prevent aberrant structures that are formed as a result of these processes [11] , [50] . The increased incidence of IS JMs in strains lacking Sgs1 further supports the claim that the sister chromatid is often used for DSB repair during meiosis [11] , [12] , [49] . The timely and efficient repair of DSBs at hemizygous loci contrasts with the pronounced DSB persistence and repair failure observed in haploid meiosis [13] , [14] or in the absence of Dmc1 [53] . Efficient IS DSB repair is restored in dmc1 diploids and haploid yeast when axis-dependent , DSB-dependent signaling through Mek1 is blocked [14] , [17] , [18] , [21] , and this has been taken as evidence for a Mek1-dependent barrier that prevents most DSBs from being repaired by IS recombination . Our finding and previous findings that IS and IH JMs appear with similar relative timing in budding yeast [10] , [11] , [38] are inconsistent with suggestions that most IS recombination occurs upon synaptic adjustment or axis breakdown late in meiosis I prophase . Rather , we suggest that IS recombination occurs with timing and frequencies similar to those of IH recombination . Our data suggest that in normal diploid meiosis , the constraint on IS strand invasion about equals the constraint on IH repair imposed by the need to search through the nucleus to find the homolog . Such an equalizing force would allow for the establishment of IH connections , while maintaining the ability to properly repair DSBs incurred in regions of heterozygosity . Possible explanations for why DSBs persist during meiosis in haploids and in dmc1 mutants will be discussed below . JM production at hemizygous loci is reduced 2- to 3-fold relative to total JM production when the same loci are homozygous ( Figure 4 ) . Since most JMs resolve as COs during meiosis [47] , this would suggest that CO recombination is less prevalent , and NCO recombination is more prevalent , during IS recombination than during IH recombination . If this is true , then previous estimates of IS and IH recombination levels , based on the relative levels of IH and IS JMs [10]–[12] , [38] , would substantially underestimate the fraction of events that involve IS recombination ( Figure 6B ) . In estimating the total fraction of events that involve IS recombination , we consider that IH COs and NCOs are produced in roughly equal numbers at his4::URA3-arg4 [29] . Since most COs are produced by JM resolution [8] , [47] , about one-half of all IH events at this locus involve JM formation . Since IS JMs levels at hemizygous loci are 2- to 3-fold lower ( Figure 4 ) , JMs constitute between one-sixth and one-quarter of IS recombination events at the hemizygous locus . If the same ratio holds for the IS recombination at homozygous loci , then previously reported IH/IS JM ratio ( between 1∶2 . 5 and 1∶7; [24] can be used to estimate the fraction of IS events that involve NCO recombination , and thus are not detected ( Figure 6B; Protocol S1 ) . Using a consensus IH/IS JM ratio of 1∶5 , the calculated ratio of IS/IH recombination is between 1∶1 . 7 ( if IS JMs are reduced 3-fold relative to IH JMs ) and 1∶2 . 5 ( if IS JMs are reduced 2-fold ) . Thus , if our findings regarding IS recombination at hemizygous loci hold for IS recombination at homozygous loci , roughly one-third of meiotic DSBs may be repaired by IS recombination in budding yeast , a fraction expected on the basis of target copy number alone . It should be noted that this analysis assumes that the outcome of IS recombination is the same regardless of the presence or absence of corresponding sequences on the homolog , a fact that remains to be determined . In addition , the calculated value of one-third is highly dependent on the actual IS/IH ratio of JMs formed during meiosis . While a consensus value of 1∶5 was used in this calculation , large variation in this value has been reported [10]–[12] , [24] . Such variation would change estimates of the fraction of breaks repaired by the sister , accordingly ( see Protocol S1 ) . A true test of the predicted frequency of IS repair will require an accurate inventory of DSBs , COs , and NCOs at multiple individual loci , as well as genome-wide . Despite the general impression that IH recombination predominates during meiosis , existing data indicate that IS recombination may be prevalent in other organisms . High levels of IS recombination have been documented at the fission yeast mbs1 locus , where about 80% of meiotic JMs detected are between sister chromatids [54] , and where DSBs are efficiently repaired during haploid meiosis [55] . About 20% of all COs detected by BrdU/FPG staining of locust spermatocytes are IS [56] . During mammalian meiosis , Rad51/Dmc1 foci ( thought to mark DSBs ) outnumber Mlh1 foci ( thought to mark COs ) by about 10- to 20-fold [57] , [58] , but sperm-typing studies measure NCO/CO ratios in the range of 3∶1 to 9∶1 [59]–[61] . While this may reflect a systematic underscoring of NCO events , it is also possible that a substantial fraction of meiotic DSB repair in mammals might occur by IS recombination . While previous studies have implicated the Mek1 kinase in reducing the frequency of IS events , our data provide the first quantitative measure , to our knowledge , of the extent to which Mek1 activity impairs IS recombination . DSB life spans at a hemizygous his4::URA3-arg4 locus are reduced 3-fold in mek1Δ mutants relative to MEK1 ( Figure 4 ) . This would suggest that Mek1 imposes a 3-fold reduction in the rate of IS repair . Our observation of similar rates of DSB repair at hemizygous and homozygous loci ( Figure 1 ) suggests that Mek1 reduces the rate of IS strand invasion to the point where it is similar to the overall rate of strand invasion of the homolog , a process where the homology search is probably the rate-limiting step [62] , [63] . It is of interest to note in this context that the rad52-Y66A allele , which substantially slows mitotic DNA damage repair , substantially increases the frequency of mitotic IH recombination [64] . In MEK1 ndt80Δ strains , IS JMs at hemizygous loci are reduced 2- to 3-fold relative to JMs formed when both homologs are present , but no such reduction is seen in mek1Δ ndt80Δ ( Figure 4 ) . This Mek1-dependent reduction in JM formation may simply be due to Mek1's effect on IS strand invasion . If Mek1 impairs strand invasion , such activity could substantially reduce JM production , since the formation of such intermediates requires two separate strand invasion events . Alternatively , it may reflect interference caused by nearby events that form IH JMs . If interference acts both on events that form IH JMs and on events that form IS JMs , the lack of IH JMs in mek1Δ would lead to elevated IS JM production . Consistent with this latter suggestion , elevated IS JM levels are also seen at later times in MEK1 ndt80Δ strains where his4::URA3-arg4 is opposite a 90-kb deletion on the chromosome III left arm , precluding the possibility of nearby IH events ( Figure 4 ) . Further studies are needed to test this possibility . We have shown here that the presence of the Mek1 kinase imposes a kinetic constraint on IS recombination . Slowing this process , which otherwise would be rapid because of the close proximity of the sister chromatid , allows time for the genome-wide homology search needed for DSBs to engage in IH recombination , while retaining the ability to efficiently repair DSBs if homology is not encountered . Thus , the extent of reduction in IS recombination would be expected to vary among organisms , depending upon the nature of the search necessary for IH recombination . IS recombination might be minimally constrained in Schizosaccharomyces pombe , where homologs are extensively co-localized and co-aligned at the time of DSB formation [55] , [65] , while substantial kinetic constraints might be imposed in organisms with large and complex genomes . If a kinetic constraint on strand invasion is to have a differential effect on IS and IH recombination , additional specificity must be involved . One way to accomplish this would be to target proteins specialized for IS recombination , as has been suggested for the Rad51/Rad54 combination [66] . However , this suggestion is challenged by the observation that increasing Rad51 protein levels or activity can partially suppress the IH recombination defect of yeast dmc1 mutants [20] , [25] , [26] , [67] , [68] , and by the existence of organisms where Rad51 is the sole source of meiotic strand transfer activity [69]–[72] . The existence of documented anti-recombination activities conferred by the Hed1 protein and by the Mek1-dependent phosphorylation of Rad54 and Rdh54 [20] , [68] , [73] supports the idea that strand invasion activities are constrained . However , for such anti-recombination activities to be specific to the sister , Mek1-mediated anti-recombination activity must be spatially restricted to chromosomal regions near DSBs , thus locally inhibiting sister chromatid recombination while allowing unconstrained DSB end-invasion of the homolog ( Figure 6C; [19] , [50] ) . This suggestion is based on the observation that DSB-induced , Mec1/Tel1 chromatin modification occurs primarily in a gradient within a 50- to 100-kb region around the break [74] , and on the hypothesis that activated Mek1 kinase has a relatively short half-life . This idea of a spatially confined Mek1 activity is distinct from what is observed for activated Rad53 , whose release from Rad9 leads to amplification of the checkpoint signal throughout the cell [75] . Under normal circumstances , when DSBs are being formed and repaired asynchronously [76] , a Mek1-dependent zone of recombination inhibition will primarily involve the broken chromosome and its sister chromatid , leading to a differential slowing of IS recombination . However , under conditions where DSB repair is delayed ( such as in dmc1 mutants , or when all homologs are absent ) , there is the possibility that increased overall levels of single-stranded DNA will lead to elevated Mec1/Tel1 signaling and consequent hyperactivation of Mek1 , thus transforming a localized kinetic constraint into the observed genome-wide inhibition of recombination . Experiments to test this suggestion are ongoing . Once established , IH connections must be maintained , so that they can be resolved as the COs necessary for proper homolog segregation at the first meiotic division . Our data are also consistent with suggestions that differential stabilization of IH JMs may contribute to their preponderance over IS JMs [50] . mek1Δ ndt80Δ strains display an excess of IS JMs at early time points ( Figure 5 ) , but over time IS JMs decrease and IH JMs increase , suggesting that IH JMs are preferentially stabilized , IS JMs are preferentially destabilized , or both . Our current data do not distinguish between these alternatives , and do not address the issue of whether or not similar mechanisms operate in MEK1 cells , where the Sgs1 helicase has been implicated in reducing formation of JMs that contain IS interactions in wild-type [11] , [37] . It will be of considerable interest to examine the impact of Sgs1 on JM formation at hemizygous loci , and examine the possible role of Mek1-mediated phosphorylation in recruiting potential JM-destabilizing activities .
All yeast strains are derived from SK1 [77] . See Protocol S1 and Table S1 for genotypes and construction . The 3 . 5-kb URA3-arg4 insert has been previously described [29] . The chromosome III left arm deletion replaces 90 kb between YCL069w and YCL004w with the 1 . 5-kb hygromycin resistance cassette hphMX4 [78] . The YCR047c deletion replaces 4 kb between YCR046c and the middle of YCR051w with hphMX4 . Sporulation in liquid , DNA extraction , and recombination product and intermediate analysis were as described previously [37] , [79] , [80] with modifications . DSB life span and cumulative curves for DSB formation and repair were calculated as described previously [81] . Nuclear divisions were monitored by DAPI staining . Details are in Protocol S1 .
|
In diploid organisms , which contain two parental sets of chromosomes , double-stranded breaks in DNA can be repaired by recombination , either with a copy of the chromosome produced by replication ( the sister chromatid ) , or with either chromatid of the other parental chromosome ( the homolog ) . During meiosis , recombination with the homolog ensures faithful segregation of chromosomes to gametes ( sperm or egg ) . It has been suggested that use of the spatially distant homolog , as opposed to the nearby sister chromatid , results from a meiosis-specific barrier to recombination between sister chromatids . However , there are situations where meiotic recombination must occur between sister chromatids , such as when recombination initiates in sequences that are absent from the homolog . By studying such a situation , we show that meiotic recombination with the sister chromatid occurs with similar timing and efficiency as recombination with the homolog . Further analysis indicates that inter-sister recombination is more common than was previously thought , although still far less prevalent than in somatic cells , where inter-sister recombination predominates . We suggest that meiosis-specific factors act to roughly equalize repair from the sister and homolog , which both allows the establishment of physical connections between homologs and ensures timely repair of breaks incurred in regions lacking corresponding sequences on the homolog .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology/germ",
"cells",
"cell",
"biology/nuclear",
"structure",
"and",
"function",
"genetics",
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"genomics/nuclear",
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"and",
"function",
"genetics",
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"genomics/chromosome",
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"repair"
] |
2010
|
Frequent and Efficient Use of the Sister Chromatid for DNA Double-Strand Break Repair during Budding Yeast Meiosis
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Melioidosis is a severe bacterial infection caused by Burkholderia pseudomallei with a high case-fatality rate . Epidemiological and animal studies show the possibility of inhalation transmission . However , no B . pseudomallei concentrations in ambient air have been researched . Here , we developed a method to quantify ambient B . pseudomallei and then measured concentrations of ambient B . pseudomallei during the typhoon season and the non-typhoon season to determine the factors influencing ambient B . pseudomallei levels . We quantified ambient B . pseudomallei by using a filter/real-time qPCR method in the Zoynan Region in Kaohsiung , southern Taiwan . Twenty-four hour samples were collected at a sampling rate of 20 L/min every day from June 11 to December 21 , 2012 including during the typhoon season ( June to September ) and reference season ( October to December ) . We successfully developed a filtration/real-time qPCR method to quantify ambient B . pseudomallei . To our knowledge , this is the first report describing concentrations of ambient B . pseudomallei . Ambient B . pseudomallei were only detected during the typhoon season when compared to the reference season . For the typhoons affecting the Zoynan Region , the positive rates of ambient B . pseudomallei were very high at 80% to 100% . During June to December , rainfall was positively correlated with ambient B . pseudomallei with a statistical significance . Sediment at a nearby pond significantly influenced the concentration of ambient B . pseudomallei . During the typhoon month , the typhoon was positively correlated with ambient B . pseudomallei whereas wind speed was reversely correlated with ambient B . pseudomallei . Our data suggest the possibility of transmission of B . pseudomallei via inhalation during the typhoon season .
Melioidosis , which is endemic in northern Australia and Southeast Asia , is an emerging infection in other Asian regions and in South America [1]–[6] . Sporadic autochthonous cases have also been reported throughout the world , including Africa , the Caribbean , America , and the Middle East [1] , [7]–[8] . Melioidosis is a severe bacterial infection caused by Burkholderia pseudomallei with high case-fatality rates of 14% to 40% in Thailand , Australia , Singapore and Taiwan [1] , [6] , [9]–[11] . With increasing worldwide travel of both humans and animals , and the concern of B . pseudomallei as an important potential bioweapon , this agent is an emerging global public health problem [1]–[3] , [7] , [10] , [12] . Risk factors of melioidosis are diabetes , hazardous alcohol use , chronic lung or renal disease , and older age [1] , [10] , [13] . Pneumonia is the most common clinical presentation [1] , [5] , [10] , [14]–[15] . The association between melioidosis and rainfall intensity is well documented from endemic regions [5]–[6] , [10] , [13]–[14] . A significant linear correlation has been observed between rainfall and melioidosis cases [1] , [5]–[6] , [13] , [15]–[16] . The case clusters were also associated with sudden and heavy rainfall related to cyclones and typhoons [1] , [4] , [6] , [10] , [14]–[18] . Although outbreaks have been linked to contamination of drinking water [1] , it is now believed that percutaneous inoculation is the major mode of acquisition [1] , [19]–[21] . Recently , epidemiological studies support inhalation as the mode of transmission of B . pseudomallei after heavy monsoonal rains and winds [5] , [6] , [10] , [12]–[13] , [17] , [21]–[22] . Animal studies also show that exhaled B . pseudomallei aerosols lead to a lower lethal dose , 50% ( LD50 ) and a shorter incubation time compared to intraperitoneal and subcutaneous injection [23]– . However , no B . pseudomallei concentrations in ambient air have been researched . There are very limited researches regarding quantifying ambient pathogens . The first study of quantifying airborne pathogens by using filter/real-time qPCR was to determine the concentrations of airborne M . tuberculosis in hospitals [25]–[26] . Then , airborne influenza virus and avian influenza virus was also quantified in poultry markets [27] . Recently , the first report describing the concentration of ambient pathogens implied the possibility of long-range transport of influenza virus because the concentration of ambient influenza A virus was significantly higher during the Asian dust storm days than during the background days [28] . This quantitative method shows promise for quantifying ambient pathogens with high sensitivity and specificity and should provide deeper insight into infectious disease transmissibility and epidemiology , as well as infection control . Therefore , the aim of the current study was to develop a method to quantify ambient B . pseudomallei and to determine the factors influencing ambient B . pseudomallei levels .
Reference strains of B . pseudomallei ( vgh19 ) were kindly provided by the laboratory for Biotechnology , National Kaohsiung Normal University ( Kaohsiung , Taiwan ) ; their characteristics have been described in previous studies [29] . We target the B . pseudomallei – specific type III secretion system ( TTSS ) gene cluster encompassing part of open reading frame 2 ( orf2 ) [30] , which was recently reported to be the most accurate clinically and has shown sensitivity beyond culture on soil samples for B . pseudomallei detection [31] . The target DNA standard solution of B . pseudomallei was purchased from Mission Biotech ( Taipei , Taiwan ) . We extracted genomic DNA from B . pseudomallei with the QIAamp DNA Mini kits ( QIAGEN , GmbH , Hilden , Germany ) as previously described [26] . The bacterial DNA was stored at −20°C within one month before the analysis . For B . pseudomallei , the primers and probe were primarily targeted to TTSS-orf2 with the sensitivity and specificity of 100% for B . pseudomallei [30] . The sequence of primers were BpTT4176F ( 5′-CGTCTCTATACTGTCGAGCAATCG-3′ ) , BpTT4290R ( 5′-CGTGCACACCGGTCAGTATC-3′ ) , and the probe was fluorogenic probe BpTT4208P ( 5′-CCGGAATCTGGATCACCACCACTTTCC-3′ ) . The PCR assay was performed at a final volume of 25 µl and 45 cycles as previously described [32] and amplification and detection were performed on the 7900HT Fast Real-Time qPCR System ( Applied Biosystems , Inc . , Foster City , CA ) . Ten-fold serial dilutions of the target DNA standard solution was made for the calibration curve . In order to achieve PCR efficiency of 90% to 110% , the slope of the calibration curve must range from −3 . 6 to −3 . 1 . The R2-value must be above 0 . 99 . The positive and negative controls were analyzed with each run . The negative controls were all uncontaminated . All samples , positive controls and negative controls were analyzed in triplicate . Statistical analyses were performed using SPSS for Windows Chinese Traditional 14 . 0 . The descriptive statistics were used to evaluate the range , mean and standard error of parameters . The Mann-Whitney U test was used to evaluate the difference of ambient B . pseudomallei and environmental factors between different groups . Since the distribution of ambient B . pseudomallei did not fit to normal distribution ( significant result was found in Kolmogorov-Smironov test ) , we used Spearman correlation to evaluate relationships between B . pseudomallei and meteorological factors . Significance was accepted at p-value<0 . 05 .
Figure 1 shows the calibration curve of B . pseudomallei from 1 . 0×100 to 1 . 0×107 copies/µl with R2 of 0 . 998 and slope of −3 . 46 . Because the DNA on each filter was extracted to a final volume of 200 µl , the detection limit of the filter/real-time qPCR method for B . pseudomallei was 6 . 94 copies/m3 . If the positive results were found in the 1/100 dilution samples due to the inhibitory effect , then the actual detection limit corrected for this effect was 0 . 07 copies/m3 . Based on our results , 1 copy/µl in the real-time qPCR assay was approximately equal to 5 . 5 CFU/µl . Figure 2 ( a ) shows the B . pseudomallei concentrations on Teflon and PC filters over 24 hours and 48 hours of sampling after spiking the same quantity of B . pseudomallei . The concentrations of B . pseudomallei on Teflon filters of both 24-hour and 48-hour samples were significantly higher than that on PC filters . So , we evaluated the influence of transport temperature on Teflon filters . Figure 2 ( b ) shows B . pseudomallei concentrations with the transport temperature at 4°C and 25°C over 24 hours and 48 hours for the spiked samples on Teflon filters . The concentrations of B . pseudomallei at 4°C for both 24-hour and 48-hour samples were significantly higher than that at 25°C . For inhibitory effect evaluation , our results show that the extracted DNA of B . pseudomallei on filters containing ambient aerosols ( 9 . 2×101 copies/µl ) were significantly lower than that on blank filters ( 2 . 1×102 copies/µl ) after spiking same quantity of B . pseudomallei ( p-value = 0 . 01 ) . We measured ambient B . pseudomallei from June 11 to December 31 , with a total of 188 samples ( we lost six samples from June 28 to June 30 and August 23 to 26 ) . The positive rate by qPCR ( the number of positive samples divided by the number of all samples ) is 20 . 2% with the concentration range from not detected to 4×104 copies/m3 . According to Taiwan Central Weather Bureau , seven typhoons affected Taiwan in 2012 with the definition of “affected periods” as the period of issuing a sea alert to the typhoon [33] . Table 1 shows the information of the seven typhoons as well as ambient B . pseudomallei and environmental characteristics during the typhoon-affected periods . The positive rate during Kai-Tak and Tembin affected periods was higher than that of other typhoons . The path of Talim , Doksuri , Haikui , Kai-Tak , and Jelawat were far away from Taiwan , whereas Saola and Tembin landed Hualien ( East Taiwan ) , and Pingtung ( South Taiwan ) , respectively ( Figure 3 ) . Only Doksuri , Kai-Tak , and Tembin affected the southern part of Taiwan where we sampled ambient B . pseudomallei . Table 2 shows the descriptive statistics for ambient B . pseudomallei and environmental factors during the typhoon season and reference season . Our results show that ambient B . pseudomallei , rainfall , wind , and UV during typhoon season were higher than that during reference season with a significant difference ( p-value<0 . 05 ) . However , the concentrations of ambient fungi , O3 , SO2 , CO , and NOx were significantly higher during the reference season than typhoon season . Table 3 shows the descriptive statistics for ambient B . pseudomallei and environmental factors in June , July , August and September , separately . Figure 4 shows the ambient B . pseudomallei concentration profile from June to September . During June to December , the concentrations of ambient B . pseudomallei were positively associated with rainfall and UV of lag 0 , lag 1 , lag 2 , 2-day sum , 3-day sum , and 4-day sum ( Table 4 ) . However , no significant correlation was observed between ambient B . pseudomallei and environmental parameters during typhoon season . In August , there were four typhoons affecting Taiwan; therefore , we defined August as “typhoon month . ” During typhoon month , the concentrations of ambient B . pseudomallei were negatively associated with wind speed at lag 0 , 2-day sum , and 3-day sum with marginal p- values of 0 . 079 , 0 . 093 and 0 . 080 , respectively . When we divide environmental parameters by the mean and median values of samples , we found that ambient B . pseudomallei of rainy days ( >median value of 0 mm ) was significantly higher than that of no rainfall days with p-value of 0 . 006 during June to December ( Table 5 ) . During typhoon month , ambient B . pseudomallei of high-wind-speed days divided by mean value ( 2 . 4 m/s ) were significantly lower than that of low-wind-speed days .
In this study , we developed a filtration/real-time qPCR method to quantify ambient B . pseudomallei with a wide dynamic range over 8 orders of magnitude and a correlation coefficient ( r ) value of 0 . 998 . The detection limit was 6 . 94 copy/m3 , which is much lower than that in the previous studies for airborne M . tuberculosis ( 583 copy/m3 ) and airborne influenza A , B , and A/H5 virus ( 886 , 653 and 1236 copy/m3 , respectively ) [26]–[27] . The low detection limit and wide linear range demonstrate that this newly established method is a promising tool for deeper insight into transmissibility and epidemiology of melioidosis , as well as infection control . In our laboratory evaluation , Teflon filters show better performance when compared to PC filters . Teflon filters were also used for measuring airborne influenza virus in poultry markets and ambient influenza virus [27]–[28] . Our results showed that samples transported at 4°C were superior to 25°C . Inhibitory effects were also observed . In a previous study , authors found that air samples containing bacteria and fungi may inhibit PCR amplification and dilution of these samples can resolve these problems [34] . Therefore , optimistic protocols for ambient B . pseudomallei quantification in our follow-up field evaluations used Teflon filters to sample ambient B . pseudomallei , transported samples at 4°C to our laboratory within one hour , and analyzed samples simultaneously using 1 , 1/10 and 1/100 dilutions . Melioidosis is a severe bacterial infection with high case-fatality rates of approximately 40% in Thailand , 30% to 14% in Australia , 40% in Singapore , and 22 . 7% in Taiwan [1] , [6] , [9]–[11] . It is now believed that percutaneous inoculation is the major mode of acquisition due to exposure history to polluted water and mud , high risk among farmers , and wide isolation of B . pseudomallei from soil , mud , and pooled surface water in endemic areas [1] , [19] . However , pneumonia was the most common clinical presentation , which accounted for 32 . 6% , 51% , 45% , 42 . 1% and 70% of cases in India [5] , northern Australia [10] , Thailand [1] , Malaysia [15] , and Taiwan [14] , respectively . In addition , epidemiological studies hypothesized that inhalation of B . pseudomallei was the mode of transmission after heavy monsoonal rains and winds [5] , [6] , [10] , [13] , [17] , [20]–[22] . In this study , we successfully quantified ambient B . pseudomallei using filtration/real-time qPCR . To our knowledge , this is the first report describing concentrations of B . pseudomallei in ambient air . Our results provided evidence to support the hypothesis from these epidemiological studies of inhalation transmission . B . pseudomallei is widely isolated from soil and water samples [35]–[38] . In Taiwan , there was a cluster of melioidosis for both cases and deaths in the Zoynan Region [11] . B . pseudomallei was isolated from this region at a rate of 25 . 9% and 13 . 5% for soil samples and water samples , respectively [11] . Our results of 20 . 2% positive air samples was similar to that of water and soil samples and implicated that ambient B . pseudomallei should be a concern as an important source of transmission . In 2012 , seven typhoons affected Taiwan whereas only three typhoons ( Doksuri , Kai-Tak , and Tembin ) affected Zoynan Region . We lost the ambient B . pseudomallei samples during Doksuri-affected periods due to communication mistakes with the personnel managing the sampling site . For the other two typhoons affecting the Zoynan Region , the positive rates of ambient B . pseudomallei were very high at 100% and 80% for Kai-Tak and Tembin , respectively . In addition , ambient B . pseudomallei were only detected during the typhoon season when comparing to the reference season . Our results support the hypothesis that heavy monsoonal rains and winds may cause a shift toward inhalation of B . pseudomallei [13] and provide a possible explanation for the observed growth in the number of melioidosis cases in the Taiwan Zoynan Region from the 2005 and 2009 typhoon season [16] , [20] . Regarding air pollutants , the significantly higher concentrations of ambient fungi , O3 , SO2 , CO and NO were observed during the reference season when compared to the typhoon season . Pollutants concentrated in autumn due to high atmospheric pressure may provide the explanation [39] . When investigating ambient B . pseudomallei in June , July , August and September separately , we found that although the highest positive rate was observed in August , the highest concentrations were all observed in July with the lowest rainfall among June to September ( Table 3 , Figure 4 ) . This observation is contrary to the results in the previous studies [5]–[6] , [10] , [13]–[14] . During our sampling period , we found that the water of the Lotus Pond was pumped out on June 27 to let sediment expose to the air . The authority ( Department of Health , Kaohsiung city government ) did confirm that water was pumped out on June 27 prior to the typhoon to avoid waterlogging . Since we lost samples from June 28 to June 30 , we compared the concentration of June and July to see the association between ambient B . pseudomallei and the appearance of sediment . The concentration of ambient B . pseudomallei in July was higher than that in June with a marginal p-value of 0 . 052 . For evaluating the association between the appearance of sediment and ambient B . pseudomallei from June to September , the linear-by-linear association test was used after logarithmic transformation of ambient B . pseudomallei . We defined log ( ambient B . pseudomallei +1 ) as the dependent variable ( Y ) and the time period after the appearance of sediment was grouped by two weeks as X = 6 , 5 , 4 , 3 , 2 , 1 for data between July 1 to July 15 , July 16 to July 31 , August 1 to August 15 , August 16 to August 31 , September 1 to September 15 , September 16 to September 30 , respectively , where the data before the appearance of sediment was defined as X = 0 . The sediment “event” was significantly associated with ambient B . pseudomallei with the predicted model as Y = 0 . 459+0 . 123× ( p-value 0 . 024 ) . Our results show that the appearance of sediment at a nearby pond may be the source of ambient B . pseudomallei during the typhoon season . The association between melioidosis and rainfall intensity is well documented from endemic regions , with 75% , 72% , 80% , 81% and 85% of cases presenting during the wet season in northeast Thailand [6] , India [5] , Taiwan [14] , northern Australia [10] and northern Australia [13] , respectively . In regard to the associations between ambient B . pseudomallei and environmental parameters , we found that rainfall was positively correlated to ambient B . pseudomallei during June to December . This is consistent with the previous observation of significantly linear correlation between melioidosis cases and rainfall [5]–[6] , [13] , [15]–[16] . However , no significant correlation was observed between ambient B . pseudomallei and rainfall during the typhoon season and typhoon month . This may be due to the appearance of sediment strongly affecting the concentration of ambient B . pseudomallei . We defined August as “typhoon month” to investigate the association between ambient B . pseudomallei and environmental parameters due to four typhoons affecting Taiwan in August , and less effect of sediment appearance in August when compared to July . We defined log ( ambient B . pseudomallei +1 ) as the dependent variable ( Y ) . Rainfall , wind speed and typhoon were defined as independent variables . We found that typhoon and wind speed were significantly associated with ambient B . pseudomallei with the predicted model as Y = 1 . 350-0 . 272 ( wind speed ) ( p-value 0 . 039 ) +0 . 713 ( typhoon ) ( p-value 0 . 046 ) with a p-value of 0 . 049 for the whole model . We found that typhoon was positively correlated with ambient B . pseudomallei . This supports conclusions from previous studies that the case clusters were associated with sudden and heavy rainfall related to cyclones and typhoons [1] , [4] , [6] , [10] , [14]–[18] , [22] . Wind speed was reversely correlated with ambient B . pseudomallei . This may be due to dilution of ambient B . pseudomallei by wind . In conclusion , we successfully developed a filtration/real-time qPCR method to quantify ambient B . pseudomallei . To our knowledge , this is the first report describing concentrations of ambient B . pseudomallei . Our results provided evidence to support the hypothesis that heavy monsoonal rains and winds may cause a shift toward inhalation of B . pseudomallei . Ambient B . pseudomallei should be concerned as an important source of transmission due to the wind speed during the typhoon season . Ambient B . pseudomallei should be taken seriously as a surveillance target in endemic areas of Melioidosis especially during typhoon season .
|
Melioidosis is a severe bacterial infection caused by Burkholderia pseudomallei with a high case-fatality rate . Epidemiological and animal studies show the possibility of inhalation transmission . However , no B . pseudomallei concentrations in ambient air have been researched . Here , we successfully developed a method to quantify ambient B . pseudomallei by using a filter/real-time qPCR method . Twenty-four hour samples were collected every day from June 11 to December 21 , 2012 including during the typhoon season ( June to September ) and reference season ( October to December ) in the Zoynan Region in Kaohsiung , southern Taiwan . To our knowledge , this is the first report describing concentrations of B . pseudomallei in ambient air . For the typhoons affecting the Zoynan Region , the positive rates of ambient B . pseudomallei were very high . Our data imply the possibility of air transmission of Melioidosis during the typhoon season . In addition , ambient B . pseudomallei aerosolized from sediment of a nearby lake should be a concern as an important source of transmission . Our results could provide deeper insight into Melioidosis transmissibility and infection control .
|
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"Introduction",
"Materials",
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"Methods",
"Results",
"Discussion"
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"neglected",
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2014
|
The Concentrations of Ambient Burkholderia Pseudomallei during Typhoon Season in Endemic Area of Melioidosis in Taiwan
|
A new polysaccharide secreted by the human opportunistic fungal pathogen Aspergillus fumigatus has been characterized . Carbohydrate analysis using specific chemical degradations , mass spectrometry , 1H and 13C nuclear magnetic resonance showed that this polysaccharide is a linear heterogeneous galactosaminogalactan composed of α1-4 linked galactose and α1-4 linked N-acetylgalactosamine residues where both monosacharides are randomly distributed and where the percentage of galactose per chain varied from 15 to 60% . This polysaccharide is antigenic and is recognized by a majority of the human population irrespectively of the occurrence of an Aspergillus infection . GalNAc oligosaccharides are an essential epitope of the galactosaminogalactan that explains the universal antibody reaction due to cross reactivity with other antigenic molecules containing GalNAc stretches such as the N-glycans of Campylobacter jejuni . The galactosaminogalactan has no protective effect during Aspergillus infections . Most importantly , the polysaccharide promotes fungal development in immunocompetent mice due to its immunosuppressive activity associated with disminished neutrophil infiltrates .
Aspergillus fumigatus is an opportunistic human fungal pathogen that causes a wide range of diseases including allergic reactions and local or systemic infections such as invasive pulmonary aspergillosis ( IA ) that has emerged in recent years as a leading cause of infection-related mortality among immunocompromised patients [1] , [2] . The innate immune system provides the first line of defense against A . fumigatus with macrophages and neutrophils that sense , phagocytose and kill conidia and hyphae through the production of anti-microbial agents . Later , antigen presenting cells initiate an adaptative response activating various populations of T-helper cells that impact differently on the evolution of the disease [3] , [4] . Because of its external localisation , and specific composition , the cell wall represents a specific target for recognition and specific interaction with the host immune cells . The cell wall of A . fumigatus is mainly composed of branched β1-3glucans , α1-3glucans , chitin , β1-3/1-4 glucan and galactomannan [5] . These constitutive polysaccharides have been shown to induce specific immune responses from the host . For example in murine models of aspergillosis , α1-3glucan and β1-3glucan chains induce a protective response through the activation of Th1 and Th17 or Treg responses [4] whereas galactomannan favours the disease through the activation of the Th2/Th17 response . In other medically important fungi , capsular and cell wall polysaccharides and especially mannan and β-glucans also induce an immune response that either favours or inhibits fungal infection [6] , [7] , [8] , [9] . During growth in vitro in aerial conditions or in vivo in the lung tissues , the mycelium of A . fumigatus is covered by a polysaccharide-rich extracellular matrix ( ECM ) that because of its outer position , plays a major role in the interaction with the host immune cells [10] , [11] . The ECM contains α1-3glucan and galactomannan that are two of the major cell wall polysaccharides , recognised by T cells . A third galactosamine-rich polysaccharide has been now identified in the ECM . Although the presence of such cell wall associated polysaccharide was noticed 20 years ago [12] , [13] , its structural analysis has not been investigated to date . The present report shows that this polysaccharide is a linear heterogenous chain constituted by α1-4 linked galactose and α1-4 linked N-acetylgalactosamine residues . Most interestingly , the analysis of the immune response towards this polysaccharide shows that it is immunosuppressive and favors A . fumigatus infection .
The culture filtrate of A . fumigatus was precipitated by 70% ethanol . In our experimental conditions , an amount of 80 mg of ethanol precipitate was recovered per g of mycelial dry weight . The incubation of the ethanol precipitate of the culture filtrate of A . fumigatus for 1 h in a 150 mM NaCl aqueous solution resulted in the solubilisation of glycoproteins and galactomannan . The NaCl-insoluble material represented 43+/−8% of the ethanol precipitate . The remaining insoluble material was separated in two fractions based on their solubility in 8 M urea . The urea-soluble material ( SGG , urea soluble galactosaminogalactan ) accounted for 30+/− 4% of the total ethanol precipitate whereas the urea-insoluble material ( PGG , urea insoluble galactosaminogalactan ) represented 13+/− 6% of the total ethanol precipitate . Gas liquid chromatography ( GC ) analysis of both fractions showed that they were exclusively composed of galactosamine and galactose with ratios of 60/40 and 15/85 in SGG and PGG respectively . Nitrous deamination of native polysaccharide did not solubilise the polysaccharide and did not produce anhydrotalose showing that all galactosamine residues were N-acetylated ( not shown ) . GC analysis showed that the galactosaminogalactan was absent in resting conidia but was present in the cell wall of mycelium from both solid and liquid cultures and in different media ( not shown ) . Immunofluorescence with specific anti-GG mAb confirmed that GG was not present on the surface of resting conidia . In contrast , a positive detection was seen in the cell wall as soon as the conidium germinates ( Fig . 1 ) . This result indicated that part of the galactosaminogalactan was not secreted and remained strongly associated with the cell wall . The amount of cell wall bound galactosaminogalactan was equivalent to the amount recovered in the culture medium ( data not shown ) . GC analysis of permethylated GG revealed only two methyl ethers: 2 , 3 , 6-tri-O-methyl-galactitol and 3 , 6-di-O-methyl-N-acetylgalactosaminitol ( Fig . S1 ) , indicating the substitution in position 4 of both monosaccharides . The absence of methylether from non-reducing end sugar or disubstituted monosaccharide indicated that the galactosaminogalactan was an unbranched linear polysaccharide . The apparent Mr estimated by gel filtration chromatography after the carboxymethylation of the GG fraction was in agreement with methylation data . The galactosaminogalactan was eluted as a polydisperse homogenous polymer between 10 and 1000 kDa with a median size of 100 kDa ( Fig . S2 ) . The 1D 1H and 2D 1H , 13C nuclear magnetic resonance ( NMR ) spectra of carboxymethylated GG fraction exhibited two main signals in the sugar anomeric region at 5 . 003/103 . 07 and 5 . 287/99 . 07 ppm compatible with α-anomers ( Fig . S3 ) . NMR data showed downfield shifts for the carbone-4 of both sugar residues , indicating their 4-O substitution and their pyranose configuration , which were in agreement with the methylation data . In order to elucidate the repartition of each monosaccharide on the main polysaccharidic chain , two specific chemical degradations of both galactosaminogalactan fractions ( PGG and SGG ) were undertaken: periodate oxidation that degraded 4-O-substituted galactose residues and N-de-acetylation/nitrous deamination that degraded hexosamine residues . Solubilised fractions were separated by gel filtration on HW40S column and chemically analysed by methylation , GC-Mass spectrometry ( GC-MS ) , Matrix-assisted laser desorption-Time of flight ( MALDI-TOF ) and NMR . The periodate oxidation followed by mild acid hydrolysis solubilised 90% of the SGG . The insoluble product was composed of only N-acetylgalactosamine ( GalNAc ) residues . Three solubilised fractions were separated by gel filtration on HW40S column ( Fig . 2A ) . GC-MS analyses showed that fraction III corresponded to threitol , resulting from the periodate degradation of 4-O-subsituted galactose residues ( not shown ) . GC-MS analyses of permethylated fraction II showed the presence of compound with a pseudomolecular ion mass [M + H]+ of m/z = 424 and [M + NH4]+ of m/z = 441 corresponding to the permethylated GalNAc-threitol ( Fig . S4 ) . NMR data confirmed this analysis and showed that the fraction II contained a compound with an α-GalNAc1-2-threitol arrangement ( Table S1 ) . MALDI-TOF analysis of compounds of fraction I indicated a mixture of GalNAc oligosaccharides linked to one threitol residue ( Fig . 2B ) . Nitrous deamination solubilised 95% of the SGG . Here , only a polygalactan that accounted for 5% of the total polysaccharide was not solubilised . The soluble material was separated on a HW40S gel permeation column . In addition to the anhydrotalose ( resulting from the degradation of the galactosamine ) , a wide peak ( fraction I ) was eluted from the column ( Fig . 3 ) . The MALDI-TOF analysis of fraction I revealed the presence of several pseudomolecular ion masses with a regular increase of m/z = 162 and a shift of 18 , corresponding to hexose oligosaccharide linked to a non-reduced anhydrotalose in its aldehyde and hydrated forms , respectively [14] ( Fig . 3 ) . This result showed that the fraction I was composed of a mixture of galactooligosaccharides of dp 2 to 11 with an anhydrotalose at the reducing end . This result was confirmed by the NMR analysis that indicated the presence of the linkage -4-αGal1-4AHT in this fraction ( Table S2 ) . Carbohydrate structure analyses showed that the galactosaminogalactan from A . fumigatus is a linear heterogeneous polymer of α1-4galactosyl and α1-4N-acetylgalactosaminyl residues . Both SGG and PGG were analyzed and showed similar structures ( Table 1 ) . The major differences between these two fractions relied on the degree of polymerization of the galactooligosaccharides and the presence of a higher amount of GalNAc in PGG . The insoluble material after periodate treatment accounted for 25% of the initial material of the PGG indicating that the homogenous linear polyN-acetylgalactosamine was 2 to 3 times higher in PGG . In addition , in contrast to SGG where galactose oligosaccharides of 2 to 10 residues were joined by one GalNAc residue , in PGG GalNAc or polyGalNAc oligosaccharides were mainly joined by a single galactose residue ( Fig . S5 ) . These data showed that the galactosaminogalactan of A . fumigatus did not contain a repeat unit and displayed a high heterogeneity in the sequences of oligosaccharides composed of Gal and GalNAc and that this heterogeneity impacted on the physicochemical properties of the polysaccharide . The antigenicity of the GG was tested first with sera from a blood bank . Surprisingly , antibodies directed against GG were present in most human sera tested: in our experimental conditions , 40% of the 131 tested sera gave by direct ELISA an OD reading >1 at a 1∶500 dilution ( Fig . S6 ) . The isotype responsible was mainly IgG2 and full inhibition of the antigen-antibody reaction was obtained with SGG , confirming the specificity of the antibody reaction . Infection with Aspergillus was not associated with an increase in the serum titers against GG . In a similar ELISA format with sera from aspergillosis patients , only 40% of aspergilloma patient gave an OD value higher than 1 by direct ELISA , whereas all these aspergilloma patients had high titers against the galactomannan that is a marker polysaccharide antigen of A . fumigatus . Similarly , only 30% of patient with invasive aspergillosis reacted positively with the galactosaminogalactan ( not shown ) . The lack of correlation between aspergillosis and the occurrence of high serum titers against GG in healthy patients suggested that the antibody reaction against GG was due to a cross-reactivity with α-GalNAc-containing molecules , since GalNAc has been recognised to be an immunologically reactive hexosamine present in several human or microbial antigens . Among all the molecules tested , the Tn-antigen ( α-GalNAc-serine/threonine ) or the serotype A marker ( α-GalNAc1-3[β-Fuc1-6]β-Gal1- ) did not cross react with GG ( data not shown ) . The lack of cross reactivity with human molecules that contained a single GalNAc molecule at their non-reducing end suggested that the presence of several GalNAc molecules was required to form the immunogenic epitope . Accordingly , a high cross reactivity was found between the GG of A . fumigatus and the N-glycan of cell surface glycoproteins of Campylobacter jejuni ( AcraA ) that is an α1-4 linked GalNAc rich structureα-GalNAc1-4 α-GalNAc1-4 [β-Glc1-3]α-GalNAc1-4 α-GalNAc1-4 α-GalNAc1-3 β-Bac1-Asn ( where Bac is 2 , 4-diacetamido-2 , 3 , 6-trideoxy-D-glucose; Asn , asparagine and Glc , glucose , [15] ) . A significant positive correlation was calculated for the OD values obtained with the GG and AcraA molecules in 131 blood bank sera . The Spearman's rho correlation coefficient had a value of 0 . 71 ( p<0 . 0001 ) ( Fig . S6 ) . In addition , ELISA showed that a specific rabbit polyclonal antiserum directed against the N-glycan of surface proteins of C . jejuni reacted positively with the GG of A . fumigatus ( not shown ) . ELISA-inhibition assays were performed on a group of 30 sera with OD >1 for both AcraA and GG antigens . AcraA positive sera with OD>1 were always highly inhibited with 5 µg/ml of SGG ( not shown ) , suggesting that the epitope recognised by these AcraA ( and GG ) positive sera was a linear α1-4GalNAc oligosaccharide . This result was confirmed by ELISA inhibition studies using the fraction containing exclusively the α1-4GalNAc oligosaccharide obtained after periodate oxidation or acid hydrolysis of SGG ( Fig . S7 ) . However , in 20% of serum samples , oligoGalNAc did not completely inhibit the GG recognition , indicating that , in human sera , some IgG could be specifically directed against Gal-GalNAc or Gal-Gal sequences ( Fig . S7 ) . Mice were treated with antigen and CpG ( oligonucleotide containing umethylated CpG motifs ) as adjuvant to assess the putative protective effect of this antigen against pulmonary aspergillosis in a murine model of vaccine-induced resistance [4] . Figure 4 shows that , in contrast to the protection afforded by conidia , SGG failed to confer resistance to infection and even favored fungal growth ( Fig . 4A ) . No reduced inflammatory pathology was seen in the lung where actual fungal growth was observed in GpG+SGG-treated mice ( Fig . 4B ) and the cytokine pattern showed that SGG inhibited Ifnγ/Il10 and activated Il4 gene expression in the TLN , thus suggesting inhibition of protective Th1/Treg cells and promotion of Th2 responses ( Fig . 4C ) . Most interestingly , when the immunomodulatory activity of SGG was assessed in intact mice with primary infection , SGG promoted the infection , as seen by the increased lung CFUs and inflammatory pathology in SGG-treated mice as compared to controls ( Fig . 5A and B ) . Figure 5C shows that SGG induced inflammatory cytokine gene expression , such as Tnfα and Il6 . Moreover , SGG induced the expression of Il17a genes but suppressed Ifnγ and Il10 expression . These data were in agreement with the expression of the relative Th cell specific transcription factors in the TLN ( data not shown ) . Of interest , SGG appeared to reduce neutrophil infiltrates in the lung during infection , as also seen by the reduced Mpo expression ( Fig . 5C ) . These data suggest that SGG inhibit host defence against A . fumigatus . Bloodstream neutrophils have a short half-life and prolongation of their lifespan is critical for efficient pathogen destruction . As SGG-treated mice exhibited reduced neutrophil infiltrates in the lung during infection as compared to controls , we investigated the effect of SGG on neutrophil apoptosis . Neutrophils cultured at 37°C died rapidly by apoptosis , about 60% of cells being annexin V+ after 20 h . As previously reported [16] , apoptosis was accelerated by cycloheximide and delayed by GM-CSF . The percentage of apoptotic cells in whole-blood samples incubated with SGG ( 10–20 µg/ml ) was significantly higher than in the PBS control . In addition , SGG significantly inhibited GM-CSF-induced PMN survival ( Fig . 6 ) . Since the C-type lectin MGL has been shown to be specific for GalNAc residues , the binding of GG to MGL was investigated . Using SGG and PGG as ligands , ELISA experiment showed a lack of specific interaction of the GG of A . fumigatus and recombinant MGL-Fc . Similarly , immunofluorescence experiments showed that MGL-Fc did not bind to the cell wall of germinated conidia expressing GG on their surface ( data not shown ) . ELISA inhibition using GalNAc coupled to polyacrylamide ( GalNAc-PAA ) as the ligand showed that GG did not inhibit the binding of GalNAc-PAA to MGL . In contrast , GalNAc oligosaccharides obtained by HCl hydrolysis ( Fig . S8 ) inhibited the interaction with MGL ( Fig . 7 ) . Since MGL recognized terminal GalNAc residues and since the average degree of polymerisation of the oligosaccharide fraction used was 7 . 5 , the relative inhibition was similar for GalNAc and the GalNAc oligosaccharide pool when expressed in molar concentration . In contrast to GalNAc monomers that inhibit 100% of the binding at 1 mg/ml in our experimental conditions , no full inhibition was obtained with the oligoGalNAc fraction because at concentrations higher than 500 µg/ml , the GalNAc oligosaccharides precipitated . The lack of binding of MGL to the whole GG was due to the presence of one terminal GalNAc per 700 GalNAc residues in average in the linear 100 kDa GG polysaccharide . Only oligoGalNAc resulting from the degradation of GG can be recognised efficiently by MGL .
Here , we describe the purification and the chemical characterization of a new galactosaminogalactan secreted by the mycelium of A . fumigatus . Cell wall and extracellular polysaccharides containing galactosamine residues have been also identified in other filamentous fungi , such as Neurospora , Rhizopus , Helminthosporium , Penicillium and Aspergillus species [17] , [18] . However , the structure of these polysaccharides has been poorly characterized with linkages that can be either α1-4 and/or α1-3 linkages with part of the GalNAc molecules being N-deacetylated [19] , [20] , [21] , [22] . The A . fumigatus galactosaminogalactan is exclusively composed of α1-4linked galactose and α1-4linked N-acetylgalactosamine residues . In our growth conditions , the GG was totally N-acetylated . It was , however , shown that this linear polysaccharide is extremely heterogeneous , with strands of galactose and N-acetylgalactosamine of variable length that impact on the polysaccharide solubility and putatively on biological properties . This heterogeneity is unique to the galactosaminogalactan because the other constitutive cell wall polysaccharides of A . fumigatus are homopolymers ( chitin , glucans ) or have well defined repeating unit , such as A . fumigatus galactomannan [12] , [23] . The main motif is Gal-GalNAc , but the variable Gal/GalNAc ratio inside each polymer chain suggests random synthesis of the polymer , as in some plant polysacharides [24] . The synthesis of polygalactose and polyN-acetylgalactosamine oligosaccharides , as well as the synthesis of repetitive Gal-GalNAc unit is totally unknown . The galactose of GG is present in a pyranose form , whereas the galactose of the galactomannan , which is a major antigen of A . fumigatus , is in a galactofuranose form . A . fumigatus has the ability to synthesise the two isoforms of galactose , like many bacterial , parasite and fungal microorganisms [25] , [26] , [27] , [28] , [29] . This was indeed shown in a UDP-Gal epimerase mutant , in which galactofuranose synthesis was abolished , but some galactose was still present in the cell wall , corresponding to the GG [30] ( data not shown . ) . It was very surprising to see that a majority of the sera from the blood bank had high titers of IgG against GG , with GalNAc residues being the main determinant for the antigenicity . This result suggested that this polysaccharide could be a very potent immunoadjuvant that could be used to induce the production of antibodies against poorly antigenic molecules . The only cross-reacting antigen identified so far was the N-glycans of glycoproteins of C . jejuni . This result suggests that the portal of entry for the GG could be the gut barrier as has been demonstrated for the galactomannan polymer [31] , [32] . N-glycoproteins of C . jejuni can bind to human intestinal epithelial cells [33] , [34]; Gal/GalNAc rich-polysaccharides are produced by many environmental fungal food contaminants including Aspergillus and Penicillium species suggesting that in both cases α1-4GalNAc oligosaccharides could cross the intestinal epithelium . This galactosaminogalactan study has confirmed the essential immunological role of the fungal cell wall polysaccharides . This has been seen with all medically important fungi [6] , [35] , [36] , [37] . Some of the cell wall polysaccharides of A . fumigatus , such as α1-3glucan and β1-3glucan chains , have been shown to induce a protective immune response through the activation of Th1 , Th17 or Treg responses and the inhibition of the Th2 response [4] . A different immunological function can be conveyed by other cell wall polysaccharides . GG not only is not inducing a protective response but is promoting an immunosuppressive function that can trigger disease in immunocompetent mice . A similar function can probably be attributed to the galactomannan that also has been shown to induce a Th2/Th17 response that was not protective [4] . However , at that time the authors did not investigate the immunosuppressive role of the later polysaccharide in immunocompetent mice . The production of a Th2/Th17 response is in agreement with the presence of anti-GG and anti-Galactomannan IgG2 antibodies in human sera , whereas the level of anti-α1-3glucan and β1-3glucan antibodies in humans is absent or extremely low . In addition , GG-induced PMN death may be involved , at least in part , in the decrease in neutrophil infiltrates in lungs from GG-treated mice despite an increased Th17 response . The GG is the first Aspergillus polysaccharide that induces cell apoptosis . The pathogenic yeast , Cryptococcus neoformans produces a polysaccharide capsule constituted by 2 polymers: glucuronoxylomannan and galactoxylomannan that induce in vitro apoptosis of human macrophages and T-cells [38] , [39] . Polysaccharide receptors of mammalian macrophages remain poorly characterized . Besides Dectin1 that recognizes β1-3glucans , receptors able to recognize α1-3glucans or galactan have not been identified yet [40] , [41] . The MGL ( macrophage galactose-type lectin ) was the obvious candidate for GG binding since it recognizes specifically GalNAc residues [42] . This receptor is located at the cell surface of immature dentritic cells and has been shown to be involved in the recognition of pathogens through GalNAc residues and in the retention of immature DCs in peripheral tissue and lymphoid organs [42] , [43] , [44] . The MGL is able to bind to N-glycoproteins of C . jejuni through α1-4 linked GalNAc residues [45] and the binding of these N-glycans to MGL influences the function of human dentritic cells . However , no specific binding of GG to human MGL-Fc was seen , suggesting that cell surface MGL was not involved in the recognition of A . fumigatus GG . However , the intracellular hydrolysis of GG , as shown for some bacterial polysaccharides [46] , may release oligosaccharides that can bind to MGL that has been seen in endocytic compartments . Such intracellular recognition of GG oligosaccharides could then induce the pro-inflammatory response . This hypothesis is currently being investigated .
The A . fumigatus , strain CBS 144–89 was grown in a 15l fermenter in modified Brian medium ( 2% asparagine , 5% glucose , 2 . 4 g/l NH4NO3 , 10 g/l KH2PO4 , 2 g/l MgSO4-7H2O , 26 mg/l ZnSO4-7H2O , 2 . 6 mg/l CuSO4-5H2O , 1 . 3 mg/l Co ( NO3 ) 2-6H2O , 65 mg/l CaCl2 , pH 5 . 4 ) for 72 h at 25°C . The mycelium was removed by filtration under vacuum and the supernatant was precipitated with 2 . 5 vol . of ethanol overnight at 4°C . The pellet was collected by centrifugation ( 3000g , 10 min ) . The pellet was washed twice with 2 . 5 l of 150 mM NaCl and then extracted with 8 M urea ( 2 h twice at room temperature under shaking ) . Urea-supernatants ( SGG ) were pooled and extensively dialyzed against water and freeze-dried . Urea-insoluble pellet ( PGG ) was washed with water and freeze-dried . Total hexoses were measured by the phenol-H2SO4 method using galactose as a standard [47] . Total hexosamines were determined with p- ( dimethylamino ) -benzaldehyde reagent after 4 h of 8N HCl hydrolysis at 100°C using galactosamine as a standard [48] . Monosaccharides were identified by GC as their alditol acetates after total acid hydrolysis ( trifluoroacetic acid ( TFA ) 4N or HCl 4N , 100°C , 4 h ) [49] . Threitol resulting from the periodate oxidation of galactose was identified by GC-MS and NMR . In absence of reference spectrum , anhydrotalose resulting from the nitrous deamination of galactosamine was identified by GC-MS by comparison with the mass spectrum of anhydromannitol and by NMR . Prior to the methylation procedure , polysaccharides were peracetylated as previously described [50] . Dried sample ( 2 mg ) was methylated by the DMSO/lithium methyl sulfinyl carbanion/ICH3 procedure [50] . After hydrolysis of the permethylated sample ( 4 N TFA 100°C , 4 h ) , borodeuteride-reduction and peracetylation , methyl ethers were identified by GC-MS . Oligosaccharides were permethylated by the DMSO/NaOH/ICH3 procedure [51] . Polysaccharide fractions ( 30 mg ) were resuspended in 4 ml of 10 mM HCl at 50°C for 24 h and then oxidized with 100 mM sodium m-periodate at 4°C in darkness during 7 days . Excess reagent was destroyed by adding 0 . 5 ml of ethylene glycol . The solution was dialysed against water and freeze-dried . The material was reduced overnight by 10 mg/ml NaBH4 at room temperature . After neutralisation to destroy the excess of borohydride , reduced oxidized polysaccharide was dialysed against water and freeze-dried . A mild acid hydrolysis was performed by 1 . 5 ml of 50 mM TFA at 100°C for 1 h . The solubilised fraction was fractionated on a HW40S column ( TosoHaas , 90×1 . 4 cm ) equilibrated in 0 . 25% acetic acid at the flow rate of 0 . 4 ml/min . Eluted sample were detected by refractometry . The insoluble fraction was washed twice in water . Polysaccharide fractions ( 30 mg ) were resuspended in 4 ml of 10 mM HCl at 50°C for 24 h and then de-N-acetylated with 40% NaOH ( final concentration ) at 100°C for 4 h . After neutralisation by addition of acetic acid , samples were dialysed and freeze-dried . Dried samples were resuspended in 600 µl of NaOAc 0 . 5 M pH 4 . The deamination was started by addition of 300 µl of 1 M NaNO3 and performed at 50°C during 3 h with the addition of 300 µl of 1 M NaNO2 each hour . Soluble degraded products were fractionated by gel filtration chromatography through a HW40S column , as described above . Neutral sugars were detected by the phenol-H2SO4 method [47] . 10 mg of polysaccharide were treated with 1 ml of 0 . 1 M HCl for 3 h at 100°C . After neutralisation with 1% Na2CO2 , solubilised materials were purified by gel filtration through a Sephadex G25 column ( GE Heathcare , 90×1 . 4 cm ) and eluted with 0 . 25% acetic acid at a flow rate of 9 ml/h . Due to its insolubility , carboxymethylation of GG was necessary to estimate its molecular size by gel filtration . The polysaccharide ( 0 . 2 g ) was carboxymethylated by addition of 20 ml of 1 . 6 M NaOH and 0 . 3 g of monochloroacetic acid . The mixture was heated at 75°C and stirred magnetically for 8 h . After neutralisation , the solution was dialysed against water and freeze-dried . The carboxymethylated polysaccharide was soluble in 0 . 5% acetic acid and 10 mg were deposited onto a Sephacryl S400 column ( Pharmacia , 90×1 . 4 cm ) at the flow rate of 10 ml/h . Dextrans ( Pharmacia , T2000 , T500 , T70 , T40 ) were used as standards for the column calibration . GC was performed on a Perichrom PR2100 instrument with a flame ionisation detector using a capillary column ( 30 m×0 . 32 mm id ) filled with a DB-1 ( SGE ) under the following conditions: gas vector and pressure , helium 0 . 7 bar; temperature program 120 to 180°C at 2°C/min and 180 to 240°C at 4°C/min . GC-MS was performed on an EI/CI mass spectrometer detector ( model 5975C , Agilent technologies , Massy France ) coupled to a chromatograph ( model 7890A ) , using a HP-5MS capillary column ( 30 m×0 . 25 mm id , Agilent technologies ) under the following conditions: gas vector: helium at 1 . 2 ml/min; temperature program: 100 to 240°C at 8°C/min and 240°C for 10 min . Ammoniac gas was used for the chemical ionisation . MALDI-TOF mass spectra were acquired on a Voyager Elite DE-STR mass spectrometer ( Perspective Biosystems , Framingham , MA , USA ) equipped with a pulsed nitrogen laser ( 337 nm ) and a gridless delayed extraction ion source . The spectrometer was operated in positive reflectron mode by delayed extraction with an accelerating voltage of 20 kV and a pulse delay time of 200 ns and a grid voltage of 66% . Samples were prepared by mixing directly on the target 0 . 5 µl of oligosaccharide solution in water ( 10–50 pmol ) with 0 . 5 µl of 2 , 5-dihydroxybenzoic acid matrix solution ( 10 mg/ml in CH3OH/H2O , 50∶50 , V/V ) . The samples were dried for about 5 min at room temperature . Between 50 and 100 scans were averaged for every spectrum . NMR spectra of the polysaccharides were acquired at 318 and/or 343 K on a Varian Inova 500 spectrometer equipped with a triple resonance 1H{13C/15N} PFG ( pulsed field gradient ) probe whereas spectra of either nitrous deamination or periodate oxidation products were acquired at 298 K on Varian Inova 500 and 600 spectrometers equipped with a triple resonance 1H{13C/15N} PFG and a cryogenically-cooled triple resonance 1H{13C/15N} PFG probe respectively ( Agilent technologies , Massy France ) . Polysaccharidic samples solubilized in acetic acid 0 . 05%V/V in H2O by warming for one hour at 100°C were freeze dried and redissolved in DCl 0 . 06 M in D2O ( DCl ≥ 99 . 0% 2H atoms and D2O ≥99 . 9% 2H atoms , Euriso-top , Saint-Aubin , France ) . After a second freeze-drying , they were redissolved in D2O and transferred in a 5 mm NMR tube ( Wilmad 535-PP , Interchim , Montluçon , France ) . The final concentration was about 5 mg/mL . Samples were dissolved in D2O and transferred in a 5 mm NMR tube ( Shigemi BMS-005 V , Shigemi Inc . , Alison Park , United States ) . 1H chemical shift were referenced to external DSS ( 2 , 2-methyl-2-silapentane-5-sulfonate sodium salt hydrate , its methyl resonance was set to 0 ppm ) . 13C chemical shifts were then calculated from 1H chemical shift and gamma ratio relative to DSS . 13C/1H gamma ratio of 0 . 251449530 was used [52] . The following strategy was used for assignment of nuclei . First , the non-exchangeable proton resonances of intra glycosidic residue spin systems were assigned using two-dimensional COSY ( correlation spectroscopy ) , relayed COSY ( up to two relays ) and TOCSY ( Total correlation spectroscopy; with mixing time ranging from 30 to 120 ms ) experiments [53] . Secondly , 1H-13C edited gHSQC ( Gradient selected heteronuclear single-quantum correlation ) and gHSQC-TOCSY ( mixing time up to 80 ms ) experiments allowed the 13C chemical shifts assignment from previously identified 1H resonances [54] . Then , 1H , 1H coupling constants for the oligosaccharides were extracted from 1D and/or 2D spectra ( 1H resolution of 0 . 1 Hz and 0 . 6 Hz respectively ) and the anomeric configuration was established from the knowledge of 3J1 , 2 value . Finally , the interglycosidic linkages determination was achieved with 1H-1H NOESY ( Nuclear overhauser effect spectroscopy ) experiments for the polysaccharides ( mixing time of 15 and 50 ms ) and with 1H-1H ROESY experiments ( mixing time of 250 ms ) [55] and/or 1H-13C gHMBC ( Gradient selected heteronuclear multiple bond correlation ) experiment ( long range delay of 60 ms ) [54] for the oligosaccharides . Patient samples were collected according to French Ethical rules . Written informed consent and approval by institutional review Board at the Pitié-Salpêtrière Hospital , at the Etablissement français du sang and at Saint-Louis Hospital were obtained . Mouse experiments were performed according to the Italian Approved Animal Welfare Assurance A–3143–01 . Legislative decree 157/2008-B regarding the animal licence was obtained by the Italian Ministry of Health lasting for three years ( 2008–2011 ) . Infections were performed under avertin anesthesia and all efforts were made to minimize suffering . Serum samples from 131 healthy subjects ( from Groupe français du sang and Hôpital Saint-Louis , Paris ) , 25 invasive aspergillosis patients ( Hôpital Saint-Louis; kind gift of A . Sulhaian ) and 5 aspergilloma patients ( CHU Toulouse; kind gift of P . Recco ) were used through this study . Blood group was determined by the Etablissement français du sang . The presence of antibodies directed against the A . fumigatus galactosaminogalactan was assessed by a direct enzyme-linked immunosorbent assay method ( ELISA ) . Purified A . fumigatus galactosaminogalactan and AcraA , a recombinant N-glycoprotein from Campylobacter jejuni expressed in E . coli [56] , [57] were used as antigens . Wells of microdilution plates ( F-form , Greiner , Frickenhausen , Germany ) were coated with 100 µl of a suspension of 1 µg/ml galactosaminogalactan ( PGG ) or 5 µg/ml AcraA diluted in 50 mM Na2CO3 pH 9 and incubated overnight at room temperature . Binding of antibodies to the ELISA-plate was estimated with patient sera diluted 1∶500 and peroxidase-conjugated anti-human immunoglobulin G , as previously described [12] . Cross reactivity between GG and the Tn antigen ( α-GalNAc-Serine ) was analysed by ELISA with a monoclonal antibody against the Tn antigen ( kind gift from Dr R . Lo-Man , Institut Pasteur ) . Mice ( Balb-C ) were immunized subcutaneously with a crude cell wall preparation of A . fumigatus mycelium . Monoclonal antibodies have been produced by F . Nato and P . Beguin ( Plateforme technique de protéines recombinantes et anticorps monoclonaux , Institut Pasteur ) as previously described [58] . Screening of positive hybridoma was followed by ELISA using the HCl-treated PGG as specific antigen . These mAbs did not react with other Aspergillus polysaccharides , such as galactomannan , β1-3glucan , α1-3glucan . ELISA-inhibition experiments showed that the recognition of mAb-galactosaminogalactan was fully inhibited by oligoGalNAc obtained after partial HCl hydrolysis and gel filtration chromatography on G25 sephadex column as described above ( Fig . S8 ) Resting conidia and conidia germinated for 8 h in a 2% glucose/1% peptone liquid medium were fixed with 2 . 5% p-formaldehyde ( PFA ) overnight at 4°C . After fixation , cells were washed with 0 . 2 M glycine in PBS for 5 min , then with 5% goat serum in PBS for 1 h . Cells were incubated with the anti-galactosaminogalactan monoclonal antibody at 20 µg Ig/ml in 5% goat serum/PBS for 1 h at room temperature . After washing with PBS-BSA 1% , cells were incubated with a goat FITC-conjugated Ab directed against mouse IgG ( H+L ) diluted 1∶100 in goat serum/PBS . After washing in PBS , cells were visualized with an inverted fluorescence light microscope . Specificity of labelling was assessed by preincubation of MAb with 50 µg/ml of G25-I fraction ( Fig . S8 ) . Binding assay to the macrophage galactose lectin ( MGL ) was done by ELISA-inhibition using a recombinant MGL-Fc chimeric protein as previously described [42] . Briefly , α-GalNAc-conjugated polyacrylamide ( 2 µg/ml , Lectinity ) was coated on ELISA plates . Plates were blocked with 1% BSA and the MGL-Fc was added ( 0 . 5 µg/ml ) for 2 h at room temperature . For inhibition assays , MGL-Fc was previously incubated for 1 h at room temperature in the presence of increasing concentrations of SGG , GalNAc oligosaccharides , Gal or GalNAc or 10 mM EGTA . Binding was quantified using a peroxidase-conjugated secondary antibody directed against human IgG Fc ( Jackson ) . The putative binding of MGL to mycelium was investigated by immunofluorescence . For that purpose , 0 . 4×105 conidia were incubated in 200 µl of Brian's medium in wells of chamber slides ( Lab-Tek , Nunc ) at 37°C for 9 h , washed with PBS and fixed in 2 . 5% PFA overnight . Cells were washed with 0 . 2 M glycine in TSM buffer ( 20 mM TrisHCl; 150 mM NaCl , 2 mM MgCl2 , 1 mM CaCl2 , pH 7 . 4 ) for 5 min , then with 5% goat serum in TSM for 1 h . Cells were incubated with the MGL-Fc at 65 µg/ml in 5% goat serum/TSM for 1 h at room temperature . After washing with TSM , cells were incubated with an anti-human Fc FITC conjugated-goat anti-serum at 15 µg/ml in goat serum/TSM . After washing in TSM , then water , cells were visualized under a fluorescent light microscope . Female , 8- to 10-week-old inbred C57BL6 ( H-2b ) mice were obtained from Charles River Breeding Laboratories ( Calco , Italy ) . The vaccination model was as previously described [4] . Briefly , mice were injected intranasally with 2×107 Aspergillus conidia/20 µl saline 14 days before the infection or with 5 µg SGG + 10 nM CpG oligodeoxynucleotide 1862 ( CpG ) /20 µl saline , administered 14 , 7 and 3 days before the intranasal infection . Mice were immunosuppressed with 150 mg/kg/i . p . of cyclophosphamide a day before infection and then intranasally infected with a suspension of 2×107 viable conidia/20 µl saline . In another set of experiments , immunocompetent mice were injected with 250 mg/kg SGG i . n . the day of the infection ( 2×107 viable conidia/20 µl saline ) and on days 1 , 2 and 3 post-infection . Mice were monitored for fungal growth ( CFU/organ expressed as mean ± SEM ) as described [59] . For histology , sections ( 3–4 µm ) of paraffin-embedded tissues were stained with periodic acid-Schiff ( PAS ) . Cytokines were quantified by Real-time PCR , performed using the Stratagene Mx3000P QPCR System , and SyBR Green chemistry ( Stratagene Cedar Creek , Texas ) . Total lung cells were recovered 3 days after the infection . CD4+ T cells ( >99% pure on FACS analysis ) from thoracic lymph nodes ( TLNs ) recovered 7 days after the infection , were separated by magnetic cell sorting with MicroBeads and MidiMacs ( Miltenyi Biotec ) . Cells were lysed and total RNA was extracted using RNeasy Mini Kit ( Qiagen ) and reverse transcribed with Sensiscript Reverse Transcriptase ( Qiagen ) , according to manufacturer's directions . The PCR primers were as described [60] , [61] . Amplification efficiencies were validated and normalized against Gapdh . The thermal profile for SYBR Green real-time PCR was at 95°C for 10 min , followed by 40 cycles of denaturation for 30 seconds at 95°C and an annealing/extension step of 30 seconds at 72°C . Each data point was examined for integrity by analysis of the amplification plot . The mRNA-normalized data were expressed as relative cytokine mRNA in treated cells compared with that of mock-infected cells . Neutrophil apoptosis was quantified by using annexin V and the impermeant nuclear dye 7-amino-actinomycin D ( 7-AAD ) as previously described [16] . Apoptosis was measured after incubation in 24-well tissue culture plates at 37°C with PBS or SGG ( 1-20 µg/ml ) for 20 h . Cycloheximide ( Calbiochem , La Jolla , CA ) ( 10 µg/ml ) and GM-CSF ( R&D Systems ) ( 1000 pg/ml ) were used as proapoptotic and antiapoptotic controls , respectively . In some experiments , blood samples were first incubated with SGG for 1 h and then with GM-CSF . Whole-blood samples ( 100 µl ) were then washed twice in PBS , incubated with allophycocyanin ( APC ) -anti-CD15 mAb ( BD Biosciences ) for 15 min , and then incubated with fluorescein ( FITC ) -annexin V ( BD Biosciences ) for 15 min . After dilution in PBS ( 500 µl ) , the samples were incubated with 7-AAD ( BD Biosciences ) at room temperature for 15 min and analyzed immediately by flow cytometry ( GalliosTM , Beckman Coulter ) . Neutrophils were identified as CD15high cells and 2×105 events were counted per sample . The combination of FITC-annexin V and 7-AAD was used to distinguish early apoptotic cells ( annexin V+/7-AAD- ) , from late apoptotic cells ( annexin V+/7-AAD+ ) , necrotic cells ( annexin V-/7-AAD+ ) and viable cells ( unstained ) . Statistical analyses of the ELISA data were performed using the Spearman's rho test with the JMP software ( SAS; Cary , NC ) . Data from mouse experiments were analyzed by GraphPad Prism 4 . 03 program ( GraphPad Software , San Diego , CA ) . Student's t test or analysis of variance ( ANOVA ) and Bonferroni's test were used to determine the statistical significance ( P ) of differences in organ clearance and in vitro assays . The data reported are either from one representative experiment out of three to five independent experiments ( western blotting and RT–PCR ) or pooled from three to five experiments , otherwise . The in vivo groups consisted of 6–8 mice/group . Data on the measurement of neutroplil apoptosis are reported as means ± SEM . Comparisons were based on ANOVA and Tukey's Post Hoc tests , using Prism 3 . 0 software ( GraphPad software ) .
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Aspergillus fumigatus is an opportunistic human fungal pathogen that causes a wide range of diseases including allergic reactions and local or systemic infections such as invasive pulmonary aspergillosis that has emerged in the recent years as a leading cause of infection related mortality among immunocompromised patients . Polysaccharides from the fungal cell wall play essential biological functions in the fungal cell biology and in host-pathogen interactions . Indeed , it has been shown that polysaccharides can modulate the human immune response; some of them ( β-glucan and α-glucans ) having a protective effect against Aspergillus infection . We report here the purification and chemical characterization of a new antigenic polysaccharide ( galactosaminogalactan ) produced by A . fumigatus . This polymer is secreted during infection . In murine models of aspergillosis , this galactosaminogalactan is not protective but it is immunosuppressive and favors A . fumigatus infection . Particularly it induces the apoptotic death of neutrophils that are the phagocytes playing an essential role in the killing of fungal pathogens .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunopathology",
"biochemistry",
"fungal",
"biochemistry",
"mycology",
"fungi",
"immunology",
"biology",
"microbiology",
"host-pathogen",
"interaction",
"glycobiology",
"immune",
"response"
] |
2011
|
Galactosaminogalactan, a New Immunosuppressive Polysaccharide of Aspergillus fumigatus
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Malaria affects 300 million people worldwide every year and 450 , 000 in Brazil . In coastal areas of Brazil , the main malaria vector is Anopheles aquasalis , and Plasmodium vivax is responsible for the majority of malaria cases in the Americas . Insects possess a powerful immune system to combat infections . Three pathways control the insect immune response: Toll , IMD , and JAK-STAT . Here we analyze the immune role of the A . aquasalis JAK-STAT pathway after P . vivax infection . Three genes , the transcription factor Signal Transducers and Activators of Transcription ( STAT ) , the regulatory Protein Inhibitors of Activated STAT ( PIAS ) and the Nitric Oxide Synthase enzyme ( NOS ) were characterized . Expression of STAT and PIAS was higher in males than females and in eggs and first instar larvae when compared to larvae and pupae . RNA levels for STAT and PIAS increased 24 and 36 hours ( h ) after P . vivax challenge . NOS transcription increased 36 h post infection ( hpi ) while this protein was already detected in some midgut epithelial cells 24 hpi . Imunocytochemistry experiments using specific antibodies showed that in non-infected insects STAT and PIAS were found mostly in the fat body , while in infected mosquitoes the proteins were found in other body tissues . The knockdown of STAT by RNAi increased the number of oocysts in the midgut of A . aquasalis . This is the first clear evidence for the involvement of a specific immune pathway in the interaction of the Brazilian malaria vector A . aquasalis with P . vivax , delineating a potential target for the future development of disease controlling strategies .
Malaria is one of the most important vector-borne diseases , affecting 300 million people worldwide every year and 22 countries in America . Brazil presents over half of the total estimated cases with numbers varying from 300 to 600 thousand over the past years [1] . The lack of effective vaccines , the development of drug resistance in Plasmodium parasites and of insecticide resistance in mosquitoes , have prevented the successful control of human malaria in many tropical regions . Understanding the biology of the Plasmodium-mosquito vector interaction is important to identify potential targets for the development of novel malaria control strategies to disrupt the parasite life cycle in the insect vectors and prevent disease transmission to humans . The mosquito immune system limits parasite development and over-activation of some immune pathways has been shown to decrease Plasmodium infection [2] , [3] . The insect immune system is very efficient in defending against a diversity of pathogens through multiple innate immune responses , which are also present in higher organisms [4] . Genetic studies in Drosophila identified three major signaling pathways that regulate expression of immune effector genes: TOLL , Immune deficiency ( IMD ) , Janus Kinase and Signal Transducer and Activator of Transcription ( JAK-STAT ) pathways [5] . In mosquitoes it was demonstrated that the Imd pathway prevents the development of Plasmodium falciparum in Anopheles gambiae , Anopheles stephensi and Anopheles albimanus while the Toll pathway is most efficient in A . gambiae against Plasmodium berghei [2] , [3] . The JAK-STAT pathway was first described as a cytokine induced intracellular signaling pathway [6] , [7] very tightly regulated by a series of activators and suppressors . In humans , over-activation of this pathway has been associated with neoplastic transformation [8] . In Drosophila , the JAK-STAT pathway has been implicated in several cellular processes such as regeneration , homeostasis , eye development and embryonic segmentation . In addition , in Drosophila this pathway participates in some cellular immune responses as differentiation of prohemocytes and hemocyte proliferation , as well as in antibacterial responses [9]–[12] . Recent studies showed that the JAK-STAT pathway mediates Anopheles gambiae immune response to P . berghei and P . falciparum [13] and Aedes aegypti response to dengue virus II [14] . In Drosophila melanogaster , activation of the STAT pathway is initiated when the peptide ligand Unpaired ( Upd ) binds to the transmembrane receptor Domeless . This activates the JAK kinase Hopscotch to phosphorylate the transcription factor Stat92E . The phosphorylated STAT protein forms a dimer , translocates to the nucleus and activates transcription of target genes [10] . This pathway is tightly regulated by various proteins , such as Suppressor of Cytokine Signaling ( SOCS ) and Protein Inhibitor of Activated STAT ( PIAS ) . The SOCS gene is transcriptionally activated by the STAT pathway as part of a negative feedback loop that modulates STAT signaling by preventing STAT phosphorylation , while PIAS inhibits signaling by directly binding to STAT proteins and targeting them for degradation [15] . Anopheles aquasalis is an important malaria vector in the Brazilian coast . Although Plasmodium vivax is more widely distributed than P . falciparum , and there are close to three billion people at risk of infection by this parasite worldwide [16] , research on the biology and transmission of P . vivax has been neglected for several decades . This is mostly due to the lack of an efficient continuous cultivation system and to the misconception that this parasite does not cause severe malaria [17] , [18] . Although it has long been considered a benign infection , it is now accepted that P . vivax can cause severe and even lethal malaria [19] . We cloned and characterized three genes from the JAK-STAT pathway: the transcription factor STAT , the PIAS regulatory proteins and the enzyme NOS . The main goal of this study was to determine whether the JAK-STAT pathway is activated in A . aquasalis in response to P . vivax infection and , if so , whether this response limits Plasmodium infection .
For the acquisition of P . vivax infected human blood , patients were selected among people visiting the Health Center ( Posto Estadual de Saúde da Vigilância em Saúde do Município de Iranduba , Distrito de Cacau Pirêra , Amazonas , Brazil ) searching for malaria diagnosis and treatment during outbreaks . Diagnosis was performed by Giemsa stained blood smears . After P . vivax positive diagnosis with presence of about 4–8% circulating gametocytes , patients were interviewed and inquired about the possibility of volunteer donation of a small amount of blood for research purposes . Subsequently , a patient consent form was first read to the potential volunteers , with detailed verbal explanation , and signed by all patients involved in the study . After this agreement , 200 microliters of venous blood was drawn from each patient and placed in heparinized tubes . Blood samples were kept under refrigeration in an icebox ( at approximately 15°C ) for about 15 minutes , taken to the laboratory and used to feed A . aquasalis . All ethical issues of this study followed international rules including the Declaration of Helsinki . The used protocols , including the human consent forms , were previously approved by the Brazilian Ministry of Health , National Council of Health , National Committee of Ethics in Research ( CONEP ) ( written approval number 3726 ) . A . aquasalis were reared at 27°C and 80% humidity [20] . Insect infections were performed in a safety insectary at an endemic area of Manaus , Amazonas state , as described in Bahia et al . [21] . Human infected blood containing 4–8% gametocytes or normal blood ( control ) were offered to the insects by oral feeding using a membrane glass feeder device under constant 37°C temperature , maintained using a water circulation system , to prevent exflagellation of microgametocytes [21] . After the experimental feeding , mosquitoes were kept in cages at 27°C and given 20% sucrose ad libitum . Mosquito infection was evaluated by PCR using a specific Plasmodium 18s rRNA gene [21] . The experimental prevalence rate of infected A . aquasalis mosquitoes with P . vivax was 36% , as detected by PCR or by oocysts presence ( number of infected mosquitoes/total examined ) . The mean intensity of the infected mosquitoes was 7 . 6% ( i . e . , the average number of parasites as calculated using the number of infected mosquitoes as the denominator ) . A low number of P . vivax oocysts were consistently found in the infected mosquitoes , which is in agreement with the usual low number of human malaria parasites found infecting mosquito vectors in nature . PCR reactions were performed as described using degenerate primers designed on conserved regions of STAT and PIAS , based in sequences of A . gambiae , A . stephensi , A . aegypti and D . melanogaster [22] . The PCR cycles used were: two cycles ( 1 min steps at 95°C , 55°C and 72°C , and 95°C , 42°C and 72°C ) followed by 30 cycles at moderate stringency ( 1 min steps at 95°C , 52°C and 72°C ) and a final 7 min extension at 72°C . All amplicon generated were cloned into pGEM®-T Easy Vector ( Promega ) and utilized to transform high efficiency DH5-α Escherichia coli . Sequencing of the selected clones was performed using an ABI 3700 sequencer ( Applied Biosystems ) and the ABI PRISM® BigDye™ Terminator Cycle Sequencing reagent ( Applied Biosystems ) in the PDTIS/FIOCRUZ Sequencing Platform . The SMART cDNA RACE amplification kit ( Becton Dickinson Clontech ) was used to obtain the 5′ and 3′ ends of the PIAS and STAT cDNAs . All amplicons generated were cloned and sequenced as described above . After sequencing , the cDNAs of STAT and PIAS were assembled using the CAP3 Sequence Assembly Program ( http://pbil . univ-lyon1 . fr/cap3 . php ) and aligned with other insect sequences with the Clustal W Program ( http://www . ebi . ac . uk/Tools/clustalw2/ ) . RNA was extracted from whole insects submitted to different experimental conditions ( immature stages – egg , first to fourth instar larvae and pupa; sugar-fed males and females; females fed on blood and blood from P . vivax malaria patients ) . The extracted RNA was treated with RQ1 RNAse-free DNAse ( Promega ) and utilized for cDNA synthesis . RTPCR reactions were performed using the SyberGreen fluorescent probe employing an ABI 7000 machine ( Applied Biosystems ) . The PCR cycles used were 50°C 2 min , 95°C 10 min , 95°C 15 sec and 63°C 1 min for 35 times for all reactions . The primer sequences were: STATFwd 5′ CTGGCGGAGGCGTTGAGTATGAAAT 3′ and STATRev 5′ CGGATAAGGAAGGCTCGTTTTGAAT 3′ , PIASFwd 5′ TAGCAGCTCACAGTATAGCCTCGAT 3′ and PIASRev 5′ TCCCATTCCAACCAACAAACCA 3′ , and NOSFwd 5′ AGGATCTGGCCCTCAAGGAAGCCGA 3′ and NOSRev 5′ ATCGTCACATCGCCGCACACGTACA 3′ . The relative expression of the selected genes was based on gene expression CT difference formula [23] . Quantifications were normalized in relation to the housekeeping gene rp49 [24] . All the experiments were performed using four to six biological replicates and three experimental replicates . The Shapiro-Wilk and Levene tests were used to determine when parametric versus non-parametric tests should be used . The ANOVA test with multiple comparisons of Tukey or Games-Howell was used in the analyses . When this parametric model was not adequate , the Kruskal-Wallis test with multiple comparisons of Dunn's was utilized . Bonferroni correction was used when necessary . All tests were performed with reliable level of 95% ( α = 0 . 05 ) . The statistical analyses were accomplished using the GraphPad Prism5® and R 2 . 9 . 0 . Proteins of whole insects submitted to different feeding regimens ( sugar-fed males and females , and females after different times of blood feeding and infection ) were extracted by Trizol Reagent ( Invitrogen ) following the manufacturer's “instructions for protein isolation” protocol . Samples corresponding to one insect were separated on 12% SDS-PAGE gels and subsequently transferred to Hybond nitrocellulose membranes . The membranes were blocked with 5% non-fat milk TBS Tween 20 0 . 1% ( TBST ) for at least one hour . The membranes were then incubated with anti-PIAS antibody at a 1∶250 dilution for two hours . After three washes of 10 minutes in TBST , the membranes were incubated with anti-rabbit secondary antibody at a 1∶80 . 000 dilution for one hour . Three more washes were performed before the incubation of the membrane with the detection system Pierce SuperSignal West Pico chemiluminescent substrate ( ThermoScientific ) . Sugar-fed male and female A . aquasalis submitted to different treatments ( sugar-feeding , infected and non-infected blood-feeding ) were collected , had their heads , legs and wings removed , and were fixed overnight at 25°C in 4% paraformaldehyde in PBS . The insects were dehydrated in 30% to 100% ethanol , and then infiltrated with Hystoresin kit ( Leica ) at room temperature for 5–7 days . Hystoresin-embedded mosquitoes were transversally sectioned using a rotary microtome in order to expose the organs located in the abdomen and thoracic regions . The 3 µm-thick sections were adhered to slides , dried , incubated for 20 minutes in 1% PBS/BSA and 20 minutes in RPMI medium in order to avoid nonspecific antibody binding . Sections were then incubated overnight with 1∶250 anti-rabbit STAT or PIAS antibodies diluted in 1% PBS/BSA . The tissue sections were washed 5–8 times with 1% PBS/BSA and then incubated with rabbit secondary antibody conjugated to FITC ( Molecular Probes ) , diluted 1∶250 in blocking solution . The same steps were performed in the control samples , except for the incubation with the primary antibody After two washes in PBS , the slides were mounted using Mowiol anti-photobleaching Mounting Media ( Sigma Aldrich ) . Immunostaining was analyzed with a confocal laser microscope ( Zeiss-LMS 510 ) . Photos are representative of at least five mosquitoes for each treatment . Alternatively , midguts of females 24 hpi were dissected , opened transversely in order to expose the lumen and fixed for 20 minutes ( m ) in 4% paraformaldehyde in PBS at 4°C in order to be processed for immunocytochemistry as described elsewhere [25] . The opened insect midguts were treated with 1% PBS/BSA followed by RPMI medium as described above . Then , the tissue sections were incubated with commercial anti-NOS antibody ( Sigma Aldrich SAB4300426 ) diluted 1∶250 in 1% BSA/PBS . Five washes were performed and the midguts were incubated with anti-rabbit antibody conjugated to Alexa 594 diluted 1∶250 in 1% PBS/BSA . Five more washes with PBS were performed before mounting the midguts in slides with Mowiol . The same steps were performed in the control samples , except for the incubation with the primary antibody . The material was analyzed by confocal laser microscopy . Double stranded RNAs ( dsRNAs ) for STAT ( dsSTAT ) and ß-gal ( dsβ-gal ) were produced from PCR-amplified fragments using the T7 Megascript kit ( Ambion ) . Amplicons for dsß-gal were produced using plasmid templates and for dsSTAT by reverse transcriptase PCR ( RT-PCR ) products , from sugar-fed female cDNA , giving rise to 544 bp and 503 bp fragments , respectively . Two rounds of PCR were performed to amplify ß-gal . The first PCR round was performed with primers containing a short adaptor sequence at the 5′ end ( tggcgcccctagatg ) . The primers used for the first round of PCR were ß-galFwd 5′tggcgcccctagatgTGATGGCACCCTGATTGA 3′ and ß-galRev 5′ tggcgcccctagatgTCATTGCCCAGAGACCAGA 3′ . The PCR cycles utilized were 95°C for 3 min , 35 cycles of 95°C for 30 s , 57°C for 45 s and 72°C for 45 s followed by 72°C for 7 min . Two microliters of the first PCR were used in the second PCR reaction . The second round of PCR was utilized to insert the bacteriophage T7 DNA-dependent RNA polymerase promoter to the DNA templates . The second round of PCR utilized the same conditions of the first reaction . The second round PCR primer , which has the T7 ( bold letters ) and the adaptador sequences , was 5′ ccgTAATACGACTCACTATAGGtggcgcccctagatg 3′ . STAT amplification was performed in one round of PCR , which also inserted the T7 sequence . The STAT primer used was STATFwd 5′ TAATACGACTCACTATAGGGGATGATGTACCGGACCTGCT 3′ and STATRev 5′ TAATACGACTCACTATAGGGGTGTACGATGACGACAACCG 3′ . The amplification of the STAT sequence was done using the PCR cycles as follows: 95°C for 5 min and 35 cycles of 95°C for 30 s , 55°C for 45 s and 72°C for 45 s . dsSTAT or dsß-gal ( 69 nL of 3 µg/µL ) diluted in water were introduced into the thorax of cold anesthetized 3–4 day old female mosquitoes by a nano-injector ( Nanoject , Drummond ) with glass capillary needles . After the injection , the insects were maintained in an air incubator and fed on sugar solution . At two to three days after the dsRNA injections , the insects were fed with P . vivax infected blood . Three to five days after infection , the oocysts in the basal lamina of the gut epithelium were counted to estimate the P . vivax load in the infected mosquito . Each dissected mosquito gut was stained with 2% mercurochrome and observed under light microscopy . At least 30 guts were used for each experimental condition and three different gene silencing experiments were performed . Oocyst numbers in dsSTAT injected insects were compared to insects injected with β-gal dsRNA , a control for a gene not found in the insect . The significance of gene silencing effect on oocysts loads was determined by the Mann-Whitney statistical test . Total RNA was extracted from females , either sugar-fed or one to five days after dsRNA injections . Up to 5 µg of RNA were treated with RQ1 RNAse-free DNAse ( Promega ) and used for first strand cDNA synthesis utilizing the ImProm-II™ Reverse Transcription System ( Promega ) . PCR reaction conditions were the same utilized for RTPCR , as were the primers ( STAT and rp49 ) . Biological and experimental triplicates were performed . The PCR reactions were separated in a 2 . 5% ethidium bromide-containing agarose gel . The housekeeping gene rp49 was used to normalize the reactions [24] and sugar-fed female samples were used as reference samples . The intensity of amplified products was measured using ImageJ 1 . 34 s software ( http://rsb . info . nih . gov/ij ) and plotted for semi-quantitative analysis . The ANOVA test was used as statistics method .
Two genes of the JAK-STAT pathway of A . aquasalis , the transcription factor STAT ( AqSTAT ) and its regulatory protein PIAS ( AqPIAS ) were amplified by PCR , using degenerate primers and genomic DNA as template . The 1150 bp ( STAT ) and 891 bp ( PIAS ) PCR fragments were cloned and sequenced . After in silico predictions of exons and introns , 836 bp and 549 bp coding sequences were obtained for STAT and PIAS , respectively . These sequences were used to design perfect-matching primers and the SMART RACE technique was used to obtain the complete cDNA sequences of these two genes using a mixture of cDNAs from males and infected and non-infected females as template . A full-length AqSTAT cDNA sequence of 1599 bp was obtained , consisting of a 1491 bp open reading frame ( ORF ) coding for a 497 amino acid residues protein , plus a 108 bp 3′ untranslated region ( UTR ) ( Figure S1 ) . The full-length AqPIAS cDNA consists of 2407 bp including a 1953 bp ORF , which encodes a protein of 651 amino acid residues , as well as a 211 bp 5′ UTR and 243 bp 3′ UTR ( Figure S2 ) . These two sequences were deposited in GenBank with accession numbers HM851178 and HM851177 , respectively . Sequence analyses and comparison with other mosquito STATs showed that AqSTAT presents the SH2 domain , the STAT binding domain and a portion of the alpha domain , but lacks the STAT interaction domain , presented schematically in Figure 1A . Phylogenetic approaches showed that AqSTAT grouped with STATs from other mosquitoes and was more closely related to A . gambiae STAT-A ( the ancestral gene ) than to STAT-B ( a gene duplication that probably resulted from a retro-transposition even ) ( Figure 1B and C ) . AqPIAS presents two very conserved domains , the SAP domain and the MIZ/SP-RING zinc finger domain ( Figure 2A ) . The deduced AqPIAS protein had higher homology to putative ortholog genes from other mosquitoes than to those of other insects , such as Drosophila pseudoobscura and Apis mellifera ( Figure 2B and C ) . Gene expression of AqSTAT and AqPIAS investigated by RTPCR revealed that these genes are expressed in all mosquito developmental stages , including adults of both genders . Transcript levels of STAT are high in eggs ( Figure 3A ) while PIAS has high transcription levels in both eggs and first instar larvae ( Figure 4A ) . In adult stages , both STAT and PIAS were transcribed at higher levels in males than in females ( Figures 3A and 4A ) . We investigated the effect of P . vivax infection on expression of these two genes . To circumvent the inability to culture P . vivax , all mosquitoes used in these studies were fed on blood drawn from human donors infected with P . vivax malaria . Both STAT and PIAS genes were transcriptionally activated by P . vivax infection at 24 and 36 hours post-infection ( hpi ) . This induction was transient and was no longer observed 48 hpi ( Figures 3B and 4B ) . Furthermore , PIAS protein expression was also higher in protein homogenates obtained from infected females 24 and 36 hpi ( Figure 4C ) . A 702 bp cDNA fragment of A . aquasalis NOS ( AqNOS ) was obtained using degenerate primers , cloned and sequenced . This fragment is part of the nitric oxide synthase domain of NOS proteins ( Figure 5A ) . The A . aquasalis NOS is closely related to mosquitoes' NOS ( Figure 5B and C ) . This sequence was deposited in GenBank with accession number HM851179 . NOS mRNA expression was induced by P . vivax infection 36 hpi ( Figure 6A ) . Immunocytochemistry of A . aquasalis midguts infected with P . vivax 24 hpi revealed high levels of NOS protein expression in the cytoplasm of some epithelial cells when compared to the blood- fed insects ( Figure 6B and C ) . To reveal the tissues responsible for the expression of STAT and PIAS proteins , immunocytochemistry experiments were carried out . Antibodies against STAT and PIAS labeled distinctly the tissue sections of A . aquasalis according to the experimental conditions . There was very little nonspecific labeling in tissue sections of male ( Figures 7A and 8A ) or female ( Figures 7B and 8B ) control mosquitoes submitted only to incubation with secondary fluorescent antibodies . In sugar-fed mosquitoes , while males presented STAT and PIAS immunolabeling in several body parts , noticeably in the fat body ( Figures 7C and 8C ) , both proteins expression was weaker in sugar-fed females ( Figures 7D and 8D ) . In non-infected blood-fed females at 24 h , 36 h and 48 h , immunolabeling for both STAT ( Figure 7E , 7G and 7I ) and PIAS ( Figure 8E , 8G and 8I ) was mainly in the fat body and eggs . The labeling intensity increased with time , with fluorescence peak at 36 h ( Figure 7G and 8G ) , remaining noticeable at 48 h ( Figures 7I and 8I ) , the last time point used in our experiments . However , in P . vivax infected mosquitoes , immunolabeling of both STAT and PIAS appears to be stronger than the non-infected mosquitoes at 24 h ( Figures 7F and 8F ) and 36 h ( Figures 7H and 8H ) , but no detectable fluorescence was seen at 48 h ( Figures 7J and 8J ) . This corroborated our mRNA and protein expression results . To test whether activation of the JAK-STAT pathway limits P . vivax infection in A . aquasalis , the effect of silencing the transcription factor AqSTAT by systemic injection of dsRNA was evaluated . As a control , females were injected with dsß-gal , a gene not present in the mosquito genome . The transcription level of STAT was greatly reduced ( 70% ) in mosquitoes injected with dsSTAT , relative to those injected with dsß-gal ( Figure 9A and B ) . This effect was already observed one day post-injection and was still present 5 days post-injection . Mosquitoes were infected with P . vivax two to three days after dsRNA injection . Three to five days after infection , the guts were dissected and the oocysts were counted . These experiments revealed that reducing expression of the STAT gene increased the proportion of infected A . aquasalis females as well as oocysts density ( Figure 9C , D and E ) .
The JAK-STAT pathway is very conserved among species all the way from insects to humans . This pathway is important in insect immune response against some pathogens as bacteria [26]–[28] , virus [14] , [29] and Plasmodium [13] . A single STAT gene ( STAT92E ) was found in Drosophila as well as several other components of this signaling pathway such as: two homologous receptor ligands ( Upd2 and Upd3 ) , a membrane receptor ( Domeless ) and a JAK-kinase homologue ( Hopscotch ) [10] . Some JAK-STAT repressors have also been characterized in D . melanogaster , as for example SOCS ( SOCS36E ) [30] and PIAS ( dPIAS ) [31] . Bioinformatics analysis of the A . aegypti and A . gambiae genome sequences revealed the existence of Domeless , Hopscotch , STAT , PIAS and SOCS orthologs in these two mosquito species [14] , [31] . All dipteran insects examined so far have a single STAT gene , except for A . gambiae , in which two functional genes ( AgSTAT-A and AgSTAT-B ) have been characterized [13] . The AgSTAT-A gene is ancestral and is the putative ortholog of STAT genes from other insects . AgSTAT-B is an intronless gene that is evolving fast and appears to be the result of a retro-transposition event in which an AgSTAT-A cDNA was re-inserted back into the genome . Interestingly , AgSTAT-B regulates transcription of AgSTAT-A in adult stages and is the only STAT gene expressed in pupae [13] . In this work , three genes of the JAK-STAT pathway of A . aquasalis , the transcription factor STAT , its regulatory protein PIAS and NOS were cloned , sequenced and characterized . The domain organization of the PIAS protein is very similar to that of the A . gambiae and A . aegypti orthologs . The deduced A . aquasalis STAT , on the other hand , lacks some of the N-terminal conserved domains present in A . gambiae , A . aegypti and Drosophila STATs . It is probably the product of alternative splicing , as a similar cDNA ( ΔN-STAT92 ) giving rise to a protein that lacks 113 aa at the N–terminus , has been characterized in Drosophila [32] . AqSTAT and AqPIAS mRNAs are expressed in all insect stages and both in males and females . The high expression in eggs and first instar larvae may be indicating that , as in D . melanogaster [33] , [34] , the JAK-STAT pathway in A . aquasalis may also participate in oogenesis and embryogenesis . The expression pattern of AqSTAT mRNA in adult stages is very similar to A . gambiae STAT-A [13] , as in both anophelines males express higher STAT mRNA levels than sugar-fed females . In A . gambiae , AgSTAT-A expression remained unchanged 24 hours after infection with P . berghei [13] . In contrast , AqSTAT expression was activated transiently by P . vivax infection at 24 and 36 hpi . AqPIAS presented an mRNA expression pattern similar to AqSTAT and the induction of these two genes suggests that the JAK-STAT pathway is activated in response to P . vivax infection . The induction of PIAS protein expression corroborated the transcriptional results and provided direct evidence that the JAK-STAT pathway is also carefully regulated in A . aquasalis . Silencing AgSTAT-A in A . gambiae females infected with P . berghei reduced the number of early oocysts present two days post-infection , nevertheless enhancing the overall infection by increasing oocyst survival [13] . AqSTAT silencing also increased the number of oocysts , but its effect on very early stages of infection remains to be established . The peak transcriptional activation of the JAK-STAT pathway at 36 hpi was similar to what we observed for other immune genes such as serpins , bacterial responsive protein and fibrinogen [21] , indicating that the immune system is activated at the time when Plasmodium parasites have invaded the midgut and come in contact with the mosquito haemolymph . The activation of the JAK-STAT pathway at this time of infection may be regulating hemocyte differentiation , as seen in Drosophila [35] . In the case of A . aquasalis , this could help killing parasites and controlling infection . Immunocytochemistry revealed that A . aquasalis STAT and PIAS not only had concomitant expression but also localized in the same tissues . The expression of these proteins in sugar-fed males and females was mostly observed in the fat body , with males presenting stronger labeling than females . This corroborated the role of the fat body as the main immune organ of the insects . The detection of high levels of protein in males is in agreement with our previous results for other A . aquasalis immune genes such as fibrinogen , bacteria responsive protein and cecropin [21] . This seems to indicate that male mosquitoes are more prepared for eventual challenges , as opposed to what was observed in vertebrates and some invertebrate species , where females are more immunocompetent than males [36] . The expression of STAT and PIAS also presented differences between non-infected and infected insects . The non-infected insects were immunologically marked mainly in the fat body while the infected ones were marked in dispersed cells along all body and in the ingested blood . This pattern of expression of proteins from the JAK-STAT pathway demonstrated that A . aquasalis is producing a systemic immune response against P . vivax . In vertebrates , STAT1 regulates NOS expression [37] . DNA sequences capable of binding to STAT and NF-κB have been described in the regulatory regions of the NOS gene in A . stephensi [38] . In A . gambiae , AgSTAT-A participates in the transcriptional activation of NOS in response to bacterial and plasmodial infections , NOS expression being activated by P . berghei 24 hpi [13] . In A . aquasalis , we observed high levels of NOS transcription at a later time ( 36 hpi ) in response to P . vivax . Luckhart et al . [39] , [40] detected an increase in A . stephensi midgut NOS mRNA at several times ( 6 , 24 , 48 and 72 h ) after P . berghei infection . In A . gambiae infected with P . falciparum induction of NOS mRNA was also observed [41] . High expression of NOS protein was also seen in the cytoplasm of some midgut cells of A . aquasalis 24 hpi . These observations suggest that activation of the JAK-STAT pathway may be regulating NOS expression and that NO may be an important mediator of the antiplasmodial response . In some models of vector-parasite interaction as A . stephensi-P . berghei , insect midgut cells suffer damage after parasite invasion . Among these are protrusions toward the lumen , loss of microvilli , induction of NOS and production of NO , which is converted into nitrite and then into NO2 , causing protein nitration that leads to cell death [42] , [43] . This epithelial immune response is important to control parasite numbers and , in some cases , can be decisive for clearance of infection . Nevertheless , this mechanism is not universal , as induction of NOS and peroxidase activities were not observed in other vector-parasite combinations such as A . aegypti–Plasmodium gallinaceum and A . stephensi–P . gallinaceum [44] . The apparent inconsistency in the timing of appearance of NOS protein in the midgut and mRNA levels for this gene might be due to the expression of NOS mRNA only in the cells of the infected midgut injured by the parasite passage . Moreover , the expression of the mRNA in others organs of the insect can explain this discrepancies since the mRNA experiments were performed with whole mosquitoes and the protein expression only with the midgut . Our results showed that the A . aquasalis JAK-STAT pathway is activated in response to P . vivax challenge . Furthermore , preventing activation of the JAK-STAT pathway by silencing the AqSTAT transcription factor increased the infection , as well as the number of P . vivax oocysts in A . aquasalis mosquitoes . These results confirm the role of the JAK-STAT in limiting P . vivax infection of A . aquasalis . Enhancing these responses by using a transgenic approach may be effective in preventing P . vivax malaria transmission to humans by A . aquasalis mosquitoes .
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Malaria is endemic in 22 countries in the Americas where the Anopheles aquasalis mosquito is an important malaria vector and the Plasmodium vivax parasite is responsible for most malaria cases . This natural vector-parasite pair is difficult to study due to the lack of cultivating system for P . vivax , and to the lack of genome data for A . aquasalis . Moreover , almost all previous studies are based on African and Asian anopheline species . Understanding the interaction mechanisms between mosquito vectors and plasmodia is important for the development of malaria control strategies . Our results showed that the JAK-STAT immune pathway is activated in A . aquasalis after P . vivax challenge and is important to maintain the low levels of P . vivax load observed in this vector . Our results add to the understanding of the A . aquasalis interaction with P . vivax and lead to possible explanations for this vector competence in P . vivax transmission . All information generated here may be used to direct the development of new or specific strategies to block malaria transmission by A . aquasalis in some parts of the Americas .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"mosquitoes",
"plasmodium",
"vivax",
"vector",
"biology",
"biology",
"microbiology",
"malaria",
"parasitic",
"diseases"
] |
2011
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The JAK-STAT Pathway Controls Plasmodium vivax Load in Early Stages of Anopheles aquasalis Infection
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The asexual reproduction cycle of Plasmodium falciparum , the parasite responsible for severe malaria , occurs within red blood cells . A merozoite invades a red cell in the circulation , develops and multiplies , and after about 48 hours ruptures the host cell , releasing 15–32 merozoites ready to invade new red blood cells . During this cycle , the parasite increases the host cell permeability so much that when similar permeabilization was simulated on uninfected red cells , lysis occurred before ∼48 h . So how could infected cells , with a growing parasite inside , prevent lysis before the parasite has completed its developmental cycle ? A mathematical model of the homeostasis of infected red cells suggested that it is the wasteful consumption of host cell hemoglobin that prevents early lysis by the progressive reduction in the colloid-osmotic pressure within the host ( the colloid-osmotic hypothesis ) . However , two critical model predictions , that infected cells would swell to near prelytic sphericity and that the hemoglobin concentration would become progressively reduced , remained controversial . In this paper , we are able for the first time to correlate model predictions with recent experimental data in the literature and explore the fine details of the homeostasis of infected red blood cells during five model-defined periods of parasite development . The conclusions suggest that infected red cells do reach proximity to lytic rupture regardless of their actual volume , thus requiring a progressive reduction in their hemoglobin concentration to prevent premature lysis .
Plasmodium falciparum , Pf , is responsible for the most severe form of malaria in humans , representing a major cause of morbidity and mortality , especially among children . The pathology of malaria is caused by the intraerythrocytic stage of the parasite cycle . Invasion of a red blood cell ( RBC ) by a Pf merozoite converts a metabolically languid , hemoglobin-filled cell lacking intracellular organelles and structures , into a complex double cell , with a eukaryotic organism growing and multiplying inside , protected from immune attack . After a relatively quiescent period of about 15–20 h post-invasion , infected RBCs exhibit large increases in metabolic activity and solute traffic [1]–[7] across their membrane . The elevated metabolic rate persists until late stages of development and relaxes only during the latest hours of the parasite's 48 h asexual reproduction cycle . Staines et al . [8] showed that if uninfected human RBCs were permeabilized to the same extent the uninfected cells would hemolyze by the unbalanced net gain of NaCl and osmotic water over a shorter time-course than that needed for parasite maturation and exit . How , then , is the integrity of parasitized cells preserved for the duration of the intraerythrocytic cycle , considering that they have a parasite growing to a substantial volume inside ? This puzzle prompted an investigation on how premature lysis is prevented in falciparum-infected RBCs . A mathematical model of the homeostasis of parasitized RBCs was formulated to attempt an understanding of the processes involved [9] , [10] . The model encoded all known kinetic parameters relevant to the control of host red cell volume , i . e . , pH , membrane potential , ion content , ion transport across the RBC membrane and parasite growth . The initial simulations with the model produced a result which led to the formulation of a “colloid-osmotic hypothesis” to explain how infected RBCs ( IRBCs ) resist premature lysis . The hypothesis linked lysis resistance to hemoglobin consumption , a link hitherto never suspected . It had been well established that during the process of growth and maturation within RBCs malaria parasites ingest and digest hemoglobin ( Hb ) to levels far above those required by parasite protein synthesis [11] . Moreover , the amino acids produced in vast excess by hemoglobin proteolysis are rapidly released to the medium across the host RBC membrane through the so called “new permeation pathways” ( NPPs ) [7] , [11]–[14] , without apparent generation of any osmotic stress . Hb ingestion and digestion and heme detoxification , required to prevent damage to both parasite and host cell , are high energy-consuming processes [15]–[17] . It was therefore puzzling why Hb was consumed in such vast excess . The original model simulations [9] suggested that excess Hb digestion was necessary to reduce the colloid-osmotic pressure within the host cell , thus preventing its premature swelling to the critical hemolytic volume ( CHV ) . The simulations led to two critical predictions: ( i ) that excess Hb ingestion and digestion would cause not only a dramatic fall in the Hb content of the host cell , as had been established already from experimental evidence , but also a progressive and large decline in its Hb concentration , and ( ii ) that parasite volume growth together with host cell swelling late in the cell cycle would bring IRBC volumes very near their CHV . Allen and Kirk [18] argued that parasite volume growth was overestimated in the model because of its assumption that the parasite retains all of the volume taken up via the endocytotic feeding process , leading to exaggerated IRBC volume estimates . They stressed that most of the host volume ingested may be lost by different processes ( e . g , Hb breakdown , Na+ extrusion from the parasite compartment ) thus freeing up space for the parasite to expand into the host cell and limit the extent of swelling undergone by the infected cell as the parasite volume increases and cations enter the cell through colloid-osmosis . If IRBC volumes do not approach the presumed CHVs , then both the role attributed by the model to excess Hb consumption and the need for freeing space appear irrelevant . It became clear from these considerations that a thorough re-evaluation of the model assumptions and predictions in the light of past and recent experimental evidence became necessary . In this paper we present a new , detailed analysis of the homeostasis of P . falciparum-infected RBCs . A full description of the model equations is given ( see Text S1 ) , and a comprehensive analysis of model assumptions and predictions over the full range of parameter values supported by experimental evidence is provided . We conclude with a re-evaluation of the colloid-osmotic hypothesis . The original model simulations [9] were generated using a restricted set of parameter values and were reported using a minimal subset of model variables , leaving out much potentially useful information on the homeostasis of IRBCs . The present account overcomes these shortcomings and defines our current understanding of the homeostasis of P . falciparum-infected RBCs .
The stage-dependent changes in NPP-mediated permeabilities were measured in samples from synchronized Pf cultures [8] . They were encoded in the model as represented in Figure 1A and 1B . The curves may be interpreted in either of two ways: as a gradual simultaneous increase in NPP-mediated permeability in all the parasitized cells ( graded response ) , or as the net population variation in onset time of sudden permeability changes in individual cells ( all-or-none response ) . Can the available experimental evidence help discriminate between graded or all-or-none alternatives ? Isotonic solutions of NPP-permeant solutes such as sorbitol have been extensively used to selectively hemolyse IRBC with developed NPPs [20] . Analysis of the lysis kinetics of IRBCs renders results compatible with both types of responses [21] . Patch-clamp studies have not yet documented intermediate conductance stages in NPP activated IRBCs [22] . Therefore , the all or none response remains a distinct possibility , deserving investigation here by analysing the predicted effects of a sudden increase in NPP-mediated permeability . The stage-dependent changes in Hb consumption were defined within wide error margins [12] , [23] . Hb consumption of up to 80% of the host cell Hb is known to proceed gradually ( see , e . g . , [23] , and there is no “all or none” alternative to gradual Hb consumption . The most important and well supported feature of the two curves in Figure 1A is that NPP development precedes Hb consumption . Sorbitol , alanine and other solutes whose permeability through uninfected RBC membranes is negligible have been extensively used to probe for NPP permeabilization [7] . In isotonic solutions of sorbitol or alanine , IRBCs with developed NPPs rapidly lyse; only those with young ring-stage parasites remain intact . The importance of delayed Hb digestion relative to NPP development is that by the time the large excess of amino acids produced by globin proteolysis reaches the host cell membrane , the permeability path available for their rapid downgradient exit is available , thus preventing osmotic stress from accumulated amino acids within the host . However , the experimental errors in the observed half-times of NPP development and Hb ingestion curves are relatively large and the possible effects of interval variations between the curves in Figure 1 on IRBC homeostasis deserve exploration . Figures 2 and 3 show the results of a typical simulation with parameter values chosen for convenient illustration of the five homeostatic periods defined by inflexions in the curves reporting net fluid movements in the host RBC ( Phases 1 to 5 in Figure 2A ) . The model predictions here allow a detailed analysis of the homeostatic processes at work during the different stages of parasite development . During the stage of initial quiescence ( Phase 1 ) , from invasion to about 20 h post-invasion , all IRBC variables remain essentially unchanged from their initial levels . Phase 2 , K+-driven net fluid loss , is triggered by NPP activation . The immediate effect of the increase in Na+ , K+ and anion ( A− ) permeabilities ( Figure 1B ) is to induce the dissipation of the steep initial Na+ and K+ gradients ( Figure 2B and 2C ) , unrestricted by co-anion movements [24] , [25] . Initially the opposite driving forces for Na+ and K+ gradient dissipation have similar magnitude , as represented in Figure 2D and 2E by the respective electrochemical driving gradients ΔENa and ΔEK . The PK/PNa permeability ratio for cation selectivities is however set at 2 . 3 [8] and thus determines that the loss of KCl transiently exceeds NaCl gain . This causes a transient net fall in RBC cytosolic anion content and concentration ( Figure 2B and 2C , respectively ) and net loss of water ( Figure 2A , cell water and Figure 2F ) . Figure 3A shows that the K+ efflux , which initially exceeds Na+ influx , rapidly returns to near-zero baseline levels as the K+ gradient is dissipated . The transient dehydration of the IRBC during this second period generates secondary transient changes in other homeostatic variables: increase in Hb concentration ( Figure 3B ) , reduced anion content ( Figure 2B , A− ) and anion concentration ( Figure 2C , [A−] ) , and cell acidification ( Figure 3C ) . The transient acidification results from the brief increase in [Cl−]o/[Cl−]i ratio due to net KCl loss; the combined operation of the CO2 shunt and anion exchanger rapidly readjusts the proton ratio to restore the equilibrium condition [H+]i/[H+]o = [Cl−]o/[Cl−]i , with consequent cell acidification [26]–[28] . In Phase 3 , Na+-driven fluid gain , the direction of net fluid movement is reversed following the reversal of the gradients driving net salt flows . This reversal also affects the direction of change in all associated variables ( Figures 2 and 3 ) . Figure 3A shows that the net fluxes of Na+ and anions into the cell persist long after the net K+ flux has returned to baseline levels , and Figure 2D and 2E shows the time-dependent changes in driving gradients which determine the direction of net ion and fluid fluxes at all times according to the model ( see Text S1 ) . In Phase 4 , fluid loss , the rate of Hb consumption is maximal . This rate determines the volume of cytosol that the parasite needs to ingest in order to incorporate the amount of Hb prescribed by the Hb consumption function ( Figure 1 ) . When this volume exceeds the concomitant Na+-driven fluid gain , host cell water contents and host cell volume are transiently reduced ( Figure 2A ) . Phase 4 is characterized by the steepest rates of Hb fall ( Figure 3B , Hb ) and parasite growth ( Figure 2A , open triangles ) , and by a decline in cell water ( Figure 2A , solid triangles ) . Transient reductions in Na+ and anion contents ( Figure 2B , Na+ , A− ) result from the transfer of RBC cytosol to the parasite as part of the Hb ingestion process . Additional reduction in host cell volume results from the removal of the space occupied by Hb molecules . Hb has a specific volume of about 0 . 74 ml/g [29] and contributes with about 25% to the total volume of a normal RBC . Therefore , a loss of 70–80% of Hb from a cell containing in average 34 pg of Hb is equivalent to a volume loss of between 15–20 fl by the end of the asexual cycle . Phase 5 , sustained swelling , is characterized by continuous NaCl and water gains by the host cell ( Figures 2A ( cell water ) , 2B ( Na+ and A− ) , and 2F ) driven by the inward Na+ gradient . The rate of fluid gain is reduced relative to that in phase 3 ( Figure 2F ) because of the marked reduction in driving force for net NaCl gain ( Figure 2D and 2E ) and in colloid-osmotic pressure due to the fall in Hb concentration ( Figure 3B ) . Parasite and IRBC volumes also increase at slower rates ( Figure 2A ( Parasite , IRBC ) ) following the reduced Hb consumption and fluid gains relative to Phase 4 . As the anion concentration increases ( Figure 2C ) , the membrane potential becomes progressively more depolarized and the equilibrium potentials of all ions approach the membrane potential Em ( Figure 2D and 2E ) , with consequent cell alkalinisation ( Figure 3C ) . The Na pump , initially stimulated by the increased intracellular Na+ concentration , shows late inhibition ( Figure 3D ) . This inhibition results from a predicted reduction in Mg2+ concentration in the host cell cytosol following global cytosolic transfers to the parasite during Hb ingestion . Late swelling further reduces the Mg2+ concentration . The Mg2+/ATP ratio is an important regulator of Na pump activity and departure from its normal value near unity is inhibitory to the pump [30] , [31] . Atamna and Ginsburg [32] measured the Mg2+ content of host and parasite compartments in IRBCs with mature trophozoite stage parasites and found that the Mg2+ content of the host cell compartment was over 60% lower than that of uninfected RBCs . They suggested that such a reduction may partially inhibit active transport by the sodium and calcium pumps . It remains to be elucidated whether the actual mechanism of Mg2+ deprivation in the host cell is the one implied by the model . Figure 4 illustrates a condition in which NPPs are switched on almost instantly to analyse the homeostatic effects of all-or-none NPP activation ( Figure 4A ) . The rest of parameter values were the same as for Figure 2 . It can be seen that the main effect of all-or-none NPP activation is to compress the time-course of the events described for phase 2 ( Figure 2 ) , with relatively minor long-term quantitative changes in volumes ( Figure 4B ) and in Hb concentration ( Figure 4C ) . The relative duration and magnitude of the effects described for each period in the examples chosen for Figures 2 and 4 will vary with the choice of parameter values . These effects are analysed below . The important point to note is that the underlying homeostatic processes described for each period remain essentially the same . The time course of volume growth of P . falciparum parasites throughout their asexual reproduction cycle in human RBCs has not been characterized . Parasite volume increases throughout the cycle but it is unknown whether this growth is uniform or variable . The minimal final parasite volume in a cell with a single parasite has to equal the sum of the volumes of all the merozoites produced plus the volume occupied by the residual body . Without relevant information available , it was difficult to design a rational strategy to model parasite volume growth . Because the time-course of parasite volume growth could be roughly associated with that of Hb ingestion , linking these two variables was considered an acceptable modelling strategy . In the initial formulation of the model [9] , parasite volume at each instant of time was defined by the cumulative volume of ingested host cell cytosol up to that time . This volume , in turn , was determined by all the complex homeostatic factors that influenced the volume of host cytosol in which the prescribed amount of Hb to be digested at each time was contained . For maximal Hb consumption around 70–80% , this strategy predicted terminal parasite volumes of about 70 to 90 fl ( Figure 2A , Parasite ) , values near the mean volume of uninfected RBCs . However , previous results suggested that this approach overestimated parasite volume . Saliba et al . [33] measured the water content of parasites at the mature trophozoite stage to be less than 30 fl . Recent results by Elliott et al . [23] suggest that single parasite volumes seldom exceed 50 fl at any developmental stage . Therefore , to explore the effect of more realistic estimates of parasite volumes a coupling factor was introduced . It defines the global volume-growth of the parasite in each iteration of the numerical computation as a fraction of the volume of cytosol incorporated during that iteration ( see Text S1 ) . For coupling factor values of less than 0 . 7 , this approach implicitly corrects for parasite volume losses due to Hb breakdown , because , although hemozoin is retained , the volume occupied by the globin molecules largely vanishes in the process of exporting the resulting amino acids to the external medium . As explained above , this volume may account for up to 20 fl . The results of simulations using the same set of parameter values applied in the example of Figure 2 , varying only the value of the coupling factor , are shown in Figure 5 which reports predicted parasite volumes as a function of time post-invasion . From these results , only coupling factor values in the range 0 . 3 to 0 . 7 appear to cover the observed range of terminal parasite volumes for single infections . This range then will be tested in the global simulations attempted below , in comparison with the original value of 1 [9] , [10] . Figure 6 shows the model predictions for five selected variables , plotted as a function of time post-invasion . The chosen range of variation for each parameter was based on experimental results when available or on outcomes of simulations consistent with observation . For instance , although single parasite volumes may remain within the 30 to 50 fl range , IRBCs are often seen with two viable parasites reaching segmentor stages ( L . Bannister , personal communication ) , or with additional volume occupied by developmentally arrested parasites [34] . From the perspective relevant to the homeostasis of the host cell , it is the combined parasite volume that counts , hence the choice of coupling ratios spanning values from 0 . 3 to 1 . The range of half-time values for NPP development and Hb ingestion is shown within ±1 standard deviation of the experimentally-reported means [8] , [12] . Figure 6 shows only simulations with parameter values in which IRBC volumes remain below the spherical volume cells can attain within a maximally-stretched membrane , at which point they would lyse . This maximal volume is usually described as the critical hemolytic volume . Following Ponder [35] , the nominal CHV was set at a mean value of 1 . 7 times the original volume of the modelled cell . The immediate conclusion from gross comparisons between Figure 6A–C and Figure 6D and 6E is that whereas host cell water ( Figure 6A ) , IRBC volume ( relative to uninfected RBC volume , Figure 6B ) , and parasite volumes ( Figure 6C ) can vary over a very wide range and with large oscillations within the five homeostatic periods described for Figure 2 ( Figure 6A and 6B ) , the predicted decline pattern in host cell Hb concentration remains remarkably uniform ( Figure 6E ) . Therefore , the single novel and invariant prediction of the colloid-osmotic hypothesis is that the Hb concentration within the host cell has to become progressively reduced , regardless of parasite and IRBC volumes ( Figure 6E ) .
The analysis of the homeostasis of Pf infected RBCs ( Figures 2 , 3 , 4 , and 6 ) provides a number of novel insights: We consider next how experimental results in the literature compare with our model predictions . In Figure 7 , experimental measurements of the five selected variables reported in Figure 6 are shown as rectangles over the grey silhouettes of the variable ranges in Figure 6 . Despite the large variability in the experimental results , it is clear that they fall within the low range of values for host cell water ( Figure 7A ) , IRBC volume ( Figure 7B ) , and parasite volume ( Figure 7C ) for single infections [33] , [38] , [39] . The hemoglobin content measurements show a declining pattern covering the full range of the values encoded in the model ( Figure 7D ) . Most significantly , the recent measurements of the stage-dependent changes in host Hb concentration by Park et al . [40] and Esposito et al . [41] , obtained with two independent techniques confirm the declining pattern predicted by the model ( Figure 7E ) , thus lending support to its most relevant prediction . Do the large variations in parasite and host cell volumes explored with the model and also apparent in the experimental measurements ( Figure 7 ) reflect true IRBC polymorphisms or merely error margins ? IRBC polymorphisms are evident in relation to a number of characteristics which can be easily observed and recorded in live cultures: single or multiple invasion , developmental and viability differences among parasites in multiple invasions , IRBC shapes and volumes , parasite sizes and shapes , hemozoin particle content , aggregation state of hemozoin crystals , number of merozoites contained and released , etc . Many of these variations are observed in highly synchronized populations and cannot be attributed simply to differences in developmental stage of the parasite , or to viability state of the IRBCs . It is therefore plausible that the domain of stable homeostatic solutions predicted by the model ( Figure 6 ) does indeed reflect , at least in part , true homeostatic polymorphisms of IRBCs . If so , parasite , host and IRBC volumes may vary within wide margins from cell to cell without necessarily compromising the osmotic stability of the IRBC . This , however , questions the fundamental tenet of the colloid-osmotic hypothesis , that excess Hb consumption is necessary to prevent premature IRBC lysis . The problem can be clearly illustrated with an example . Let us consider an IRBC whose volume remains near a relative cell volume of 1 throughout the asexual reproduction cycle , as in many of the curves shown in Figure 6B , and as documented experimentally [23] , [33] , [40] . If the critical hemolytic volume remains set at 1 . 7 times the initial RBC volume , as originally assumed based on data from uninfected RBCs [35] , model simulations indicate that ∼20% Hb consumption would be enough to prevent the premature lysis of a cell with relative volume around 1 . So , for such a cell , excess Hb consumption would appear irrelevant for lysis prevention . But the available evidence overwhelmingly supports the view that Hb is consumed in large excess in all viable IRBCs . It follows that reduced colloid-osmosis may not be the main reason for excess Hb consumption , at least not in all instances . However , as discussed next , the conundrum here rests with the rigid attribution of a CHV of 1 . 7 in the model simulations , not with the basic understanding of IRBC homeostasis provided by the model . Previous results from osmotic fragility studies in IRBCs showed that the osmotic fragility of RBCs infected with mature trophozoite- and schizont-stage parasites is substantially increased relative to IRBCs with ring-stage parasites or to uninfected cohorts [9] , [10] . If the actual volume of at least some IRBCs harbouring mature parasites remains low , then for the osmotic fragility to be increased their CHV has to be somehow reduced . How can this occur ? The CHV of each RBC depends critically on membrane area [35] , [42] , [43] . If membrane area is reduced by infection , the CHV will also be reduced . The relation between volume ( V ) and area ( A ) in a sphere is given by V = A3/2/ ( 6π1/2 ) . Therefore , since the ratio of maximal volumes ( V1 , V2 ) of two cells with different surface areas ( A1 , A2 ) is V1/V2 = ( A1/ A2 ) 1 . 5 , a fractional decrease in area will propagate to a fractional decrease in volume to the power of 1 . 5 , stressing the magnified effect of effective membrane area reductions on CHV . Early results in the literature report opposing claims in relation to membrane area changes in infected IRBCs: population estimates report substantial reductions [39] whereas single cell measurements suggested no change [44] . Recent movies by Glushakova et al . [45] show infected cells about to rupture whose near spherical diameter is less than 80% that of surrounding uninfected discocytes indicating reduced membrane area . Considering , in addition , that the membrane geometry and fluid properties of Pf-infected RBCs become progressively altered by knobs and increased rigidity [46]–[51] , the increased osmotic fragility may be compounded by an increased lytic vulnerability to volume expansion , resulting from reductions in membrane area , in the capacity to effect a normal expansion of the full membrane area before lytic rupture , or both . The increase in the osmotic fragility of IRBCs reflects a progressive hemolytic vulnerability of Pf-infected RBCs to volume expansion by fluid gains . This shows that IRBCs become progressively closer to their effective CHV as the parasite matures , regardless of their actual volume levels . Although the contributions of membrane area loss and other factors to this hemolytic vulnerability remain to be elucidated , excess Hb consumption retains its credential as a general protection mechanism for IRBCs of all volumes , by preventing excessive rates of fluid gain . This mechanism depends critically on the prediction illustrated in Figures 3B and 6E that the Hb concentration must become progressively reduced in all IRBCs , regardless of the specific volume evolution of each IRBC . In conclusion: the original formulation of the colloid-osmotic hypothesis , using a coupling coefficient of one , predicted that IRBCs would swell close to a CHV level taken as the mean value for uninfected RBCs , premature rupture being prevented by the reduced Hb concentration . Simulations with coupling coefficient values below 0 . 7 deliver more realistic IRBC volume estimates ( Figures 5B and 7B ) , but experimental results indicate that the progressive proximity of IRBCs to a reduced CHV is retained . Thus , whatever the reason for CHV proximity , reduction in Hb concentration remains essential for preventing rapid fluid gains leading to premature IRBC lysis .
The mathematical-computational model of the homeostasis of Plasmodium falciparum-infected red blood cells ( IRCM ) was derived as an extension of the original Lew-Bookchin red cell model ( RCM ) [26] . Both models are available as free-standing executable files from http://www . pdn . cam . ac . uk/staff/lew/index . html . The IRCM first computes a “Reference” steady-state ( RS ) meant to represent the initial condition of a human red blood cell just invaded by a falciparum merozoite generating a ring-stage internalized parasite occupying 4% of the red cell volume . In the formulation of the RS the programme offers a large variety of options for the user to change constitutive properties of the IRBC such as the value of all the parameters tested in the simulations reported in this paper . For the simulations reported here the medium was assumed to be an infinite reservoir ( vanishingly low hematocrit condition ) . With the RS defined , the programme is set to follow the dynamic evolution of the IRBC system ( Dynamic state , DS ) for 48 hours with a data output frequency chosen by the user . To enable realistic comparisons with experimental results , experimental conditions can be simulated to explore the modified dynamic behaviour of the system .
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The parasite Plasmodium falciparum is responsible for severe malaria in humans . The 48 hour asexual reproduction cycle of the parasite within red blood cells is responsible for the symptoms in this disease . Within this period , the parasite causes massive changes in the host red cell , increasing some metabolic activities hundredfold , making it leaky to many nutrients and waste products , and consuming most of the cell's hemoglobin , far more than it needs for its own metabolism . The challenge that we faced was to explain how the infected cell maintained its integrity throughout such a violent cycle . Seeking clues , we developed a mathematical model of an infected cell in which we encoded our current knowledge and understanding of the complex processes that control cell homeostasis . We present here for the first time a detailed description of the model and a critical analysis of its predictions in relation to the available experimental evidence . The results support the view that host-cell integrity is maintained by the progressive reduction in the hemoglobin concentration within the host cell , resulting in a reduced rate and extent of swelling .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Model"
] |
[
"physiology",
"biophysics/theory",
"and",
"simulation",
"microbiology/parasitology",
"computational",
"biology"
] |
2009
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The Homeostasis of Plasmodium falciparum-Infected Red Blood Cells
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In injured neurons , “leaky” voltage-gated sodium channels ( Nav ) underlie dysfunctional excitability that ranges from spontaneous subthreshold oscillations ( STO ) , to ectopic ( sometimes paroxysmal ) excitation , to depolarizing block . In recombinant systems , mechanical injury to Nav1 . 6-rich membranes causes cytoplasmic Na+-loading and “Nav-CLS” , i . e . , coupled left- ( hyperpolarizing ) -shift of Nav activation and availability . Metabolic injury of hippocampal neurons ( epileptic discharge ) results in comparable impairment: left-shifted activation and availability and hence left-shifted INa-window . A recent computation study revealed that CLS-based INa-window left-shift dissipates ion gradients and impairs excitability . Here , via dynamical analyses , we focus on sustained excitability patterns in mildly damaged nodes , in particular with more realistic Gaussian-distributed Nav-CLS to mimic “smeared” injury intensity . Since our interest is axons that might survive injury , pumps ( sine qua non for live axons ) are included . In some simulations , pump efficacy and system volumes are varied . Impacts of current noise inputs are also characterized . The diverse modes of spontaneous rhythmic activity evident in these scenarios are studied using bifurcation analysis . For “mild CLS injury” , a prominent feature is slow pump/leak-mediated EIon oscillations . These slow oscillations yield dynamic firing thresholds that underlie complex voltage STO and bursting behaviors . Thus , Nav-CLS , a biophysically justified mode of injury , in parallel with functioning pumps , robustly engenders an emergent slow process that triggers a plethora of pathological excitability patterns . This minimalist “device” could have physiological analogs . At first nodes of Ranvier and at nociceptors , e . g . , localized lipid-tuning that modulated Nav midpoints could produce Nav-CLS , as could co-expression of appropriately differing Nav isoforms .
In any healthy sodium channel ( Nav ) -rich plasma-membrane , the bilayer is a far-from-equilibrium nanostructure that degrades wherever mechanical or chemical insult causes the inner leaflet to detach from adherent cortical cytoskeleton [1]–[4] . Severe insults cause readily-visualized rounded blebs of disordered , fluidized bilayer ( see Figure 1 ) , while milder damage causes intermediate degrees of disordered “bleb-like” injury [2] , [5] , [6] . Though many membrane proteins would be affected , Nav channels are overwhelmingly the key players in many excitable membranes , including nodes of Ranvier [1] . Positive-feedback Nav currents yield action potentials ( APs ) that dissipate Na/K gradients maintained by Na/K-ATPases so not surprisingly , membrane-damaging conditions ( e . g . , trauma , ischemia , muscular dystrophy ) that render Nav channels chronically leaky trigger excitotoxic cellular demise [3] , [7] . Pipette aspiration electrophysiology studies on Nav1 . 6-rich membranes ( patch-clamped Xenopus oocyte patches ) [8] showed that the aspiration-induced bleb-like injury causes “left-shift Nav-leak”; progressive aspiration damage irreversibly and progressively shifts the voltage midpoint of gNa ( V ) in the hyperpolarizing direction . When maximal disorder is reached , the irreversible shifting process “saturates” and any further aspiration-induced left-shifts are reversible ( see also [9] , [10] ) . Nav-availability depends on fast inactivation , a transition limited by fast activation [10] . Accordingly , damage causes equal-magnitude left-shifts for gNa ( V ) and availability ( V ) , thereby left-shifting the window conductance . The shifted steady-state ( window ) current constitutes a Nav-leak or abnormal “subthreshold persistent current” , the entity we describe as coupled left-shift ( CLS ) Nav-leak [11] . Pipette aspiration also causes irreversible Nav-CLS for Nav1 . 4 and Nav1 . 7 [12] , [13] ( preparation: oocytes ) and Nav1 . 5 channels [14] ( preparation: HEK cells ) . In hippocampal neurons , a Nav-CLS based window current left-shift occurs following metabolic insult from prolonged epilepsy-like stimulation [15] . Hippocampal neurons exposed to the industrial compound , melamine , also show Nav-CLS and exhibit hyperexcitability [16] . In neurons and muscle fibers , left-shift of Nav availability ( i . e . , steady-state inactivation ) [17] is reported for many damaging and/or toxic conditions ( see Table 1 of [3] ) and for membrane fluidizing conditions [18]; fast activation also becomes left-shifted in muscles ( e . g . [19] ) and neurons ( e . g . [20] ) . As predicted when membrane injury causes Nav-CLS [11] , sick excitable cell pathologies range from hyperexcitability through ectopic excitation to depolarizing block . Sucrose-gap voltage clamp of nodes of Ranvier subjected to ischemic and other insults could , we have suggested [3] , be used to test to what extent the initial Nav-leak of injured Nav-rich native membranes is explained by Nav-CLS . Injured-bilayer ICLS-window could help explain [3] why , invariably , clinical Nav inhibitors protective against excitotoxicity are lipophilic [21]; moreover , if bilayer structure matters , then retuning therapeutic strategies to better target channels in damaged bilayer could pay dividends [3] . Here , our goal is to understand in dynamical terms the mechanisms of abnormal steady-state excitability in membrane modeled with CLS-type injuries of various intensities . In particular , we wish to determine if – in conjunction with axolemmal Na/K pumps – CLS-injury predicts forms of abnormal excitability reported for “mildly” injured excitable cells , i . e . , cells that , with appropriate remediation , could be salvaged . In healthy unstimulated axons , quiescence is the norm and spontaneous firing is neuropathic and ectopic . Several recent studies involving simulation and dynamical modeling addressed abnormal or paroxysmal discharge in injured neurons . Injured DRG neuron simulations [22] showed that subthreshold oscillations ( STOs ) resembling ones recorded in vivo and relevant to neuropathic pain can be generated via depolarizing stimuli to a membrane with three distinctive gNas . Importantly , though , for STOs , the slower two gNas required first order , rather than the usual third order activation kinetics . We address this later . Similarly , for two Nav-type and two Kv-type conductances , Choi and Waxman [23] showed responses to current injection ( mimicking sensory input ) that included STOs with the spikes; there too , for STOs to occur , one of the gNas required first-order activation kinetics . STOs typically occur in conjunction with bursts of spikes , appearing in healthy neurons , ( e . g . , entorhinal cortex [24] ) as small Vm oscillations for a discrete range of conditions . Dynamically-speaking , STOs emerge where there is bistability between tonic firing and quiescence [25] . For allodynia-related neuropathic pain , a dynamical study of firing patterns showed EAnion changes having a key stability role [26] . Firing abnormalities of demyelinated axon were mimicked in a dynamical modeling study with fixed Nernst potentials and gNa/gleak ratios varied [27] . Regarding paroxysmal spiking , the same group [28] explored initiation and termination of afterdischarges and spontaneous activity; there , a non-inactivating gNa induced bistability and to mimic [ion] homeostasis following transient Na+-loading , an exponential decay provided a slow relaxation toward initial [Na+]intracellular . Käger et al [29] investigated epilepsy-like spontaneous bursting patterns and elevated [K+]extracellular , and Barreto , Cressman and colleagues [30] , [31] performed a dynamical study for oscillating [ion]s connected with epileptic seizures . Our Nav-CLS-based model of membrane injury uses a Hodgkin-Huxley axon without or with a Na/K pump as developed previously in [11] . That model focused on transitory responses to abrupt CLS “injury” ( left-shift intensity and the fraction of total gNa affected were varied ) and revealed how CLS-injury affects Vm ( t ) and ion homeostasis . Once the injured system ( no pumps ) stabilized , depolarizing current was applied , and based on spontaneous and stimulated behaviors , Nav-CLS injury activity was classified under various regimes ( Figures 5 and 9 in [11] ) . CLS-injury caused hyperexcitability , ectopic excitation or depolarizing block , and interfered with saltatory propagation of normal action potential ( AP ) traffic . Varying extracellular volume can significantly alter the quantitative measures of the bursting , consistent with a major role for pump activity . Unexpectedly , it was discovered that Nav-CLS in conjunction with pumps could generate STOs . Since injured neuron neuropathic pain discharge is characterized by diverse STO phenomena , we undertook the dynamical analysis of Nav-CLS injury presented here . We model acute injury: even in egregiously blebbed native membranes , Nav channels retain their ability to respond to voltage [32] , [33] . Keeping gNa-max constant corresponds to an absence of de novo Nav channel expression or membrane remodelling . Immunochemistry confirms an abundance of axolemmal Nav channels at damaged nerve-end neuromas , sites considered to be loci of ectopic excitation [34] . Our CLS-injury model is consistent with present views of voltage-gated channel structure/function [35]–[37] . Nav-CLS injury in situ would likely be of non-uniform intensity , a point we address computationally in several ways . Except for some instances of modified pump intensity , “impairment” refers exclusively to Nav-CLS . Na/K pump activity is sensitive to ATP levels , injury and bilayer lipid characteristics [38]–[40] , but how mild membrane injury would affect pump rates is unclear . So here we vary the maximal pump rate to explore its effect on tonic firing and bursting ( in this paper , both firing patterns are spontaneous ) . The diverse spontaneous steady-state rhythmic activity patterns that became evident in our injury scenarios are studied using bifurcation analyses . For mild CLS injury , a prominent and robust feature was the emergent slow process of pump/leak-mediated EIon oscillations [11] . As we will illustrate , these slowly oscillating EIon values cause time-dependent changes in the firing thresholds , which in turn will lead to complex spontaneous STO and bursting behaviors; the complexity of the observed patterns is further exacerbated by current noise . In summary , we study , via dynamical analysis , a simple , robust , and biophysically explicable model of mild axonal injury in which pumps remain functional , i . e . , we examine a collection of mild Nav-CLS injury scenarios . The major finding is that interactions between the window current based Nav-leak and Na/K pump activity engender slow oscillations of the Na+ and K+ driving forces that spontaneously trigger a plethora of known neuropathological excitability patterns . The following results are based on simulations of a Nav-CLS model of injured node described in the Methods section and in Table 1 which is a list of parameters .
Simulated nodes with Nav-CLS injury were shown [11] to exhibit activity regimes that include tonic and burst firing , plus a quiescent steady state . In this section we explore the node with simulated more nuanced versions of Nav-CLS injury and find that rhythmic firing combined with small-amplitude Vm oscillations are commonplace . We start with cases of constant [Ion] ( pump turned off ) , approximating axonal situations over brief times . We choose cases that provide snapshots of dynamics at selected fixed reversal potentials that could occur at different stages of injury . For fixed reversal potentials ( EIon ) we take three sets of values corresponding to different transmembrane Na+ and K+ gradients: ( i ) ENa = 50 mV , EK = −77 mV; ( ii ) ENa = 42 mV , EK = −77 mV when initial injury has elicited a change in INa thence [Na+]s; and ( iii ) ENa = 42 mV , EK = −71 mV . In this latter case , IKpump , because of its dependence on [Na+]s , changes , which results in EK changes . Nav-CLS intensities induced by membrane damage would vary within and between axons , as suggested in Figure 8 Aiii in [8] . To reflect this , three sets of LSi and fi are applied . To incorporate the idea of “smeared-out LS” , the fraction fi of the population are given a Gaussian distribution of LS with mean±SD of 1 . 3±0 . 4 mV , 8±1 mV and 15±1 mV . The numerical results are plotted in Figure 2 . For the first two EIon pairs ( i ) and ( ii ) ( left and middle columns ) , Vi dynamics in the injured node vary from quiescence to repetitive spiking , with the firing rate increasing and the spike amplitude decreasing as mean ( LS ) increases . However , for EIon pair ( iii ) ( right column ) , this node shows changes from STF at high amplitude ( again , with increasing firing rate and decreasing amplitude ) to a very low amplitude oscillation ( Figure 2I ) that shares features of subthreshold oscillations ( STOs ) . The question of what happens to the threshold for STF for these changes in EIon is raised by these results . The bottom row , panels J-K-L , displays the bifurcation diagram of the voltage excursions as a function of left-shift; the EIon values for each panel are those used in the three panels above it . For these diagrams , the left shift is the bifurcation parameter; all channels ( f = 1 ) assume this shift ( there is no spread , i . e . SD ( standard deviation ) = 0 ) . Each diagram is constructed by choosing a value of LS , running a simulation , letting transient behavior die out , then measuring various characteristics of the steady-state voltage solution . In particular , here we measure the value of a fixed point ( resting potential , RP ) or the minimum and maximum values of a Vm oscillation . This procedure is repeated over a range of LS values , and the characteristic values are plotted against LS . As LS increases , we see in panels J , K , and L a Hopf bifurcation ( HB ) i . e . a transition between a stable resting potential ( RP ) , or in the diagram , stable fixed point , and tonic firing . Further , there is a narrow range of LS where both RP and tonic firing coexist; this is known as a “subcritical” HB . Subcritical HBs are seen on the left part of each diagram , and on the right part of diagrams J and K . In panel L however , the right part displays no such coexistence , and the HB is “supercritical” . This means that as LS increases further , there is an abrupt ( although continuous ) transition from tonic firing to RP . Upon decreasing ENa ( panels J to K ) , the threshold moves to higher LS values , and the spike height is reduced . However , when EK is reduced ( panel L ) , the threshold moves to a lower LS , which explains the onset of firing in panel C . The decrease of the repolarizing current also continuously raises the minima and lowers the maxima of the voltage excursions . This underlies the trend to low amplitude spiking behavior ( cf . panels C→F→I ) . Thus , in axons where injury has caused Nav-CLS and is fostering gradual rundown ( depletion ) of the ion gradients , a range of abnormal excitability patterns could be expected to appear then disappear . Note that the mean LS in Figure 2I corresponds to the limit cycle regime ( Figure 2L ) – although it is very close to the fixed point ( quiescent ) regime which is to the right of the supercritical Hopf bifurcation in Figure 2L . This is why the spike amplitude is so small – but technically they are still spikes , not STOs; this would be the case even if the Hopf bifurcation were subcritical ( as in the right part of Figures 2J and K ) . There is no injected current here , and the system can generate tonic firing of low amplitude spikes , so we cannot speak of depolarization block . However , depolarization block can be produced by injecting a current of sufficient magnitude ( not shown ) . Since the EIon are controlled by intra- and extracellular [Ion]s ( Eq ( 13 ) ) which in turn depend on pump currents via Eq ( 10 ) , these results imply: a ) Ipump will substantially affect excitability at injured nodes [41] , and b ) in the presence of a small rundown of the K+ gradient , Nav-CLS is sufficient to produce STO-like voltage excursions . We will see in the two sections on bursting below ( Bursting in injured nodes and Bifurcation analysis of bursting ) that these excursions and STOs share a common origin . Whereas the transition from quiescence to tonic firing when EK moves closer to zero ( Figure 2B to 2C ) is expected , since the move causes a small depolarization , the appearance of STO-like excursions ( Figure 2H to 2I ) is less intuitively obvious . To better understand how pump current affects the emergence of small oscillations , we simplify the above multiple Gaussian-distributed gNa populations by forming two subpopulations: LSi = [0 , 15]mV and fi = [0 . 5 , 0 . 5] , signifying that half of Nav channels have no shift , and the rest have a 15 mV CLS . This choice for gNa populations is taken from the tonic firing regime ( Figure 9B in [11] ) that occupies the largest part ( ∼40% ) portion of the LS/f plane depicting five spontaneous activity regimes of injured nodes . We turn on the Na/K pump and mimic injury to pump function by varying the parameter Imaxpump in Eq ( 10 ) . Imaxpump is a functional maximum , a rate that , as per Eq 13 would only be attained for [K+]o = 0 and [Na+]i = 0 ( unrealistic in living systems ) . It differs among axons [42] and will vary with the cellular surface area , Na/K-ATPase density , bilayer lipid composition [39] , [42] and fluidity [43] , and temperature [44] among other factor [45] . Importantly , Imaxpump can be reversibly decreased experimentally by specific inhibitors ( e . g . strophanthidin , ouabain ) . Figure 3 demonstrates that when Imaxpump falls from 95 to 30 µA/cm2 , repetitive AP activity ( dotted line ) is replaced by tonic low-amplitude Vm oscillations ( solid line ) . While the Vm -oscillation amplitude increases as Imaxpump increases ( Figure 3D ) , the firing rate decreases . This suggests that , if Ipump were to decrease , repetitive APs could change to STOs . Inhibiting the Na/K pump can further lead to a complete cessation of firing . This is in general agreement with experimental results [42] . It is noteworthy that because [Na+]i and [K+]o ( Eq ( 10 ) ) limit maximal pump current , the upper values of Ipump are considerably less than Imaxpump . In Figure 3B , e . g . , with Imaxpump at 95 µA/cm2 , Ipump fluctuates around 22 . 7±0 . 5 µA/cm2 . The section Effects of varying maximal pump current discusses the impact of Imaxpump on the bursting regime . After repetitive firing activity , the electrogenic Na/K pump mediates the restoration of the ion gradients on a relatively slower time scale . Figures 2E and 2F suggest that pump current , by driving EIon changes , could also induce patterns of bursting in which volleys of high-amplitude spikes are separated by periods of low-amplitude STOs . In this section we pursue this idea by simulating nodes with three gNa populations ( LSi = [26 . 5 , 2 , 0]mV and fi = [0 . 2 , 0 . 08 , 0 . 72] ) and Imaxpump set at 95 µA/cm2 . In Figure 4A a node injured this way produces bursts of spikes separated by STOs . The silent and active phases of such bursts are associated with pump current dynamics and the left-shifted window conductance ( m3 h ) . In the silent phase where Vm is near the RP ( −60 mV ) , the Nav-CLS channels are a “leaky” Nav component ( Figure 4B and 4C ) flowing into the injured node , but without depolarizing it above firing threshold , because outward INapump slightly exceeds the inward sodium current ( the sum of INa and INaleak ) . The result: Vm is destabilized and STOs develop . INapump keeps decreasing ( Figure 4Aii ) , becoming less than inward sodium current at about the time marked ( pink star ) in Figure 4Ai . Therefore Na+ accumulates inside and K+ outside the node , resulting in ENa and EK changes , based on Eq ( 13 ) . When changes in EIon further reduce the firing threshold ( system dynamics will be explained in the following section ) the injured node would cross the diminished threshold and produce APs . With the consequent [Na+]i increase , INapump starts increasing . It eventually prevents the node from crossing the threshold and APs cease ( green dot in Figure 4Aii ) and Vm falls back to the STO state around the RP . Repeated switching between clusters of spikes and STO intervals constitutes a form of bursting behavior that , given the involvement of the pump , should be sensitive to the surface to volume ratio , as per the numerical results of Käger et al [29] . With intracellular and extracellular nodal volumes tripled ( Voli = Volo = 3×10−9 m3 ) and the surface area fixed ( 6×10−8 m3 ) ( Figure 4D ) , bursting period ( BP – from the beginning of one burst to the beginning of the next ) and burst duration ( BD ) ( Figure 4Ai ) are prolonged . This confirms that , for the Nav-CLS model of injury , both the burst parameters are indeed sensitive to the surface-to-volume ratio . Interestingly , the solutions in Figures 4A and 4D do not exactly repeat . The number of spikes during the active phase of the burst varies slightly among bursts . Additionally , missed spikes at the end of the burst phase relate to the existence of period-doubled solutions ( PD ) as we will see in Figure 5C . Even though below we characterize them by an approximate bursting “period” , BP , these solutions are likely chaotic . As seen above , bursting is followed by quiescence and STO's are observed at the onset and offset of bursting . We now expose the dynamical structures underlying these behaviors . During firing , the ion gradients are slowly depleted due to the window current in the injured node . The pumps cannot compensate for the loss , and ENa and EK move towards zero . During quiescence the pumps replenish the concentration gradients , and the absolute values of ENa and EK increase . Spontaneous rhythmic bursts in Figure 4A are shown three-dimensionally in Figure 5A with dynamic ( i . e . time-varying ) EIon . A bifurcation analysis based on a decomposition of the full dynamics into slowly and rapidly changing variables ( e . g . EIon and Vm respectively , Figure 5B and 5C ) helps identify the burst mechanism . This is known as a slow-fast decomposition ( [24] and references therein ) . We first focus on the initial phase of the burst ( e . g . pink star , Figure 4A ) . For now , EK and Ipump are regarded as fixed , i . e . as constants taking their ( arbitrarily chosen ) values at the pink star ( −83 . 17 mV , 14 . 96 µA/cm2 ) . We pick a value of ENa , run a simulation , wait until transients die out , and measure the minimum and maximum values of Vm . This procedure is repeated for the range of ENa values on the abscissa of Figure 5B . On the ordinate we plot the corresponding minima and maxima of Vm . A striking feature is that in certain regions of the diagram there are more than two ordinate values; this is a hallmark of bistability as discussed further below . Since ENa = 40 . 2 mV at the pink star , the diagram demonstrates that the CLS injury places the system in a superthreshold oscillation ( i . e . spiking ) regime . The spiking trajectory at the pink star in Figure 4A and 5A corresponds to the stable limit cycle ( i . e . , stable periodic oscillation ) in Figure 5B . At the onset of firing ( pink star in Figure 5A ) , the pumps are still driving ENa upwards and past ( i . e . to the right of ) the Hopf bifurcation point ( see Figure 5B ) . In that region , the fixed point , around which the STO oscillates , has become unstable; the trajectory moves towards the only possible stable state , a stable limit cycle corresponding to repetitive firing ( APs ) . During firing ENa is decreasing and consequently this limit cycle shifts to the left and approaches the bistability regime . During this process , both amplitude and frequency of the limit cycle decrease . In the bistability region of Figure 5B , the system has two stable states: a steady fixed point or resting potential ( i . e . RP , marked by solid line ) and a superthreshold oscillation ( i . e . APs , or tonic firing ) . Between these states is an unstable limit cycle . The system phase space is then split into two sets of points . In the first set , typically near the RP , phase space solutions converge to the RP . In the other , typically further from the RP , solutions converge to the tonically firing solution . In both these sets , initial conditions close to the unstable limit cycle yield solutions that diverge away from it in an oscillatory manner: in the first set the oscillation grows into the tonic solution , and below , oscillations damp out towards the RP . Further , a perturbation from the RP must “jump over” this unstable limit cycle in order to lead to tonic firing , and vice-versa . Near the offset of firing ( green dot ) , with ENa still decreasing , the dynamics move toward a region of period doubling ( PD ) . Sometimes the trajectory falls off the limit cycle on the upper branch before reaching this region such as in Figure 5C . Other times during the same solution the trajectory enters briefly into the period doubling regime . This manifests itself as a longer interspike interval at the end of the firing phase ( see Figure 4A , second burst ) . For parameter choices corresponding to bursting the trajectories are not periodic , i . e . they appear to be chaotic unless the transients exceed our simulation times . The precise dynamics in this region warrant more extensive investigation beyond the scope of this paper . Note also that the AP amplitude decreases together with ENa . This is expected as the ion concentration gradients drive the action potential . This suggests that the upper branch of the PD regime is not reached by the trajectories near firing offset . Let us inspect Figure 5 in more detail . Figure 5A shows that both ENa and EK are dynamic , changing slowly during a bursting period . Figures 5B and 5C capture the behavior of the system near the two transitions ( pink star and green dot ) in Figure 5A . The pink bistability region in Figure 5B – corresponding to the pink star – sits between a limit point ( LP: where a “saddle-node of limit cycles” bifurcation occurs ) , and a Hopf bifurcation point ( HB: where a transition between a stable fixed point and a stable limit cycle occurs ) . The green region in Figure 5C lies between ( at left ) an area ( PD ) of complex dynamics where many period-doubling bifurcations occur and ( at right ) a HB . The unstable limit cycle solution ( marked by open dots ) between the stable fixed point and stable limit cycle is the aforementioned threshold boundary . The arrow in Figure 5B shows the direction in which ENa changes during the firing phase ( EK changes as well ) . Likewise , the blue arrow in Figure 5C shows how ENa changes during the STO phase . During the bursting period , the bifurcation diagram in Figure 5B slowly morphs into the Figure 5C diagram and back . These two diagrams , snapshots of the system's possible steady state behaviors at the two ends of the bursting cycle , help us understand how the whole solution plays out during an entire bursting cycle . Interestingly , from Figure 5B one might think spiking would continue until the point LP is reached , where ENa is almost nil . However , the pump's dependence on [Ion]s limits this decay , such that a PD region appears and truncates the spiking phase at a relatively large value of ENa ( note the difference in ENa scales in Figure 5B and 5C ) . The two-parameter phase diagram in Figure 5D provides a view of the burst dynamics from the EIon perspective . Here the pink star and green dot have the same meaning as in Figure 5A–C ( see caption ) . The black loop connecting pink star to green dot is the projection of the 3D trajectory in Figure 5A onto the ENa−EK plane , and displays the ENa and EK trajectories during bursting . The solid and dashed curves are , respectively , sets of all the LP and HB points for the range of EIon of interest ( exemplars of these points were seen in Figure 5B , C ) . The area bounded by them is the bistability regime . This involves computation of many bifurcation diagrams along the entire bursting trajectory , choosing from the trajectory the two extremal pump values ( pink for the lowest and green for the highest ) . One can imagine that , when the system state moves from pink star to green dot , the periodically varying Ipump pushes the bistability regime between the pink-curve-bounded and green-curve-bounded areas . Thus , injured node dynamics switch between different modes , resulting in bursting behavior . Various spontaneous activities of an injured node with three gNa subpopulations ( LSi = [26 . 5 , 2 , 0]mV ) comprising different fractions are presented in Figure 6A . The fractions ( f1 and f2 ) corresponding to the Nav-CLS populations form the x- and y- axes; the fraction of intact channels is simply f3 = 1−f1−f2 . When the percentage of channels with deeper injury ( i . e . LSi = 26 . 5 mV ) increases , the state of the injured node goes from RP→bursting→bistability ( APs or RP , depending on the initial condition ) → tonic firing→bistability→RP . For two random points from the burst and bistability regimes , Vm is plotted in Figures 6B and 6C , respectively . Overall , STOs can arise from various combinations involving decay to or growth away from RP , but the particular behavior seen depends sensitively on the percentage and degree of injury . Neuronal noise arises naturally from a wide variety of sources including channel noise , synaptic noise , electrogenic ion pumps , and thermal noise . In this subsection we investigate the influence of current noise on spontaneous electric activity of a node with Nav-CLS injury by including a simplified Gaussian white noise σξ on the right side of Eq 1 as an additive term . This additive noise ξ has zero mean , and its autocorrelation function is <ξ ( t ) ξ ( s ) > = δ ( t−s ) where δ ( · ) is the Dirac delta function; σ is the noise strength ( in µA/cm2 ) . For a node , the white noise can be taken as describing conductance and thermal noise . By definition it has equal power at all time scales , in particular beyond the fastest time scales present in our deterministic ( i . e . noiseless ) node model . Furthermore , because the central limit theorem applies to the sum of different independent fluctuation sources acting on Vm , its amplitude distribution is assumed to be Gaussian ( see for instance , [46] ) . For a deterministic bursting activity with burst period BP = 10 . 2 s illustrated in Figure 6B , additive noise dramatically decreases BP ( Figure 7A ) . It also makes BP irregular because the crossing of the threshold by the Vm trajectory is now a probabilistic process , especially in the vicinity of the threshold [47] . When the node operates in a bistable regime , as in Figure 6C , this additive noise causes stochastic switching between the quiescent and tonic firing modes ( Figure 7B ) ; noise-induced bursts appear . In fact , the injured node produces bursting in both the burst and bistability regimes of Figure 6A . With higher noise intensity , the mean BPs of noise-induced bursts is shorter . Such bursting is also referred to as noise-induced mixed-mode oscillations [48] . This phenomenon has been found in experimental settings , for example the bistable squid giant axon [49] , electroreceptors of paddlefish [50] and entorhinal cortex neurons [51] , as well as in excitable neuron models such as the Hodgkin-Huxley model [49] , the FitzHugh-Nagumo model [48] , and an excitable spine model [52] . The expanded sections in the right column of Figure 7 demonstrate that , upon introduction of noise , the silent phase of the burst behaviour in Figure 6B and the steady state in Figure 6C turn into STOs . This is observed in injured primary sensory neurons [53] , and constitutes coherence resonance ( CR ) ( or autonomous stochastic resonance ) wherein noise alone excites subthreshold oscillatory responses in excitable systems ( see [47] , [54] and references therein ) . Noise continually modifies the firing pattern because it randomly pushes the system into and out of different regions of phase space , - similar behavior has been described for thermoreceptors [46] . In terms of Figure 5C , when the system is on the lower STO branch , the noise induces the behavior seen at the nearby Hopf bifurcation . In summary , for our Nav-CLS system , noise can elicit a random mixture of the behaviors seen in the phase diagram in Figure 6 . Next , we explored the spontaneous activity of an injured node with different Nav-CLS variances . Gaussian distributions of Nav-CLS were imposed with different means and standard deviations ( SDs ) . As illustrated in Figure 8A , we tested mean ( LS ) = [0 . 5 , 1 , 2 . 5 , 5 , 10 , 20 , 27 , 30 , 20]mV with corresponding SD ( LS ) = [0 . 2 , 0 . 4 , 5 , 5 , 5 , 5 , 5 , 5 , 10]mV . With increased injury intensity ( greater mean ( LS ) ) , the Vm changes are dramatic ( Figure 8 ) . There is a progression from quiescence ( B ) →bursting ( C–D ) →tonic firing ( E–G ) →bursting ( H ) →quiescence ( I ) . For a smeared Nav-CLS injury as small as LS = 1±0 . 5 mV , the node generates bursts ( BP = 35 s ) , indicating this system's extreme susceptibility to even small changes in window current . ( Left-shifting Kv activation by an equivalent amount [11] does , however , provide some stabilizing protection for Vm ) . A slightly larger trauma ( mean ( LS ) = 2 . 5 mV ) shrinks BP dramatically to 0 . 78 s , then further increasing mean ( LS ) leads to tonic firing . If , however , mean ( LS ) is taken to 27 mV ( Figure 8H ) , bursting with STOs ( not visible ) returns . Then , for mean ( LS ) ≥30 mV no spiking occurs . In Figures 8C , D , H the within-burst firing rate and Vm excursions decrease with time . In Figures 8E–G the instantaneous within-burst and tonic firing rates gradually increase with mean ( LS ) ( Figure 8K ) . The corresponding mean Vm excursions decrease with increased mean ( LS ) ( Figure 8L ) . With a smear of Nav-CLS that encompasses a wider range of LS values ( SD = 10 mV: Figure 8J; see Figure 8A ) ) , the injured node fires tonically , as in the lower SD case for the same mean ( LS ) ( Figure 8G ) . Evidently the larger LS components of the SD = 10 mV distribution do not sufficiently dominate to yield the type of quiescence associated with a ( smaller SD ) 30 mV LS ( Figure 8I ) . In Figure 3D we saw that decreased Imaxpump suppresses spontaneous tonic firing with CLS injury . In Figure 9 we look at the effect of varying the pump activity on bursting patterns in a mildly injured node ( LS = 2 . 5±0 . 5 mV ) . Imaxpump = 95 µA/cm2 ( the value used in Figure 9C ) is our standard or healthy cell reference . Imaxpump depends on the density of pump expression in the membrane , which will differ among axons and also for different regions of a given axon . It also varies with a multitude of factors , including injury conditions that affect the turnover rate at individual pump molecules . To explore these possibilities in a mildly injured node , we varied Imaxpump over a wide range below and above the standard value in Figure 9C . Figure 9B shows that a lower Imaxpump is associated with longer interburst intervals ( IBI: see Figure 4 ) than for the standard case ( Figure 9C ) . Figure 9A , an extreme example in which excitability is lost , has an infinite IBI . Increasing Imaxpump , by contrast , initiates burst of spikes and shortens both burst duration ( BD ) and burst period ( BP ) ( Figure 9D , E ) , reflecting the hyperpolarization produced by the electrogenic Na/K pump . The differences between Figure 9B and 9C are consistent with experimental observations in rat spinal interneurons where , during the course of pump blockade , the burst rate decreases ( larger BP ) [42] . It is noteworthy that for the uninjured system , varying maximal pump current had little impact on the steady- state Vm ( see Table 2 ) . What vary substantially are the steady state EIon . This is consistent with the mechanistic interpretation that Ipump oscillations responding to chronic Nav-CLS-based Nav-leak underlie the array of bursting patterns in the many simulations above . The basic phenomena ( ectopic APs and STOs ) are extremely robust properties of nodal membranes with mild Nav-CLS and a pump , and appear in various manifestations without the need to invoke novel conductances or Nav channels with peculiar kinetics . Unlike nodes , somata express multiple Nav isoforms , and in recent modeling work of injured somata , Kovalsky et al [21] showed that a system with three distinctive gNa sub-types ( but no Kv and no Na/K pumps ) yields STOs , provided the two slow gNa sub-types are given 1st rather than 3rd order activation . This provided the system with the “several delayed components” needed to mimic the repertoire of STO-triggered phenomena of live neurons . To simulate Nav1 . 7 and Nav1 . 8 interacting in a fashion that elicits STOs , Choi and Waxman [23] also depicted one of the gNa sub-types with 1st order activation . Interestingly , in our system , left-shifting a fraction of the m3 h-based Iwindow acts like introducing a lower order activation process ( see Figure 10 ) . What physical change in injured axons that could yield such pseudo-first order m∞ ( V ) curves for total gNa , even though individual channels continue to exhibit their normal m3 activation ? Heterogeneity in the extent of bilayer damage could cause this by fluidizing a fraction of the nodal bilayer . This would yield a subthreshold persistent INa . Differences in bilayer packing in different parts of the membrane [3] , [36] also arise developmentally in some circumstances . In a given region of plasma membrane , a membrane remodeling process that places some Nav channels in ( say ) cholesterol-poor [55] and others in cholesterol-rich subdomains could , in principle , create or “tune” physiologically useful subthreshold persistent currents .
Regions of membrane with mild Nav-CLS have a “subthreshold” persistent gNa ( a Nav-leak conductance ) due to gwindow operating abnormally close to the cell's normal resting Vm; when only a small fraction of Nav channels are affected , the cell's gwindow plot has a shoulder as in Figure 4C; such plots strongly resemble coupling-induced subthreshold persistent conductance of pacemaker neurons [56] . Like that physiological pacemaker , our injury model includes no slow mode ( or non-inactivating ) gNa . Calculations [3] show , in any case , that at voltages near typical AP thresholds , left-shifted Iwindow would dominate over equivalently left-shifted non-inactivating INa . In much of this study , we mimicked “smeared” extents of bilayer damage via Gaussian distributions of Nav-CLS , reflecting the notion that nodal axolemmal injury is unlikely to exhibit a unique intensity . Smear , though expected in situ [2] , [8] , is not actually required for neuropathic activity . Use of assorted smears confirmed that CLS-fuzziness in no way abrogates dysfunctionality and it demonstrated the robustness of Nav-CLS as a model for leak . Nav-CLS injury thus provides a minimalist explanation for multiple spontaneous modes of firing in which APs , bursts and subthreshold oscillations ( STOs ) occur in various patternings . In severe cases , it also predicts depolarizing block [11] . We used bistability diagrams and various bifurcation analyses to help clarify the mechanistic underpinnings of the Nav-CLS-induced dynamics . A mildly injured excitable cell cannot survive for hours or days ( the time course , e . g . , of diffuse axonal injury ) without operational Na/K pumps . In electrical models of axon injury , pumps do not only maintain ion gradients , they also contribute to slowly varying excitability patterns of the damaged-but-viable axons [11] , [29] , [30] . Pursuing this further here , we found the following: mild Nav-CLS induces STOs through a gradual reduction of firing threshold mediated by slow EIon dynamics whose characteristic times depend on pump-mediated fluctuations of extra- and intracellular ion levels . Threshold voltages for firing are not fixed but depend on EIon . EIon fluctuations induced by Nav-CLS produced , in a bistable fashion , both STOs and bursts of full-sized APs . With mild Nav-CLS injuries , adding Gaussian white noise to the current-balance equation induced erratic bursting , or , where injury was already causing sustained bursting , noise influenced the rates and durations of the ectopic signals . These effects of noise are consistent with those seen in a recent computational study of neuropathic firing in a hyper-excitable system with more ion channel species than used here , but without pumps [57] . In the following we discuss and provide more context for the above results . Trauma-induced [58] and ischemia-induced [59] Nav leak triggers Ca2+-excitotoxicity , the proximate cause , in diffuse axonal injury and oxygen glucose deprivation , of axon demise . A mechanistic understanding of early stages of Nav channel dysfunction , when salvage is possible [60] , is needed . Although pathological TTX-sensitive Na+ leaks are attributed to increased “persistent INa” ( e . g . [61] , [62] ) or slow-inactivating INa [63] it is not known how membrane damage elicits chronic Nav-leaks . A molecular-level understanding is lacking as to what constitutes leaky native Nav channels . A common Nav-leak culprit in diverse sick excitable cell conditions is , we propose , Nav-CLS [3] . For recombinant Nav1 . 6 , this phenomenon occurs as an immediate consequence of mechanical membrane damage [8] , [11] . Any fraction of Iwindow ( an attribute of fast gNa ) that has become left-shifted acts as a leak [3] , [8] that could trigger positive feedback excitation . In previous modeling [11] , we established that mild axonal Nav-CLS would effectively dissipate [Na+] gradients , bringing on excitotoxicity . Total nodal gNa was modeled by an intact fraction plus a second fraction with a discrete level of CLS . Various “Nav-CLS injuries” were imposed , Vm ( t ) was plotted as new steady-states were attained , then excitability was probed with current injection . Mild Nav-CLS caused spontaneous APs ( tonic or damped trains ) . With Na/K pump activity included , it caused AP bursts whose specifics varied with compartmental volumes . From temporal patterns of [Na+] gradient rundown , it was evident that Nav-CLS type injuries could cause axon demise by overwhelming an axon's capacity for ion homeostasis . Injured nodes , moreover , generated pernicious ectopic signals and impaired transmission fidelity during saltatory propagation . Pathological activity patterns , plotted as a function of the extent ( in mV ) of Nav-CLS , and of the fraction ( 0–1 ) of affected nodal Nav channels , fell into several regimes . What can we infer about responses to stimulating inputs when there is Nav-CLS injury ? Effects of stimulation , a multi-faceted issue , was addressed for nodes with fixed reversal potentials in a preliminary study [11] involving two Nav populations , one intact and one with a specified CLS injury . Spontaneous firing occurs over a range of damage , then beyond a critical threshold level ( LSc ) the system is quiescent . Stimulating with constant current yields a larger maximal firing rate but , due to depolarizing block , quiescence occurs with less damage ( LS<LSc ) . Effects of stimulation are currently under study for bursting nodes ( model with pumps as in Figure 5 ) . Because bursting is a globally attracting behaviour , a single spike as a form of input may transiently change a bursting cycle but not its steady state . For the regime we considered , bifurcation analysis reveals that a single spike cannot “trigger” bursting behavior . Though ectopic signals in vivo are generated at both axons and somata [64] , peripheral neuropathic ( as distinct from nociceptive ) pain mechanisms are mostly studied via ectopic activity in damaged somata such as those of primary mechanoreceptor afferents [62] , [65] , [66] . A closely-related issue of relevance here is that of low threshold afferents , dubbed “algoneurons” [67] . These are non-pain sensory neurons that can serve double functions , signalling pain only when peripherally hypersensitized due to trauma , inflammation and the like . Spontaneous activity patterns described here are like those of both damaged mechano-afferents neurons and hypersensitized algoneurons . This is a post hoc assessment; we monitored behaviors across parameter space , but did not adjust parameters to mimic particular neuron activities . Clearly , it would be interesting to determine if “hypersensitization” in algoneurons corresponds to Nav-CLS in damaged peripheral endings . Emerging from that “injury”-modified Hodgkin-Huxley axon ( two gNa sub-populations and the Na/K pump ) was a critical feature of the electrical dysfunction of injured excitable membranes , abnormal STO phenomena [11] . We lacked , however , a dynamical understanding of the phenomenon and its robustness; given the prevalence of STOs in neuropathic firing ( plus physiological correlates ) this represented a significant gap . Typically , STOs and injury have been modeled with non-inactivating and/or slow-gating gNa . Our model - Nav-CLS - includes only a fast-gating gNa to which a simple biophysically-justified ( and biophysically-explicable ) modification has been applied at varying intensities . Here , using smeared-intensity versions of Nav-CLS to model injury , we generated diverse STO phenomena . The “spared but impaired axons” of injured tissue are targets for Nav antagonists ( see [21] ) and such mildly-injured axons were our focus here . We examined sustained spontaneous ( ectopic ) behaviors , extending our analysis first to three gNa sub-populations ( i . e . , for otherwise identical gNa mechanisms , the Nav population was given three extents of Nav-CLS ) , then to various Gaussian-distributed ( “smeared” ) Nav-CLS populations . Realistically untidy , but conceptually simple , all these Nav-CLS injury variants exhibited the key components of the injury repertoire . STOs arise with ( Figure 8D ) or without smear . Along with the basic spontaneous activities ( APs and bursts ) , injured nodes spontaneously produced sustained STOs ( Figure 3 ) and STOs as parts of bursts consisting of clusters of spikes and STOs ( Figure 4 ) . Na/K pump turnover rates are sensitive to substrate concentrations , membrane potential [68] and lipid packing [39] , [40] . Quiescent ( “at rest” ) axons maintain a steady basal pump activity that counteracts all system leaks . In our model Ipump is always substantially smaller than INa and IK ( ∼22-fold in Figure 4A ) and pump rates oscillate significantly more slowly than APs ( e . g . , Figures 8C , D , ∼2 orders of magnitude slower ) . In our simulations of injury , small amplitude slowly oscillating Ipump plays an essential role in mediating spontaneous Vm excursions ( Figures 3 , 4 and 9 ) . Larger magnitudes for Imaxpump ( see Figure 3D and Figure 9 ) accelerate the efflux/influx of Na/K ions . This was associated with dynamical changes , from RP to STOs to bursts or tonic APs . Figure 3D in particular is a bifurcation diagram; it characterizes the transition from quiescence to tonic firing as Imaxpump increases . This shows clearly the increase in the amplitude of voltage excursions Vm and the decrease in firing rate . Figure 9 shows the effect of Imaxpump in the bursting regime . As Imaxpump increases , we go from quiescence to bursting . All characteristics of the burst summarized in Figure 4 shorten with this increase . In the injured nodes , therefore , a reduced Imaxpump ( due , say , to ATP depletion and/or to a more fluidized pump-embedding bilayer ) would modify ectopic excitation patterns . In line with this , in endogenously bursting snail neurons , inhibiting the pump shortens burst periods and increases spike frequency [69] , though unlike injured nodes , pacemaker neurons have multiple slow processes that confer resilience on specific oscillatory patterns . Dynamic transitions of Ipump are seen in a number of rhythmically active cells including sinoatrial node cells [44] and trigeminal motoneurons [70] . Insofar as Na/K pumps show greater ATPase activity in membranes with greater lipid packing order [39] , [40] , membrane injury that caused Nav-CLS should simultaneously impair pump activity . To better understand ectopia arising from injured nodes or axon initial segments , it would be helpful to know if Na/K pump inhibitors ( e . g . ouabain , but also generic membrane fluidizers [43] , [71] ) reduce ectopic burst firing in mildly damaged axons . In this regard , we note that peripherally-applied ethanol ( shown recently to inhibit neuronal Na/K–ATPase [72] ) induces a “feeling no pain” condition when injected locally to relieve peripheral trigeminal neuralgia [73] . Although neuropathic STOs trigger APs in many neurons [58] , [74] , STOs are not principally a neuropathic phenomenon . In the CNS [75] , STOs are a filtering mechanism by which neurons decode oscillatory inputs from other neurons in a frequency dependent manner [76] . Disparate underlying mechanisms for STOs have been noted , including Ca channel Iwindow [77] and HCN-channel based Ih [75] , and , of particular interest here , a fast gNa-based [56] subthreshold persistent INa [78] ) . Our mild Nav-CLS-based Iwindow resembles that mechanism , but generates STOs and AP bursts only in conjunction with the electrogenic pump . STOs arising spontaneously at nodes are , by definition , pathologic , and given the dominance of nodal conductances by gNa ( specifically , Nav1 . 6 channels ) would likely be simpler in nature than the STOs elicited ( by current stimulation ) in multi-Nav isoform sensory neuron somata [21] or in double-Nav nociceptive terminals [23] . STOs simulated here involve a small-amplitude rhythmic mechanism that develops with mild Nav-CLS Iwindow ( Figures 3 and 4 ) operating near what would normally be the RP level . Bifurcation analysis of this system enables us to propose that slow dynamics of the firing threshold are responsible for the timing of spikes . In a system where the EIon vary , the firing threshold varies too , gradually decreasing in the interval between successive STOs ( Figure 9 ) . This is broadly consistent with experimental findings of a decreased spike rheobase in injured dorsal root ganglion neurons [79] and , more general terms , seems consistent with the injury-induced hypersensitization of algoneurons [67] . Models involving fixed EIon cannot exhibit spontaneous oscillations of firing threshold , but in vivo , and especially in fine processes ( e . g . , Nav-rich nociceptive endings ) , fluctuating [Ion]s and pump currents are expected once channels activate . Analyses of the electrical excursion diversity seen in excitable cells gradually going through their death throes have , historically , been fruitful in providing sketches of the behavioral diversity of healthy excitable cells . For example , the Hodgkin [80] classification of various spiking behaviors in isolated crayfish axons and the Morris-Lecar [81] analysis of giant barnacle myocyte voltage oscillations provide the springboard for analytical descriptions of oscillatory types in mammalian interneurons [82] . Here we simulated sick cell behaviors in a context where large fluxes into small volumes made it crucial to include the contributions of the electrogenic Na/K pump . From this emerged an STO mechanism that triggers bursts of spikes in a manner not , to our knowledge , previously recognized , i . e . , the oscillating threshold . Since threshold occurs at Vm values where fluxes unbalance , threshold varies with EIon variations . An ultra-simple biological exemplar of this point is a gCa-based biphasic AP ( Figure 3c of [83] ) that shows different thresholds for its depolarizing and hyperpolarizing excursions and that is modeled simply by letting [Ca2+]intracellular accumulate with gCa activation ( Figure 3d and Equation ( 8 ) of [81] ) . Here we explicitly considered injury-induced Nav-CLS in a setting where Nav1 . 6 would be the exclusive Nav isoform . But Nav-CLS may have resonances for healthy excitable membranes with two or more Nav isoforms with different voltage midpoints , such as seen in axon initial segments [33] and nociceptive nerve endings [23] . Moreover , even with a single isoform , non-homogeneous physiological modulation ( e . g . , from inhomogeneous lipid packing density ) could yield CLS-like situations that might affect tuning ( e . g , . in the cochlea [83] , [84] ) . As in vivo lipid imaging becomes refined , it may be possible to detect lipid-packing changes before and after injurious stimuli at nodes or axon initial segments . This is important given that the activities of voltage-gated channels and the Na/K pump are both modulated by lipid packing [37] , [39] . The kinetic phenotypes of the membrane proteins simulated here are , of course , constrained by amino acid sequence , but they also vary according to the bilayer mechanical milieu . Our work here suggests how , in the face of bilayer injury , the sensitivity of Nav channels to bilayer mechanics can be perilous . By the same token , it may spell opportunity , with developmentally controlled CLS-type kinetic modulations spawning behavioral amplifications beyond what would initially be expected from a limited set of membrane proteins .
Axonal voltage excursions are modeled at an individual node of Ranvier with the Hodgkin-Huxley model [85] using the values listed in Ochab-Marcinek et al [86] . We start with the basic equation for membrane potential ( Vm ) : ( 1 ) where C is the nodal membrane capacitance . The total INa for all Nav channels and the potassium current IK are given as: ( 2 ) ( 3 ) and are the maximal conductances of the Nav and Kv channels , respectively; ENa and EK are the sodium and potassium reversal potentials , respectively; and n4 gives the steady-state open probability of potassium channels . By the HH formulation , gating variables m , h , and n evolve according to: ( 4 ) ( 5 ) ( 6 ) The forward ( and ) and backward rate functions ( and ) describe the first-order transitions between the deactivated and activated states of activation ( m ) and inactivation ( h ) processes in Eqs ( 4–5 ) . They are determined by the membrane potential Vm: ( 7 ) The rate functions αn and βn of potassium gating variable n in Eq ( 6 ) also depend on Vm: ( 8 ) Experimental findings for recombinant INa from nodal type Nav1 . 6 channels [8] show that , with mechanical membrane damage ( “injury” ) , transient INa at a given Vm irreversibly accelerates because the activation and steady state inactivation ( availability ) processes undergo irreversible hyperpolarizing ( “left” ) -shifts . Consistent with this , the steady-state product of activation and availability ( m3 h ( Vm ) t→∞ ) , also called the window conductance , also left-shifts . This injury response we term “coupled left-shift” ( CLS ) . This CLS can be easily modeled within the above HH model by shifting the voltage dependences of the activation ( m ) and inactivation ( h ) functions by LS , i . e replacing Vm by ( Vm+LS ) in Eqs ( 7 ) . In other words whatever used to be observed at a given Vm in any function of m and h is now observed at ( Vm−LS ) . This CLS is the basis of our model for axon damage . In patch clamp experiments the activation/inactivation time course data are explained with a single LS value for each degree of injury [8] . However , axon injury is spatially non-homogeneous [2] and is therefore likely to result in spatially inhomogeneous CLS . To account for this possibility we introduce fractions fi of Nav channels in damaged membrane , with left-shift intensity LSi ( in millivolts ) . A Gaussian distribution of LSi seems a realistic model of axon injury , hence we explore various Gaussians . But discrete populations with a small number of LS values are more amenable to a thorough analysis , such as the bifurcation analysis done on a three population system exhibiting bursting dynamics ( see Figure 5 ) . Specifically for a population of left-shifted Nav 1 . 6 channels {fi , LSi}i = 1 , N , for each fi of intensity LSi , independent activation variables mi ( i = 1 , 2 , …N ) and inactivation variables hi ( i = 1 , 2 , …N ) are introduced . The total INa for all Nav channels is now given as: ( 9 ) Three classes of Nav-CLS are considered here: ( a ) two gNa populations: one intact , one left-shifted by a specified fixed amount ( as in [11] ) ; ( b ) three populations: one intact , two with discrete LS values; and ( c ) assorted versions of LS of all or specified fractions of the total Nav population , but with fi ( LS ) following Gaussian distributions to mimic the expectation that nodal injury would produce “smeared” ( as opposed to discrete ) extents of “Nav-CLS” . At the node of Ranvier , gNa dominates over gK , but previously [11] we briefly discussed the effects of also applying a LS to the gating of the Kv channels . The following features are also included in the model . Leakage currents [29] , INaleak and IKleak , account for the background permeabilities needed to bring the basal system to a quiescent steady-state Vm with an active pump present , along with the usual unspecific leakage current Ileak . These leak currents take the form: ( 9 ) where conductances gNaleak , gKleak and gleak are constants . Parameter values are summarized in Table 1 . With an active Na/K pump , the model system has dynamic intracellular and extracellular Na+ and K+ concentrations , denoted by [Na+]i , [Na+]o , [K+]i , and [K+]o . The Na/K pump balances the accumulation and depletion of ions in the intra- and extracellular space by exchanging 3 internal Na+ for 2 external K+ ions . Thus [K+]o and [Na+]i determine the pump amplitude [29] , [87]: ( 10 ) where is the maximal current generated by the pump , and are Michaelis-Menten kinetic constants , and the Na+ and K+ currents flowing through the pump are INapump = 3Ipump and IKpump = −2Ipump . Ion fluxes across the node of Ranvier membrane cause the ion concentration changes: ( 11 ) ( 12 ) where F is the Faraday constant , A is the surface area of the nodal membrane , and ( or ) is the intracellular ( or extracellular ) volume of the node of Ranvier under study ( we take for simplicity ) . Ion concentration dynamics alter the reversal potentials EIon in Eqs ( 2–3 ) by the Nernst equations: ( 13 ) Model equations are solved using a 4-th order Runge-Kutta scheme with 10−3 ms as time step in MATLAB and bifurcation diagrams were plotted using XPPAUT .
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Nerve cells damaged by trauma , stroke , epilepsy , inflammatory conditions etc , have chronically leaky sodium channels that eventually kill . The usual job of sodium channels is to make brief voltage signals –action potentials– for long distance propagation . After sodium channels open to generate action potentials , sodium pumps work harder to re-establish the intracellular/extracellular sodium imbalance that is , literally , the neuron's battery for firing action potentials . Wherever tissue damage renders membranes overly fluid , we hypothesize , sodium channels become chronically leaky . Our experimental findings justify this . In fluidized membranes , sodium channel voltage sensors respond too easily , letting channels spend too much time open . Channels leak , pumps respond . By mathematical modeling , we show that in damaged channel-rich membranes the continual pump/leak counterplay would trigger the kinds of bizarre intermittent action potential bursts typical of injured neurons . Arising ectopically from injury regions , such neuropathic firing is unrelated to events in the external world . Drugs that can silence these deleterious electrical barrages without blocking healthy action potentials are needed . If fluidized membranes house the problematic leaky sodium channels , then drug side effects could be diminished by using drugs that accumulate most avidly into fluidized membranes , and that bind their targets with highest affinity there .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"physics",
"computational",
"neuroscience",
"biophysics",
"theory",
"biology",
"computational",
"biology",
"biophysics",
"simulations",
"biophysics"
] |
2012
|
Spontaneous Excitation Patterns Computed for Axons with Injury-like Impairments of Sodium Channels and Na/K Pumps
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In mid-2015 , the United States’ Pandemic Prediction and Forecasting Science and Technical Working Group of the National Science and Technology Council , Food and Agriculture Organization Emergency Prevention Systems , and Kenya Meteorological Department issued an alert predicting a high possibility of El-Niño rainfall and Rift Valley Fever ( RVF ) epidemic in Eastern Africa . In response to the alert , the Kenya Directorate of Veterinary Services ( KDVS ) carried out an enhanced syndromic surveillance system between November 2015 and February 2016 , targeting 22 RVF high-risk counties in the country as identified previously through risk mapping . The surveillance collected data on RVF-associated syndromes in cattle , sheep , goats , and camels from >1100 farmers through 66 surveillance officers . During the 14-week surveillance period , the KDVS received 10 , 958 reports from participating farmers and surveillance officers , of which 362 ( 3 . 3% ) had at least one syndrome . The reported syndromes included 196 ( 54 . 1% ) deaths in young livestock , 133 ( 36 . 7% ) abortions , and 33 ( 9 . 1% ) hemorrhagic diseases , with most occurring in November and December , the period of heaviest rainfall . Of the 69 herds that met the suspect RVF herd definition ( abortion in flooded area ) , 24 ( 34 . 8% ) were defined as probable ( abortions , mortalities in the young ones , and/or hemorrhagic signs ) but none were confirmed . This surveillance activity served as an early warning system that could detect RVF disease in animals before spillover to humans . It was also an excellent pilot for designing and implementing syndromic surveillance in animals in the country , which is now being rolled out using a mobile phone-based data reporting technology as part of the global health security system .
Rift Valley Fever ( RVF ) is a mosquito borne viral zoonoses that primarily affects cattle , goats , sheep , and camels in Africa and the Arabian Peninsula [1–3] . Humans become infected through close contact with blood and organs of infected animals or through bites from an infected mosquito [4] . Epidemics of RVF are a major global health security threat due to the high morbidity and mortality in humans , and the economic impact associated with loss of livestock and ban in international trade . The World Organization for Animal Health ( OIE ) identifies RVF as an important transboundary and notifiable disease because of its potential for rapidly spreading across international borders , resulting in devastating economic effects through losses in the international trade of animals and animal products [5–8] . RVF epidemics are characterized by massive livestock abortions and death , resulting in high economic losses associated with animal quarantines and trade restrictions [9] . For example , the economic losses resulting from the 2006–2007 RVF epidemic in Kenya were estimated at US $32 million [7] . In humans , over 80% of RVF virus-infected humans are either asymptomatic or have a mild influenza-like illness; however , high morbidity and mortality has been reported in some outbreaks [4 , 10–13] . A 1977 RVF epidemic in Egypt resulted in an estimated 200 , 000 human cases and 600 deaths whereas the RVF outbreak in East Africa ( Kenya , Somalia , Tanzania ) during 1997–1998 resulted in over 100 , 000 cases and over 450 deaths in Kenya [10 , 12–14] . A RVF epidemic in Saudi Arabia and Yemen in 2002 resulted in an estimated 4000 human cases and over 200 deaths [2 , 3] . Globally , livestock RVF epidemics have been most frequently reported in Eastern Africa , occurring every 4 to 10 years and closely linked with periods of heavy rainfall that occur during the warm phase of the El Niño/Southern Oscillation phenomenon [15] . Predictions of RVF epidemics in the region can be given up to 5 months in advance , based on ecological parameters and satellite imagery [16] . In mid-2015 , the United States’ Pandemic Prediction and Forecasting Science and Technical Working Group of the National Science and technology Council , Food and Agriculture Organization Emergency Prevention Systems , and Kenya Meteorological Department all issued alerts predicting a high possibility of El-Niño rainfall and RVF outbreaks in Eastern Africa [17 , 18] . In response to the alert , the Kenya Directorate of Veterinary Services ( KDVS ) in the Ministry of Agriculture , Livestock and Fisheries pilot tested an enhanced surveillance system between November 2015 and February 2016 in 22 RVF high-risk counties [19] . In Kenya , as in many resources-limited countries , the routine livestock surveillance is passive where public and private animal health officers must wait for farmers to report animal illness before responding . The aim of the enhanced surveillance reported here was to collect near real-time data on syndromes and risk factors associated with RVF to enhance early detection of the disease in livestock before spill over to humans . We describe how the surveillance was conducted , results of the surveillance , and recommend next steps towards establishing a national syndromic surveillance system in livestock and wildlife populations in Kenya .
To increase the chances of early detection of RVF disease in livestock ( cattle , sheep , goats , and camels ) , an enhanced surveillance system was implemented over a 14-week between November 2015 and February 2016 in the 22 counties at a high-risk of RVF outbreak ( out of the 47 counties in Kenya ) . The 22 RVF high-risk counties shown in Fig 1 had previously been identified through the RVF risk map for the country [19] . In each of the high-risk counties , we selected three sub-counties with the greater risk of the epidemic for the enhanced surveillance . The criteria used to select the sub-counties included the number of susceptible livestock , areas prone to flooding , and history of RVF outbreaks . For the 25 counties that were not at RVF high-risk and therefore not targeted with the enhanced RVF surveillance , routine RVF surveillance was maintained by KDVS . The surveillance system consisted of an RVF Alert Center at the KDVS headquarters to receive , compile and report the surveillance data from the ub-county veterinary officers ( SCVOs ) who carried out the surveillance at sub-county level , and the livestock farmers who provided the information to the SCVO ( Fig 2 ) . The SCVO in each sub-county was responsible for reporting cases of suspected RVF in livestock from the selected farms in their area , using a data collection tool developed for RVF reporting . Each SCVO identified 20 livestock owning farmers evenly spread across the sub-county , and whom they interviewed weekly by telephone to determine whether there were suspected RVF cases in cattle , sheep , goats , camels on their farms or neighboring farms , and any suspect RVF human cases . Weekly , the SCVO collected animal demographic data ( farm location , animal numbers and species ) , RVF risk factors ( livestock production system , vaccination status , weather , and vector information ) , and RVF associated syndromes ( abortion , hemorrhagic disease , mortalities and human illness ) . The SCVOs sent reports every Friday to the RVF Alert Centre via email ( Fig 2 ) . The 20 farmers in each in high-risk counties were also trained to use the toll-free number and report directly to the RVF Alert Center . Located at Veterinary Epidemiology and Economics Unit ( VEEU ) at the KDVS headquarters , the RVF Alert Centre was managed by two veterinary epidemiologists each reachable round the clock through a toll-free numbers . Reports to the RVF Alert Center were reviewed daily and the County Director of Veterinary Services in area informed within 24 hours , who in turn carried out further investigation and appropriate response . Suspected RVF illness in humans were reported to the County Director of Health in the area , and the Disease Surveillance and Response Unit of the Kenya Ministry of Health headquarters for investigation . A suspected RVF herd was defined as a herd reporting abortion in any of the livestock in the herd in an area experiencing heavy rainfall and flooding . A probable RVF herd was defined as a herd reporting abortions , mortalities in the young ones , and/or hemorrhagic signs in any of the livestock in the herd in an area experiencing heavy rainfall and flooding . A confirmed RVF herd was defined as a herd where an animal tested positive to RVF by RVF IgM ELISA . Each suspected or probable RVF herd was investigated by the SCVO of the area and reports sent to the RVF Alert Center . During the follow-up investigation , the SCVO collected blood samples from suspected or probable herds and shipped them to the Central Veterinary Laboratories ( CVL ) at Kabete , Nairobi for testing . The presence of anti-RVF immunoglobulin ( IgG ) and IgM antibodies in sera was determined using the IDVet enzyme linked immunosorbent assay ( ELISA ) kits according to the manufacturer’s instructions ( IDVet Innovative Diagnostic , Grabels , France ) . For detection of anti-RVF IgG antibodies , ELISA plates were coated with RVF virus recombinant nucleoprotein overnight before washing and adding 50ul of the test serum at 1:10 dilution . A positive and negative control sera were provided in the kit . The plates were incubated for one hour at 37°C , washed , and anti-RVF nucleoprotein peroxidase conjugate added . Following 30 mins incubation , the plates were washed and presence of anti-RVF IgG detected using odometer . For detection of anti-RVF IgM antibodies , anti-bovine , ovine , or caprine ( for cattle , sheep and goat sera ) IgM polyclonal antibodies were used to coat ELISA plates overnight , washed and test serum added at 1:10 dilution . Plates were incubated for 1 hour at 37°C , washed , and RVF nucleoprotein added and results recorded . Actual rainfall data for the surveillance period ( November 2015 to February 2016 ) were obtained from the Tropical Rainfall Measuring Mission supported by the United States’ National Aeronautics and Space Administration ( https://pmm . nasa . gov/precipitation-measurement-missions ) . The data used were combined microwave-IR-gauge estimates generated from Version 7 Tropical Rainfall Measuring Mission ( TRMM ) Multi-Satellite Precipitation Analysis algorithm . Rainfall data for November 2015 to February 2016 ( files 3B43 . 20151001 . 7 . nc– 3B43 . 20160201 . 7 . nc ) with a resolution of 0 . 25° were downloaded and exported into R statistical software [20] for extraction . The extraction used the current Kenya Counties shape file obtained from the Kenya Bureau of Statistics . The extraction function ( extract ( rainfall data , counties shape file ) is supported by the raster package in the R software . Data received from the SCVOs and toll-free numbers were entered into a Microsoft access database . Each report was given a unique identification number . Data cleaning involved an independent , process with two-persons checking all data entries to ensure that duplications and errors were removed . Complete data entries were those containing name and contacts of the farm/farmer , location of the farm , size of the herd and number of animals affected per species for each syndrome , humans affected; and associated environmental conditions . All data were exported as a Microsoft Excel 2010 ( Microsoft Corp . , Redmond , WA , USA ) file for data cleaning which was imported into STATA version 14 ( StataCorp , College Station , TX , USA ) where data variables were summarized to check for outliers . Suspected and probable RVF herd reports were flagged from these data , and descriptive analyses were performed to generate weekly plots of the RVF cases , and compared with the reported weather conditions and actual rainfall data . Correlations and associations between data variables were assessed by the value of Pearson’s correlation coefficient and Pearson’s Chi-Squared test of significance . The descriptive and statistical analyses were performed in both STATA and Tableau Desktop 10 . 0 ( Tableau Software , Seattle , WA , USA ) and geographic visualization performed in ArcMap 10 . 3 . 1 ( ESRI , Redlands , CA , USA ) . This surveillance was part of the routine government of Kenya’s response to the threat of RVF outbreak . Therefore , it did not require ethical approval .
Between November 2015 and February 2016 , 56 of the 66 ( 84 . 8% ) sub-counties in 22 selected counties participated in the RVF enhanced surveillance system for the entirety of the 14-week period . A total of 1 , 102 of the targeted 1 , 120 farmers ( 98 . 4% ) participated . This resulted in 10 , 958 reports submitted to the RVF Alert Center that were 100% complete . Each surveillance officer submitted an average of 670 ( range 297–898 ) reports per week . Of these reports , 49 . 3% were from mixed farm production systems , 19 . 9% from pastoral , 17 . 8% from agro-pastoral , 10 . 3% from zero grazing , 1 . 5% from group ranches , and 1 . 2% from commercial ranch farming systems . Abortions , bleeding and deaths syndromes were reported in all species ( Table 1 ) . A time-series plot of reports submitted during the study period by week is shown in Fig 3 . Of the 10 , 958 syndromic and non-syndromic reports submitted , 362 ( 3 . 3% ) had at least one syndrome observed within livestock . Of all reported syndromes , 196 ( 54 . 1% ) were deaths in young livestock , 133 ( 36 . 7% ) abortions , and 33 ( 9 . 1% ) hemorrhagic diseases . Abortion and hemorrhagic bleeding were reported more frequently in the first two months ( November and December ) , whereas death in young animals was reported consistently throughout the surveillance period ( Fig 3 ) . To evaluate the relationship between the reported syndromes and rainfall , we correlated the time-series plot of weekly reports of syndromes with reports of flooding and mosquito swarms ( Fig 4 ) . Across syndromes , 211 out of 362 ( 58 . 3% ) were reported when no flooding was observed . In contrast , more syndromes ( 69 . 3% ) were reported when mosquito swarms were observed . The reporting across all syndromes with observations of flooding and mosquito swarms were similar with high correlation ( Pearson’s correlation coefficient , r> 0 . 87 and p<0 . 001 ) . Fig 5 shows the correlation between these variables ) . A total of 69 ( 19 . 1% ) suspected RVF cases ( abortion in flooded area ) from 45 farmers in 10 counties were identified . Of these 24 ( 6 . 6% ) cases from 18 farmers in 7 counties met the definition for a probable RVF herd . Fig 6 presents the geographic distribution of RVF suspect and probable herds in the study region . Fig 7 plots the suspect RVF herds and actual rainfall over study period . The majority ( 45 of 69 ) of suspect RVF herds were reported in November and December 2015 , whereas three probable RVF herds were reported in both January and February 2016 . Although the mean monthly actual rainfall was lower than the amount typically observed each year during the same months and counties during this period , more rain occurred during November and December and this was highly associated with increased reporting of suspect RVF herds ( Pearson’s Chi-Squared , χ2 = 72 . 9 , p<0 . 001 ) . Of the total reports submitted ( 10 , 958 ) , only 27 . 0% reported having livestock vaccinated for RVF within the previous three months . Specimens were collected from animals in 17 of the 24 RVF probable herds . Goats from two herds tested positive to RVF IgG antibodies but they were negative on RVF IgM ELISA ( Table 2 ) . Samples from the other herds were negative for both IgG and IgM antibodies .
Routine livestock surveillance in Kenya is primarily passive , with public and private veterinarians waiting for farmers to report animal illness before responding and reporting . The enhanced surveillance for RVF reported here provided animal RVF disease data that served as an effective early warning for a major outbreak , giving a chance to prevent spillover to humans . The pilot created a model communication network for emergency reporting of animal health status between farmers , county government surveillance officers , and the national government . While the pilot focused on a select number of farmers , it demonstrated the willingness of farmers to participate , which is vital for the success of any national syndromic surveillance system [21] . Although the predicted heavy El Niño rainfall that is associated with RVF outbreaks was not received in the East Africa region , the occurrence pattern of syndromes and RVF herds showed a positive correlation with rainfall and flooding . Overall , the number of reports of RVF-associated syndromes , in particular abortions and hemorrhagic disease were high in the months that reported the highest rainfall ( Fig 3 ) . A similar trend was observed with suspected and probable RVF herds ( Fig 6 ) . These data resulted in increased awareness among farmers , and animal and human health officers in these areas , thus increasing the chance of detecting RVF cases . The surveillance had a number of limitations that will be important to address for any future syndromic surveillance efforts in Kenya . Since this was for selected regions , the surveillance and resulting data collected were not representative of the targeted animal populations of interest . While it would then be possible that RVF cases could have occurred and not been detected by this system , it was expected that any other outbreaks would have been reported through regular reporting channels set by the KDVS . Another limitation of this work was that the surveillance officers submitted their reports on a weekly basis , affecting the timeliness of data collection . Furthermore , the data received at the RVF Alert Center had to be manually transferred to another database for analysis , a step that introduced possible additional human error and delays in data analysis . Leveraging current technologies for both data collection ( e . g . , mobile phones ) and data integration/analysis that allow for near real-time reporting of animal health will be required in order for future syndromic surveillance efforts to successfully meet their intended purpose of early detection of disease events . Another limitation is that the laboratory results may not have been representative of disease status of the herd , with a possibility that IgM positivity in the suspected or probable herds was missed . This is because the method of collecting and testing of samples from suspected and probable herds was neither random nor did it target animals with the clinical signs . There were no RVF outbreaks confirmed during the surveillance period , most likely because the predicted El Niño rainfall was not received . However , it is important to note that 27% of the farmers reported having vaccinated their livestock against RVF within the previous three months , and surveys in these RVF high-risk regions have typicaly reported >10% seropositivity in livestock , and up to 20% seropositivity in humans [22] . Given that occurrence of RVF epidemics seems to require low herd immunity , this level of immunity may have also have reduced the risk of RVF outbreak in the country . This RVF enhanced surveillance pilot demonstrated the capacity and need for establishing a national syndromic surveillance system in livestock in Kenya . Such a system would need to be synergistic with other surveillance systems in the country so as not to overburden data providers . The fact that both the KDVS and Kenya Wildlife Services do not have established national disease surveillance systems is an advantage as it enables the designing of a system that works in both livestock and wildlife . Similarly , guidelines would need to be established between the responsible animal and public health government agencies so as to ensure the infrastructure is in place to handle the additional information , and to determine appropriate responses to potential disease events that are effective and do not overwhelm their resources [23] . An ideal surveillance system should also implement data collection standards and be expanded to include a comprehensive set of clearly defined disease syndromes so as to have the capability to detect transboundary , emerging , and zoonotic disease events . Finally , the system should allow regular and near real-time feedback of the collected data to surveillance officers so as to enhance situational awareness and support the sustainability of the overall system . By leveraging current technologies such as mobile phones that are gaining usage globally for syndromic surveillance , most of the aforementioned successes can be enhanced , and the limitations from this RVF enhanced surveillance can be addressed .
This surveillance demonstrated the need to establish a national syndromic surveillance system in livestock and wildlife in Kenya . Further , the interaction between humans , animals , and the environment reinforces the concept of syndromic surveillance within the One Health concept [24] . The RVF enhanced surveillance served as an important first step toward designing and implementing an animal syndromic surveillance system in Kenya . As follow-up to these efforts , the United States’ Centers for Disease Control and Prevention ( CDC ) is currently funding work to develop and deploy syndromic surveillance system in domestic animals and wild animals in Kenya , using a mobile and data integrations/analysis technologies customized for the country , referred to as the Kenya Animal Biosurveillance System ( KABS ) . The KABS is capable of integrated analysis of animal and public health data using algorithms defined by veterinary officers within the Kenya government . The KABS technology will allow data providers and government animal health officials to quickly detect and report the animal health status in domestic animals and wildlife populations across different geographical areas and provide early warning information from validated sources signaling activity to assist in decision-making and response during a disease event . Furthermore , KABS will be the first instance of implementing routine surveillance in Kenya wildlife populations . Once fully developed , KABS will be a low cost , easy to implement surveillance technology solution that can be customized and adapted to other country’s needs and requirements for supporting human and animal health .
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Occurrence of Rift Valley Fever ( RVF ) outbreak is associated with heavy El-Niño rainfall . In July 2015 , an alert on the likelihood of El-Niño rainfall and RVF outbreak in Eastern Africa region was issued by the United States , Food and Agriculture Organization , and Kenya Meteorological Department . In response to the alert , the Kenya Directorate of Veterinary Services ( KDVS ) carried out an enhanced syndromic surveillance system between November 2015 and February 2016 in the 22 counties that had previously been identified as RVF high-risk counties . The surveillance system collected data on RVF-associated syndromes and risk factors in cattle , sheep , goats and camels from more than 1100 farmers . Of the 10 , 958 field reports submitted , 45 were consistent with suspect RVF disease and 24 of these identified as probable RVF , triggering an immediate response . Whereas investigations of the suspect cases and laboratory testing did not confirm RVF cases , the surveillance system served as an excellent early warning system that could detect disease in animal before spillover to humans .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion",
"Conclusions"
] |
[
"livestock",
"medicine",
"and",
"health",
"sciences",
"animal",
"diseases",
"ovine",
"abortion",
"tropical",
"diseases",
"geographical",
"locations",
"rift",
"valley",
"fever",
"neglected",
"tropical",
"diseases",
"zoology",
"africa",
"veterinary",
"science",
"infectious",
"diseases",
"veterinary",
"diseases",
"zoonoses",
"veterinary",
"epidemiology",
"epidemiology",
"bovine",
"abortion",
"agriculture",
"people",
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"kenya",
"disease",
"surveillance",
"biology",
"and",
"life",
"sciences",
"viral",
"diseases"
] |
2018
|
Enhanced surveillance for Rift Valley Fever in livestock during El Niño rains and threat of RVF outbreak, Kenya, 2015-2016
|
Triple-negative breast cancer ( TNBC ) cells do not express estrogen receptors , progesterone receptors , or human epidermal growth factor receptor 2 . Currently , apart from poly ADP-ribose polymerase inhibitors , there are few effective therapeutic options for this type of cancer . Here , we present comprehensive characterization of the genetic alterations in TNBC performed by high coverage whole genome sequencing together with transcriptome and whole exome sequencing . Silencing of the BRCA1 gene impaired the homologous recombination pathway in a subset of TNBCs , which exhibited similar phenotypes to tumors with BRCA1 mutations; they harbored many structural variations ( SVs ) with relative enrichment for tandem duplication . Clonal analysis suggested that TP53 mutations and methylation of CpG dinucleotides in the BRCA1 promoter were early events of carcinogenesis . SVs were associated with driver oncogenic events such as amplification of MYC , NOTCH2 , or NOTCH3 and affected tumor suppressor genes including RB1 , PTEN , and KMT2C . Furthermore , we identified putative TGFA enhancer regions . Recurrent SVs that affected the TGFA enhancer region led to enhanced expression of the TGFA oncogene that encodes one of the high affinity ligands for epidermal growth factor receptor . We also identified a variety of oncogenes that could transform 3T3 mouse fibroblasts , suggesting that individual TNBC tumors may undergo a unique driver event that can be targetable . Thus , we revealed several features of TNBC with clinically important implications .
Triple-negative breast cancer ( TNBC ) comprises 15–20% of all breast cancers ( BCs ) and is defined by a lack of estrogen and progesterone receptor expression and the absence of ERBB2 gene amplification , which encodes human epidermal growth factor receptor 2 ( HER2 ) [1] . Recent advances in sequencing technology have provided meaningful genomic and epigenomic insights into the pathogenesis of BC types including TNBC [2–5] . Mutations of TP53 [2 , 4 , 5] , loss-of-function of BRCA1 [6–8] , and amplification and enhanced expression of MYC [9] are common events in TNBC . Because it is difficult to specifically target MYC , cytotoxic chemotherapy remains the only approved treatment . Poly ADP-ribose polymerase ( PARP ) inhibitors are newly developed treatment options for a subset of TNBCs [10] . Tumors with a defective homologous recombination ( HR ) pathway are expected to be susceptible to PARP inhibitors , because tumor cells cannot tolerate additional DNA damage in the absence of HR pathway proteins and DNA damage repair mechanisms mediated by PARP . At present , only tumors with mutations in BRCA1 or BRCA2 have been shown to be responsive to PARP inhibitors . Thus , identification of biomarkers that distinguish responders to PARP inhibitors is required [11] . Deconvolution of oncogenic events can contribute to the development of targeted therapy for cancer because oncogenes can be ideal therapeutic targets . For example , treatment of BC with HER2 amplification is greatly improved by the use of an anti-HER2 agent [12] . Identification of EML4-ALK fusion genes in lung adenocarcinoma has led to the application of ALK inhibitors for the treatment of lung adenocarcinoma with EML4-ALK fusions [13] . Although alterations have been reported in certain oncogenes , such as those involved in the phosphatidylinositol-3-kinase-AKT pathway [3] or NOTCH pathway [14 , 15] , the frequency of these oncogenic events appears to be relatively low in TNBC . It is likely that many rare oncogenes remain to be identified in TNBC , which constitute the “long tail” [16] . Comprehensive analysis of the TNBC genome has often been hampered by low tumor content in a given specimen because of the presence of stroma and/or necrotic tissue . Thus , we characterized the genomic alterations of TNBC to identify oncogenic gene alterations by high coverage whole genome sequencing ( WGS ) combined with whole exome sequencing ( WES ) and transcriptome sequencing ( RNA-Seq ) . To assess the tumorigenic potential of candidate oncogenes with high probability , we also employed biological assays for transformation [17] where possible . We describe the molecular phenotypes of tumors with a defective HR pathway in detail , providing fundamental information for the development of treatment strategies involving PARP inhibitors . Our observations also support the notion that SVs in TNBC affect tumor suppressor genes and oncogenes , as suggested in previous reports [6 , 18] . As one of the oncogenes affected by SVs , we have identified TGFA , a gene encoding one of the ligands for the epidermal growth factor receptor . Upregulation of TGFA expression has been reported in a subset of TNBC [19] , and enhanced expression of TGFA is associated with BC development [20] . However , the mechanistic basis of enhanced TGFA expression has not yet been elucidated . In this study , we present the possible mechanisms of TGFA activation . We also identified several rare oncogenes and confirmed their tumorigenic potential in biological assays . Here , we present several important findings that could advance our understanding of TNBC pathogenesis .
To comprehensively characterize the genetic alterations that occur in TNBC , we subjected 36 surgically resected TNBC tissues to WES , together with paired normal tissues . We further analyzed 23 tumors out of these 36 tumors , together with 17 estrogen receptor-positive ( ER+ ) and 15 HER2-positive ( HER2+ ) BC samples , using RNA-seq ( S1 Table ) . WES identified a median of 52 ( range , 3–170 ) somatic nonsynonymous single nucleotide variations ( SNVs ) and a median of 5 ( range , 0–20 ) somatic insertions/deletions ( indels ) in the coding regions of TNBC samples . Samples with expected high tumor content ( > 30% , 16 samples ) were subjected to deep WGS ( S1 Table ) , yielding a median of 162 ( range , 137 . 5–173 . 9 ) mean coverage ( S2 Table ) . WGS identified a median of 102 . 5 ( range , 46–193 ) somatic nonsynonymous SNVs in the exonic regions and a median of 5 . 1 ( range , 2 . 8–7 . 9 ) SNVs per megabase . We also found a median of 6 . 5 ( range , 1–15 ) somatic indels in the exonic regions and a median of 0 . 11 ( range , 0 . 048–0 . 22 ) indels per megabase in the entire genome ( S2 Table ) . Frequencies of SNVs and indels were in good agreement with previous reports [2–5] . As previously reported [2–5] , we observed a high frequency of TP53 mutations ( 72% ) and relatively low frequency of PIK3CA mutations ( 19% ) ( S1 Fig ) . In the majority of tumors with TP53 mutations , expression of the mutant allele was greater than that of the wild-type allele ( S1 Fig ) . Mutational signature analysis [21] of SNVs detected by high coverage WGS in 16 TNBC tumors identified the BRCA signature , age-related signature , and APOBEC ( apolipoprotein B mRNA editing enzyme , catalytic polypeptide-like ) signature ( Fig 1A and 1B ) that were consistent with previous reports [21–23] . It has been suggested that loss-of-function of several genes , including BRCA1 , BRCA2 , RAD51C , or BRIP1 , results in HR deficiency [11 , 24] . It has also been suggested that the BRCA signature is dominant in tumors with a defective HR pathway [6 , 24] . In accordance with these notions , HR pathways were expected to be defective in all tumors with a dominant BRCA signature , because of low BRCA1 or RAD51C mRNA expression , or BRCA1 mutations ( Fig 1B ) . Furthermore , all tumors with low BRCA1 or RAD51C expression exhibited DNA methylation of the corresponding promoter regions ( S2 Fig ) . Thus , we hypothesized that a disruptive mutation and promoter methylation of BRCA1 or RAD51C are the major causes of the defective HR that is manifested by BRCA signature dominance . To validate the relationship between BRCA1/RAD51C promoter methylation , BRCA1/RAD51C mRNA expression , and the mutational signature , we analyzed The Cancer Genome Atlas ( TCGA ) data set ( 110 TNBC specimens ) . The three mutational signatures were again extracted from the TCGA exome data ( S3 Fig ) . Low expression of BRCA1/RAD51C was closely associated with high methylation levels of BRCA1/RAD51C promoter regions ( S3 Fig ) . When HR defects were defined by promoter methylation or disruptive mutations of BRCA1/RAD51C , HR defects were significantly associated with the BRCA signature ( P = 3 . 2 × 10−6 , Wilcoxon rank sum test; S3 Fig ) , supporting our hypothesis and suggesting that mutation and transcriptional silencing of BRCA1/RAD51C may be determinants of responsiveness to PARP inhibitors . The high coverage WGS analysis identified a large number of somatic SVs , with a median of 310 . 5 ( range , 6–711 ) SVs per sample ( Fig 1B; S2 Table ) , which was equivalent to a previous report [6] . They were classified into four types: translocations , inverted rearrangements , deletions , and tandem duplications . In accordance with previous reports [24 , 25] , SV counts were higher in tumors with a defective HR pathway than in tumors with an intact HR pathway ( P = 0 . 013 , Wilcoxon rank sum test; Fig 1B ) . Thus , loss of BRCA1 or RAD51C functions was associated with a dominant BRCA signature and higher SV numbers . In our cohort , BRCA1 deficiency was significantly associated with an increase in the number of tandem duplications ( P = 0 . 016 , Wilcoxon rank sum test; Fig 1C ) . Although our cohort contained only two tumors with defective RAD51C , it appeared that defective RAD51C was not associated with increased tandem duplications . It is thought that a recombination event mediated by break-induced replication ( BIR ) can lead to the generation of tandem duplication [26] . Because RAD51C facilitates the assembly of RAD51 filaments to promote strand invasion , RAD51C may be required for recombinational DNA repair processes including BIR [27 , 28] . Further study is required to reveal the contribution of RAD51C to the formation of tandem duplication and the influence of RAD51C deficiency on genomic structural variations . Several sophisticated methods have been used to analyze the clonal architecture of cancer [4 , 29] . However , the complicated chromosomal copy number ( CN ) status of TNBC has hampered the precise application of these methods . In particular , the exact number of gained or amplified alleles is quite difficult to determine in the presence of an unknown fraction of contaminating normal cells . Thus , we analyzed clonal architecture using data from regions with a CN of one because the tumor cellularity can be unambiguously determined in such regions . To perform the CN-based global analysis , we first determined the correlation between the minor allele log R ratio and tumor cellularity deduced from the proportion of minor alleles using data from all regions in which the CN of the major allele was one and the CN of the minor allele was zero ( S4 Fig ) . Based on this correlation , the clonal architecture was inferred using data from regions in which the CN of the minor allele was zero ( Fig 2A ) . CN-based global analysis revealed only a few subclones of detectable size in each tumor ( Fig 2B ) , which was consistent with previous results of single cell analysis [30] . We next determined the local clonal architecture of the TNBC samples using variant allele frequencies ( VAFs ) of SNVs . VAFs within selected regions with low CNs were analyzed separately ( Fig 2C , S4 Fig ) , because the high read depth in the current study enabled such local clonal analysis . In the case of TN-19 , analysis using PyClone [4] revealed a truncal clone with 89% cellularity ( or 100% clonality by definition ) and a subclone with 42% cellularity ( or 47% clonality ) ( Fig 2C , S4 Fig ) . Of note , this subclone was also identified in the analysis of VAFs within all CN-low regions and the CN-based global analysis ( Fig 2A ) . The truncal clone of TN-19 harbored mutations encoding TP53 ( R213L ) and APC ( E109X ) , and the major subclone had undergone biallelic loss of a part of the long arm of chromosome 4 , encompassing the CASP3 locus . Analysis of other tumors revealed that the cellularity of cells with TP53 mutations or methylated CpG dinucleotides in BRCA1/RAD51C promoter regions coincided with those of truncal clones , suggesting that most TP53 mutations and the promoter methylation of BRCA1/RAD51C were acquired in truncal clones ( Fig 2D ) . The great read depth of the present WGS analysis enabled us to analyze the clonal architecture in detail . The analysis suggested that the CN status of tumors is stable during tumor evolution , and that TP53 mutations and silencing of BRCA1/RAD51C are earlier events during TNBC carcinogenesis . As previously reported [25] , intrachromosomal SVs were more prevalent than interchromosomal SVs ( S2 Table ) . The breakpoints of the intrachromosomal SVs showed that crossover occurred in a complicated manner , indicating the complex nature of the mechanisms underlying SVs in TNBC ( S5 Fig ) . In chromosomal regions where CN changes were prominent , including the long arms of chromosomes 3 and 8 , and the short arm of chromosome 6 , a large number of SVs were observed ( S5 Fig ) . This finding is not surprising given that CN changes are expected to occur as a result of sequential SVs such as breakage-fusion-bridge cycles [31] . An unexpected observation was that many intrachromosomal SVs crossed over a centromere . The distances between breakpoints of intrachromosomal SVs had an unexpected trimodal distribution with peaks of approximately 5 kbp , 300 kbp , and 10 Mbp ( Fig 3A ) . Tumors with a defective HR pathway had SVs with short distances between breakpoints ( P = 4 . 6E-4 , Wilcoxon rank sum test for log10 ( median distance ) ; Figs 1B and 3A ) . The distances between breakpoints of inverted rearrangements were relatively large with a peak of approximately 10 Mbp , while those of tandem duplications were relatively small with peaks of approximately 5 and 300 kbp . It should be noted that the distance between breakpoints does not always reflect the exact size of the rearrangement because there are many crossovers . More precise assessment of the size of the rearrangement by long read sequencing or phasing ( haplotype mapping ) technologies in combination with short read sequencing is required in the future . Large tandem duplications contributed to the CN gains , such as the duplication of the long arm of chromosome 8 in TN-2 and TN-13 , and the long arm of chromosome 3 in TN-25 ( S5 Fig ) . Some large inverted rearrangements that crossed over a centromere appeared to result in CN alterations within chromosome 8 in TN-19 , chromosome 19 in TN-9 , and chromosome 3 in TN-2 ( Fig 3B ) . We proposed a novel mode of CN alterations in which a part of a chromosome arm is replaced by a part of the opposite arm of the homologous chromosome in an inverted rearrangement , thus resulting in CN gain and loss of chromosome regions . Long-range genomic analysis by linked-read sequencing [32] of TN-19 confirmed the break points of the inverted rearrangement in chromosome 8 within consistent haplotype blocks ( S5 Fig ) . The result of three-color fluorescence in situ hybridization ( FISH ) analysis of the formalin-fixed , paraffin-embedded ( FFPE ) specimen was compatible with the expected chromosome structure ( S5 Fig ) . Based on this assumption , the observed CN statuses are simply explained by the observed inverted rearrangements ( Fig 3B ) . It would be advantageous for SVs to occur between homologous chromosomes because such an SV does not result in centromere duplication that causes catastrophic mitosis . In summary , WGS revealed that the size of SVs has a distinctive distribution depending on the type of SVs . It also revealed processes involving inverted rearrangements through which chromosomal regions were gained or lost . SNVs or indels in putative tumor suppressor genes , such as RB1 , KMT2C , PTEN , and RUNX1 , are relatively infrequent in TNBC compared with ER+ or HER2+ BC [2] . Consistent with this notion , our WES analysis of 36 TNBC tumors identified only two RB1 mutations , two KMT2C mutations , two PTEN mutations , and one RUNX1 mutation . However , our WGS analysis revealed that these tumor suppressor genes were frequently disrupted by SVs in TNBC . Out of 16 analyzed TNBC tumors , six , three , two , and one tumor harbored SVs involving RB1 , KMT2C , PTEN , or RUNX1 , respectively ( S1 Fig ) . The observed SVs also resulted in the amplification of oncogenes including MYC , NOTCH2 , and NOTCH3 ( S1 Fig ) . Amplification of the loci resulted in enhanced expression of the respective genes ( S6 Fig ) . We also identified two tumors with amplification of the NOTCH2 locus by droplet digital PCR CN analysis among 48 FFPE specimens ( S6 Fig ) . Taken together , these findings indicate that the major consequences of gene rearrangements in TNBC appear to be the disruption of tumor suppressor-coding sequences and the amplification and enhanced expression of oncogenes . We further searched for genes that were affected by SVs . SVs in gene regulatory regions influence the expression of genes [33 , 34] . Whereas TGFA expression was activated in a subset of TNBCs ( Fig 4A ) , we observed SVs within or near the TGFA locus in five tumors ( Fig 4B , S7 Fig ) . Analysis of CN data from the TCGA BC cohort ( 1097 specimens including 110 TNBC specimens ) revealed 17 possible SVs within or near the TGFA locus ( Fig 4D ) , which were enriched in TNBC ( 6/104 in TNBC , 11/976 in non-TNBC , P = 0 . 0044 , Fisher’s exact test ) . TGFA mRNA expression in these tumors was significantly high ( P = 0 . 0012 , Wilcoxon rank sum test ) ( Fig 4C and 4D ) . These data suggested that the observed SVs were associated with enhanced expression of TGFA . TGFA expression is elevated in the hypopharyngeal squamous cell carcinoma cell line BICR6 that harbors a focal CN gain involving the TFGA locus , similar to that of TNBC tumor samples ( TN-M4 in the present study and TCGA-AR-A256 in TCGA ) , according to Cancer Cell Line Encyclopedia ( CCLE ) data ( Fig 4B , 4D and 4E ) . Acetylation of the lysine residue at position 27 of histone H3 ( H3K27ac ) was enriched on the duplicated TGFA locus in BICR6 cells ( Fig 4E ) . Although the BICR6 cell line does not originate from mammary tissue , the H3K27ac profile of the TGFA locus in BICR6 cells was similar to that in human mammary epithelial cells according to the Encyclopedia of DNA Elements ( ENCODE ) project data . The binding profile of H3K27ac identified seven putative enhancers ( e1–e7; Fig 4F ) , among which e6 was the most prominently enriched for H3K27ac ( S7 Fig ) . These observations indicated that the H3K27ac-enriched regions might be regulatory regions of TGFA expression , and that BICR6 could be used to investigate the functional role of SVs within or near the TGFA locus . To determine whether the H3K27ac-enriched genomic regions were required for the enhanced expression of TGFA in BICR6 cells , the regions encompassing e6 were deleted using the CRISPR-Cas9 system . Deletion of the regions in BICR6 cells resulted in decreased expression of TGFA ( Fig 4F ) , indicating a direct regulatory function of the region . In luciferase reporter assays using BICR6 cells , the e6 region was found to have strong activity ( Fig 4G ) . In contrast , ectopic expression of TGFA conferred growth factor independence on MCF10A immortalized mammary epithelial cells ( Fig 4H ) . Taken together , these results suggested that SVs involving putative regulatory regions of TGFA in TNBC could result in enhanced expression of TGFA , another candidate oncogene in TNBC . Next , we searched for SNVs that produce potential oncogenes by the soft agar assay , a classical biological assay using the 3T3 immortalized mouse fibroblast cell line [17] . We identified a mutation in the NFKB1 gene encoding NFKB1 ( N580S ) ( Fig 5A ) . According to TCGA pan-cancer data , mutations in NFKB1 are scattered along the protein with moderate enrichment within the ankyrin repeat domain ( Fig 5A ) , but the mutations are quite infrequent . Although another mutation in the ankyrin repeat domain of NFKB1 ( T585M ) has been detected in a BC specimen [29] , its significance has not been analyzed . Remarkably , both NFKB1 ( N580S ) and ( T585M ) conferred anchorage-independent growth on mouse 3T3 fibroblasts ( Fig 5E ) , strongly suggesting the oncogenic potential of the mutant proteins . p50 , the active subunit of the transcription factor NF-κB , is processed from full length NFKB1 or p105 . Full length NFKB1 ( p105 ) tethers p50 within the cytoplasm and prevents nuclear translocation of p50 [35] . Biochemical analyses indicated that the affinity of these NFKB1 mutants for p50 was lower than that of wild-type NFKB1 , thus leading to increased nuclear translocation of p50 ( S8 Fig ) , which in turn leads to CCND1 activation [36] . Two out of 36 frozen tumor samples harbored frame shift mutations within the PEST domain of NOTCH1 ( Fig 5B ) , which are well-described activating mutations of NOTCH1 in T-cell acute lymphoblastic leukemia [37] . One NOTCH1 PEST domain mutation was found among 48 FFPE samples . By combining the three tumors with NOTCH2 locus amplification and a tumor with NOTCH3 locus amplifications , seven tumors with an activated NOTCH pathway were identified out of 84 tumors . These data indicated that the NOTCH pathway was genetically altered and activated in a subset of TNBCs , which is in agreement with a previous report [14] . Activating mutations of ERBB2 have been shown to contribute to carcinogenesis [38] . Two out of 36 frozen tumor samples harbored such ERBB2 mutations ( Fig 5C ) . In addition , two out of 48 FFPE TNBC tumors and two out of 31 ER+ tumors harbored ERBB2 mutations ( S3 Table ) . ERBB2 mutations were enriched in HER2+ BCs compared with ER+ BCs and TNBCs in the TCGA BC data ( P = 0 . 00061 , S4 Table ) . We also identified mutations in small GTPases , such as RIT1 ( T83R ) , RRAS2 ( Q72L ) , and MRAS ( R83H ) , in TNBC samples . RIT1 ( T83R ) and RRAS2 ( Q72L ) were found to be oncogenic in a soft agar assay ( Fig 5E , S9 Fig ) , whereas MRAS ( R83H ) did not show a transforming capacity in a 3T3 transformation assay . Although no RIT1 , RRAS2 , or MRAS mutations were found in the TCGA BC dataset , one tumor with undetermined ER and HER2 statuses harbored a RAC1 ( P69S ) mutation , and one TNBC tumor harbored a RHOB ( D13Y ) mutation . Both of these mutant proteins were confirmed to be oncogenic in a tumorigenicity assay in nude mice ( S9 Fig ) . We also identified one tumor that expressed an FGFR3-CAT fusion transcript ( Fig 5D ) . 3T3 cells expressing the FGFR3-CAT fusion protein formed tumors in mice and exhibited anchorage-independent growth in a soft agar assay ( Fig 5E , S9 Fig ) . Thus , SV in TNBC resulted in oncogenic gene fusion . However , our attempt to identify fusion genes involving FGFR genes ( FGFR1 , FGFR2 , and FGFR3 ) in the TCGA RNA-seq data was unsuccessful . The identification of the wide variety of oncogenic driver events presented above suggested that individual TNBC tumors might harbor a unique oncogenic driver event that is not always found in TNBC .
In the present study , through high coverage WGS , we comprehensively analyzed the genetic alterations in TNBC . We have presented some novel findings about the genetic features of TNBC . Furthermore , we searched for actively functioning oncogenes , because identification of oncogenes has the potential to contribute to the development of targeted therapies . First , our analysis focused on the genetic features of tumors with HR deficiency . Our results were in accordance with the recently developed notion that tumors with a defective HR pathway harbor SNVs with the BRCA signature , relatively abundant SVs , and relatively abundant tandem duplications [6 , 24] . We showed that tumors with BRCA1 or RAD51C promoter methylation exhibit a similar molecular phenotype to those with BRCA1 mutations . It should be clarified whether these tumors respond to platinum-based antitumor agents and PARP inhibitors in a similar manner to tumors with BRCA1 mutations in future studies . In this respect , it is noteworthy that the cellularity of cells with methylated CpG dinucleotides in BRCA1 promoter regions of the TN-6 and TN-13 samples were variegated , while those in other specimens coincided with tumor cellularity ( Fig 2D ) . This observation indicated that the promoter of BRCA1 was not fully methylated in a subset of tumor cells in TN-6 and TN-13 samples , and that these cells may develop resistance to platinum-based antitumor agents or PARP inhibitors . Second , our data indicated the evolutionary pathway of TNBC carcinogenesis in which HR deficiency plays a pivotal role . It is reasonable to consider that TP53 and the HR pathway are impaired at the initial phase of TNBC carcinogenesis , causing the generation of SVs , which in turn disrupts the coding sequences of other tumor suppressors , such as RB1 , KMT2C , and PTEN , and cause amplification of the MYC oncogene , as proposed previously [6 , 18] . Accordingly , to reveal the pathogenesis of TNBC and identify the ideal therapeutic target , more attention should be focused on SVs that affect not only protein-coding sequences , but also noncoding regulatory elements . Third , we searched for oncogenes that positively regulate the proliferation of tumor cells using biological assays for cellular transformation where possible . We found that SVs encompassing putative regulatory regions of TGFA were associated with high expression of TGFA . Because ectopic expression of TGFA confers growth factor independence on MCF10A cells , and the oncogenic potential of TGFA has been demonstrated using a transgenic mouse model [20] , it is expected that TGFA can be a therapeutic target . Further study is required to reveal the contribution of TGFA to the proliferation and survival of TNBC . In addition , we identified various oncogenic gene alterations , some of which may be targetable . Although the frequency of each identified event was rare , identification of potent oncogenes has the potential to provide important information for treatment options for patients whose tumors harbor that particular oncogene . The high coverage WGS integrated with exome sequencing and RNA-seq in the present study revealed several important aspects of TNBC biology and also yielded data that are potentially useful in the era of clinical sequencing and personalized medicine .
The genomic analysis of primary tumor tissue samples was approved by the Human Genome , Gene Analysis Research Ethics Committee of The University of Tokyo . Genomic DNA was isolated from each sample and prepared for WGS with an NEBNext Ultra DNA Library Prep Kit ( New England BioLabs , Ipswich , MA ) according to the manufacturer’s instructions . Adaptor-ligated samples were amplified by three PCR cycles . For WES , genomic DNA was subjected to enrichment of exonic fragments with a SureSelect Human All Exon Kit v5 ( Agilent Technologies , Santa Clara , CA ) . cDNA was prepared from isolated RNA using an NEBNext Ultra Directional RNA Library Prep Kit ( New England BioLabs ) . Massively parallel sequencing of the prepared samples was performed with a HiSeq2000/2500 platform ( Illumina , San Diego , CA ) using the paired-end option . Paired-end reads of WGS were aligned to the human reference genome ( hg19 ) using the Burrows-Wheeler Aligner ( BWA , http://bio-bwa . sourceforge . net/ ) [39] . SNVs , indels , and SVs were called using our in-house program as described previously [40 , 41] with some modification . To predict somatic SNVs and indels , the filters described previously were applied . SNVs and indels were selected when the frequency of the non-reference allele was at least 5% in the tumor genome . In our somatic mutation call , we first compared variants in a matched pair ( tumor/normal sample for each individual patient ) and removed personal germline variants . Next , we made a comparison with all normal samples grouped together , a so-called “normal panel” , and removed false positive variants that occurred by sequence errors . This strategy is very effective for removing false positives because sequence errors occur in a sequence-specific manner at a certain frequency rather than randomly . Fifty base-pair paired-end reads were used for rearrangement analysis , because they contain longer spacers than 125 bp paired-end reads . Therefore , 125 bp paired-end reads were separated to generate 50 bp paired-end reads . To detect structural variations , we used a paired-end read for which both ends aligned uniquely to the human reference genome , but with improper spacing , orientation , or both . First , paired-end reads were selected based on the following filtering conditions: ( i ) sequence read with a mapping quality score greater than 37; ( ii ) sequence read aligned with two mismatches or less . Rearrangements were then identified using the following analytical conditions: ( i ) forward and reverse clusters , which included paired-end reads , were constructed from the end sequences aligned with forward and reverse directions , respectively; ( ii ) two reads were allocated to the same cluster if their end positions were not farther apart than 400 bp; ( iii ) paired-end reads were selected if one end sequence fell within the forward cluster and the other fell within the reverse cluster ( we hereafter refer to this pair of forward and reverse clusters as paired-clusters ) ; ( iv ) for the tumor genome , rearrangements predicted from paired-clusters , which included at least six pairs of end reads , were selected; ( v ) rearrangements detected in the tumor genome , but not present in the panel of non-tumor genome ( all non-tumor genomes grouped together ) , were selected as somatically acquired rearrangements . Paired-end WES reads were aligned to the human reference genome ( hg19 ) using BWA [39] , Bowtie2 ( http://bowtie-bio . sourceforge . net/bowtie2/index . shtml ) [42] , and NovoAlign ( http://www . novocraft . com/products/novoalign/ ) independently . Somatic mutations were called using MuTect ( http://www . broadinstitute . org/cancer/cga/mutect ) [43] , SomaticIndelDetector ( http://www . broadinstitute . org/cancer/cga/node/87 ) [44] , and VarScan ( http://varscan . sourceforge . net ) [45] . Mutations were discarded if ( 1 ) the read depth was <20 or the variant allele frequency ( VAF ) was <0 . 1 , ( 2 ) they were supported by only one strand of the genome , or ( 3 ) they were present in the “1000 genomes” database ( http://www . 1000genomes . org ) or in normal human genomes from our in-house database . Gene mutations were annotated by SnpEff ( http://snpeff . sourceforge . net ) [46] . CN status was analyzed by our in-house pipeline that calculates the log R ratio using normal and tumor VAFs based on dbSNPs of the 1000 genomes database . For expression profiling with RNA-seq data , paired-end reads were aligned to the hg19 human genome assembly using TopHat2 ( https://ccb . jhu . edu/software/tophat/index . shtml ) [47] . The expression level of each RefSeq gene was calculated from mapped read counts using Cufflinks ( http://cufflinks . cbcb . umd . edu ) [48] . Mutational signatures were analyzed using the Wellcome Trust Sanger Institute Mutational Signature Framework ( http://jp . mathworks . com/matlabcentral/fileexchange/38724-wtsi-mutational-signature-framework ) [49] . The optimal number of signatures was determined according to signature stabilities and average Frobenius reconstruction errors . CN-based clonal analysis was conducted as follows: ( 1 ) we first chose genomic regions where the CN of the major allele was one and the CN of the minor allele was zero; ( 2 ) at each selected region , the cellularity of tumor cells harboring the CN alteration was deduced from the minor allele proportion; ( 3 ) correlations between the minor allele log R ratio ( minor allele LRR ) and tumor cellularity were determined; ( 4 ) by k-means clustering of the minor allele LRR values of each sample , minor allele LRR values representing the tumor clone and subclones were inferred; ( 5 ) cellularity values were calculated using the above correlation of ( 3 ) and representative value of ( 4 ) . Clonality was then determined by setting the cellularity of the truncal clone to 100% . For the clonal analysis using VAFs at low CN regions , PyClone ( http://compbio . bccrc . ca/software/pyclone/ ) [50] was used . Genomic DNA of TN-19 was analyzed to obtain long-range genomic information by molecular barcoding [32] . Partition barcoded libraries with sample indexing were prepared on a Chromium Controller Instrument ( 10X Genomics , Pleasanton , CA ) using a Chromium Genome Reagent Kit ( 10X Genomics ) according to manufacturer’s protocols . Sequencing of the prepared samples was performed with a HiSeq2500 platform ( Illumina ) using the paired-end option ( 2 × 130 paried-end reads ) . Data were analyzed with Long Ranger ( 10X Genomics , https://support . 10xgenomics . com/genome-exome/software/pipelines/latest/what-is-long-ranger ) and visualized with Loupe ( 10X genomics , https://support . 10xgenomics . com/genome-exome/software/visualization/latest/what-is-loupe ) . To analyze mutational signatures , mRNA expression and methylation , level 2 mutation data , level 3 mRNA expression data ( RNA-seq V2 RSEM ) and level 3 methylation data from the TCGA invasive breast carcinoma cohort were obtained from the TCGA data portal . For the mutational analysis of specific genes , including NOTCH1 , ERBB2 , and genes encoding small GTPases , level 1 sequencing data in BAM format were downloaded via The Cancer Genomics Hub . Data from 906 tumor-normal pairs were subjected to mutation calling with MuTect . To detect fusion transcripts , level 1 prealigned RNA-seq data in BAM format were downloaded from The Cancer Genomics Hub . To determine ER and HER2 statuses , clinical information was downloaded from the TCGA data portal . CCLE CN data were downloaded from the Memorial Sloan Kettering Cancer Center’s cBio portal [51] Genomic DNA was subjected to bisulfite conversion with an EpiTect Bisulfite Kit ( Qiagen , Valencia , CA ) . Converted DNA fragments were amplified by PCR using a Kapa HiFi Uracil+ Kit ( Kapa Biosystems , Woburn , MA ) with the following primer sets: BRCA1-1-S , 5′-TTAGAGTAGAGGGTGAAGGTTTTTT-3′; BRCA1-1-AS , 5′-AACAAACTAAATAACCAATCCAAAAC-3′; BRCA1-2-S , 5′-TTTTTTAGTTTTAGTGTTTGTTATTTTT-3′; BRCA1-2-AS , 5′-CCAAACTACTTCCTTACCAACTTC-3′; BRCA1-3-S , 5′-GTTGGTAAGGAAGTAGTTTGGGTTAG-3′; BRCA1-2-AS , 5′-AAACTCTCTCATCCTATCACTAAAAC-3′; RAD51C-1-S , 5′-GTTGAGGAATTTTTAGAGGTGAAATT-3′; RAD51C-1-AS , 5′-ATTCAAACAACTTATAAATAAAATC-3′; RAD51C-2-S , 5′-GAGAATTTATTGGGTTTGGTTTTT-3′; RAD51C-2-AS , 5′-AATTTCACCTCTAAAAATTCCTCAAC-3′ . Amplified PCR products were prepared for high throughput sequencing . FFPE 4 μm-thick sections were treated using an FFPE FISH Pretreatment Kit ( GSP Laboratory , Kobe , Japan ) and hybridized with BAC clone-derived three-color probes in a humidified chamber overnight at 37°C . Texas red- , Cy5- , and FITC-labeled probes were designed as the three-color probes to detect FGFR1 , RUNX1T1 , and CCNE2 loci , respectively ( GSP Laboratory ) . The sections were washed in 2× SSC , counterstained with 4 , 6-diamidino-2-phenylindole , and observed under a fluorescence microscope ( Leica CTR6000; Leica Microsystems , Wetzlar , Germany ) . Human embryonic kidney ( HEK ) 293T cells and mouse 3T3 fibroblasts were obtained from the American Type Culture Collection and maintained in Dulbecco’s modified Eagle’s medium ( DMEM ) -F12 supplemented with 10% fetal bovine serum ( FBS ) ( both from Life Technologies , Carlsbad , CA ) . The hypopharynx squamous cell carcinoma cell line BICR6 was obtained from Sigma-Aldrich and maintained in DMEM-F12 supplemented with 10% FBS . ChIP was performed using a SimpleChIP Plus Enzymatic Chromatin IP Kit ( Cell Signaling Technology , Danvers , MA ) according to the manufacturer’s instructions . Briefly , crosslinking of chromatin was achieved by incubation in 1% formaldehyde at room temperature for 10 min . Crosslinked chromatin was fragmented enzymatically with MNase for 25 min at 37°C . The antibodies used for ChIP were as follows: negative control normal rabbit IgG antibody ( Cell Signaling Technology , #2729 ) , anti-histone H3 rabbit mAb ( #4620 ) , and anti-acetyl-histone H3 ( Lys27 ) rabbit mAb ( #8173 ) . After reversal of crosslinking of immunoprecipitated chromatin , genomic DNA was extracted and then prepared for high throughput sequencing . LentiCas9-Blast ( Addgene plasmid # 52962 ) was a gift from Feng Zhang ( Broad Institute , Cambridge ) , and pgRNA-humanized ( Addgene plasmid # 44248 ) was a gift from Stanley Qi ( Stanford University , Stanford ) [52 , 53] . The following target sequences for guide RNAs were cloned into pgRNA-humanized: TGFA-int1-2 , 5′-CCCTGGGGTATACCTGTGAG-3′; TGFA-int1-6 , 5′-GGGTCACTCCAAACAAAGGA-3′; TGFA-en-4 , 5′-CCTGATGAGCATACACTCCG-3′; TGFA-en-5 , 5′-TATTCTCTCGGTCCTGCACG-3′; TGFA-en-6 , 5′-CACCTTAGGTACCAGCCGTG-3′; TGFA-en-7 , 5′-TGTATCTAGCACTTAGACCA-3′ . BICR6 cells were infected with LentiCas9-Blast , followed by selection with 10 μg/ml blasticidin for 4 days . BICR6 cells stably expressing Cas9 were then infected with a pair of pgRNAs to achieve deletion of the indicated genomic regions . The pGL4 . 10 luciferase vector ( Promega , Madison , WI ) was used . The enhancer regions were cloned upstream of the luciferase-coding sequence . The reporter constructs were then cotransfected with a control pGL4 . 74 ( Promega ) vector expressing Renilla luciferase . The luciferase signal was first normalized to the Renilla luciferase signal and then normalized to the signal of the empty pGL4 . 10 plasmid . Primers used for cloning were as follows: e6-S , 5′-TGTATGGGTTTCTTCCTGGGCTGT-3′; e6-AS , 5′-CAGTTTTTCAGGTTTCTCTGGGGTCC-3′; e7-S , 5′-TGGGCTTCATGACAGCATCCCTA-3′; e7-AS , 5′-TTGACATGGGCCATTACTCCATCC-3′ . The coding sequences of genes were amplified by RT-PCR and inserted into the retroviral plasmid pMXs-ires-EGFP ( Clontech , Mountain View , CA ) . To produce infectious viral particles , HEK293T cells were transfected with the plasmids together with ecotropic retroviral packaging plasmids ( Takara Bio , Otsu , Shiga , Japan ) . Virus particles were then used to infect 3T3 cells that were subsequently suspended in culture medium containing 0 . 4% ( wt/vol ) agar ( SeaPlaque GTG agarose; FMC BioProducts , Rockland , ME ) and layered on top of culture medium containing 0 . 53% ( wt/vol ) agar in six-well plates . Colonies were allowed to form for 21 days and then stained with crystal violet . 3T3 cells ( 1 × 106 ) expressing wild-type or mutant forms of the indicated proteins were also injected subcutaneously into BALB/c nu/nu mice for in vivo tumorigenicity assays . The mouse experiments were approved by the Institutional Animal Care and Use Committee of the University of Tokyo . The coding sequences of wild-type and mutant forms of NFKB1 were amplified by RT-PCR and inserted into the expression vector pcDNA3 . The plasmids were transfected into HEK293T cells , and then nuclear translocation of the N-terminal half of NFKB1 protein ( p50 ) was analyzed as follows . Cytoplasmic and nuclear fractions were prepared from cell lysates , separated by SDS-polyacrylamide gel electrophoresis , transferred to a membrane , and then subjected to western blotting to detect p50 and full-length NFKB1 protein ( p105 ) using an anti-NFKB1 antibody ( Cell Signaling Technology #3035 ) . The coding sequences of the C-terminal region ( CTR ) of wild-type and mutant forms of NFKB1 , which were tagged with Myc peptide , were amplified by RT-PCR and inserted into the expression vector pcDNA3 . The plasmids were transfected into HEK293T cells along with a plasmid expressing p50 tagged with the FLAG peptide . Total cell lysates were immunoprecipitated with an anti-FLAG antibody ( M2 , Sigma-Aldrich , St . Louis , MO ) and analyzed using an anti-Myc antibody ( Cell Signaling Technology , #2276 ) . To assess the stability of wild-type and mutant forms of the CTR , transfected HEK293T cells were treated with 10 μg/ml cycloheximide for the indicated times before total cell lysates were prepared . The total cell lysates were analyzed with anti-FLAG and anti-Myc antibodies . The densities of detected bands were measured using ImageJ software ( https://imagej . nih . gov/ij/ ) . The raw sequencing data have been deposited in the Japanese Genotype-Phenotype Archive ( JGA , http://trace . ddbj . nig . ac . jp/jga ) , which is hosted by DDBJ , under accession number JGAS00000000095 .
|
Cancer can result from genetic alterations , some of which can be good drug targets . To reveal genetic alterations that provide important information for the development of ideal therapeutic strategies for triple-negative breast cancer ( TNBC ) , TNBC tumor samples were subjected to comprehensive genomic analyses . We identified novel recurrent structural variations associated with enhanced expression of the TGFA gene that encodes one of the high affinity ligands for epidermal growth factor receptor ( EGFR ) . Although TGFA expression is known to be elevated in a subset of TNBC tumors , this is the first report of the mechanistic basis of this phenomenon . It is of particular importance considering that anti-EGFR agents are possible therapeutic options for TNBC patients . Our study also revealed several features associated with “BRCAness” , which is critical for identification of patients who may be responsive to platinum agents and/or poly ADP-ribose polymerase inhibitors . Thus , the data presented in this report may advance our understanding of the pathogenesis of TNBC .
|
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2017
|
Integrative analysis of genomic alterations in triple-negative breast cancer in association with homologous recombination deficiency
|
Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease . Unfortunately , the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind . Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs , we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact . Grouping patients into 408 non-exclusive patient-phenotype groups , we identified a functional association amongst the genes disrupted in 209 ( 51% ) groups . We find evidence for a significant number of molecular interactions amongst the association-contributing genes , including a single highly-interconnected network disrupted in 20% of patients with intellectual disability , and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype . Exploiting the systematic phenotyping of this cohort , we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that ( i ) this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway , and ( ii ) that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes , rather than sharing a more specific phenotype , inferring that these pathways are best characterized by their pleiotropic effects .
Developmental disorders and congenital abnormalities affect 3% of births , and represent an extremely heterogeneous group of disorders including intellectual disability , autism , and developmental delay , along a diverse range of structural and morphological defects[1] . The epidemiology of these heterogeneous disorders strongly implicates an underlying genetic etiology , with many patients possessing an increased burden of copy number variants ( CNVs; regions of the genome > 1Kb that are deleted or duplicated ) . CNV screens now routinely included in primary diagnostics[2] with exome analyses expected to grow in use as the cost falls [3 , 4] . However , the heterogeneity in patient phenotypes is similarly reflected in the underlying genetic variation making it difficult to pin-point those particular genes whose mutation contributes to the phenotype . The field of disease genomics has , in particular , heralded two developments to address heterogeneous and multigenic disorders , namely ( i ) deep and systematically-defined patient phenotypes[5 , 6] and ( ii ) pathway analysis approaches[7 , 8] . For genetically heterogeneous disorders , the power of a cohort of patients to identify a shared pathoetiology may be diminished by the presence of multiple etiologies , each etiology contributing non-exclusively to different aspects of the phenotypic heterogeneity . Accordingly , it is often advantageous to analyse more phenotypically-similar subgroups , assuming that these subgroups would be enriched for a particular etiology[9] . Indeed , the observation by clinicians of marked phenotypic similarities across a broad range of features for a particular subgroup of patients has enabled the identification of the genetic causes of many syndromes; for examples see[10] . To enable large-scale , systematic and automated patient phenotypic comparisons , phenotype ontologies , such as the Human Phenotype Ontology ( HPO ) [11 , 12] , have been developed . These ontologies consist of thousands of predefined phenotypic terms arranged in a hierarchy in which more specific child terms are organised underneath broader parent terms; for example , a patient ascribed the more specific phenotype “abnormality of the retina” would also recursively inherit any overarching phenotypic terms such as “abnormality of the eye” . Once these phenotypic terms have been rigorously assigned to large numbers of patients , ontologies such as the HPO enable various degrees of phenotypically-similar subgroups of patients to be systematically and objectively constructed , permitting the search for shared pathoetiologies at many levels of phenotypic homogeneity . A second challenge for large-scale analyses of patient phenotypes is that often only the presence of phenotypes is recorded without confirmation that unrecorded phenotypes had been considered . This forces the dangerous assumption that the absence of evidence for the presence of a given phenotype is evidence of absence of that phenotype . Many non-obvious and non-superficial genotype/phenotype relationships may be missed unless the presence/absence of phenotypes are explicitly determined and , in particular , pleiotropy will likely be under-reported[6] . Complementing patient phenotype subgrouping , pathway analysis approaches rely on the observation that disruptions to different genes that operate within the same pathway often produce similar phenotypes[9] . Thus , the analysis of patients that share a common phenotype , regardless of whether they can be classed into an over-arching disorder , may yield insights into commonly disrupted pathways underlying that phenotype and contribute to the spectrum of presentations in each patient . This approach is well suited to the study of multigenic disorders as pathway approaches gain power from coverage of the pathway , rather than recurrent hits to the same gene . One approach to identifying commonly disrupted pathways amongst distributed variants is to employ “functional enrichment” approaches[13] . This approach proposes that the genes affected by dispersed variants that act within a common pathway are likely to share other functional or biological characteristics , such as being annotated to a particular biological process[14 , 15] , exhibiting a particular expression pattern[16] , expressing protein products that interact with each another[17] and/or presenting a shared phenotype upon their orthologue’s disruption in a model organism[15 , 18 , 19] . Such collections of gene annotations vary both in terms of their rates of false positives , especially when formed from high-throughput experiments or computational-inference , and false negatives , for example where gene coverage is poor[20–22] . Thus , different annotation types may be combined to increase confidence that genes are functionally concordant[23 , 24] . In this study , we tested the paradigm that pathway analysis approaches applied to a large and systematically-phenotyped cohort that present heterogeneous developmental disorders can detect common molecular pathologies and the extent to which these inferred common etiopathologies confer common phenotypic presentations . Focusing on 197 patients that possessed de novo CNVs smaller than 5 Mb , we systematically grouped them according to the structure of the HPO and applied a range of complementary functional enrichment approaches that converged on numerous molecular pathways underlying a range of phenotypes . These gene networks were deemed biologically coherent through enrichments of direct molecular interactions , and we provide an exemplar as to how they can be used as “baits” to identify genes disrupted in other cohorts that participate in the same network . Finally , we show that patients whose variants contribute to the same functional enrichments are significantly more phenotypically-similar overall and results primarily from pleiotropic effects arising from the perturbation of the same inferred network , but that this similarity varies with the enrichment approach employed .
We sought to employ common functional enrichment and pathway analysis to a large cohort of deeply and systematically-phenotyped patients presenting with heterogeneous developmental disorders , in order to identify the genes and molecular pathways underlying these phenotypes and to investigate the phenotypic similarity among patients whose variants affect genes detected to lie in the same pathways . We focused on sporadic patients possessing de novo CNV events as it is often the case that the de novo CNV mutation is consequential , and thus copy change of one or more of the genes disrupted by the CNV is responsible for the phenotypes observed2; 10 . Furthermore , we excluded patients with CNVs >5Mb , as the large numbers of genes affected make it substantially more challenging to identify specific functional enrichments . Through our integrative approach , we sought to identify the genes and pathways underlying each phenotype presented by members of the cohort . A cohort of 4297 patients was collected by the Radboud University Medical Centre , Nijmegen , the Netherlands . All patients were diagnosed with intellectual disability , developmental delay and/or congenital abnormalities . Each patient was deeply phenotyped by clinicians , using terms from the Human Phenotype Ontology ( HPO ) to describe their clinical abnormalities . The HPO contains over 10 , 000 terms for clinical phenotypic abnormalities , which relate to one another through a hierarchical structure , with less specific parent terms , covering more specific child terms . All parent ( more general ) phenotypic terms were additionally assigned to patients based on their clinically-assigned phenotypes . Central to the analyses performed in this study , these patients were systematically phenotyped and thus each patient was considered for the same phenotypes as every other , enabling accurate comparison of patient phenotypic similarity . Of 1663 rare CNVs observed within at least one patient in the cohort , 437 were identified as de novo . Filtering our patients to include those that had only a de novo CNV shorter than 5Mb left 197 patients remaining ( see Materials and Methods ) . Of these , 154 patients ( 78% ) had intellectual disability of varying severity , 80 were diagnosed with developmental delay , 54 with growth abnormalities , and 37 with autistic spectrum disorder ( ASD ) . These 197 patients possessed 826 distinct HPO phenotypes ( individuals possessing 2–182 phenotypes , including parental terms ) , while the median number of phenotypes per patient increased to 31 . There were 219 de novo CNVs remaining across the 197 filtered patients , with a median size of 1 . 37 Mb . Of these , 82 were duplication , or gain , CNVs , while the remaining 137 were deletion , or loss , CNVs . Gains and Losses had a median size of 1 . 36Mb and 1 . 40Mb respectively . 2907 unique genes were affected across all 197 patients , ranging from 0–190 genes per patient , with a median 95 gene disrupted per patient . We employed a multifaceted functional genomics approach to analyzing the genes disrupted in the cohort . In turn , we investigated each set of genes found to be affected by de novo CNVs in patients that shared a specific HPO phenotype , where patients sharing the phenotype numbered 3 or more ( 408 patient-phenotype groups ) . For each phenotype , we employed a four-way functional genomics analysis , to identify functional associations between genes disrupted in these particular patient-phenotype groups which could represent a disrupted biological process that underlies the shared phenotype . Firstly , we employed a Gene Ontology ( GO ) analysis[25] , in order to determine whether or not genes disrupted with each phenotype were associated with any particular GO terms , using a whole genome background as a comparator . The second method applied was to similarly determine enrichments among disrupted genes using pathway annotations from the Kyoto Encyclopedia of Genes and Genomes ( KEGG ) [26] . As a third method , we examined the abnormal phenotypes observed from gene disruption events ( “knockouts” ) in mouse [18 , 27] . For this , we asked whether the unique mouse orthologues of genes affected by these CNVs yield particular phenotypes when disrupted . Finally , our fourth method examined whether or not genes from patients’ CNVs clustered together in a gene co-expression network . Given these patients predominantly neurological phenotypes , we used the BrainSpan dataset which measured the spatiotemporal expression of genes across 16 brain regions and at 6 developmental time points ( see Materials and Methods ) . Each of these functional association approaches was applied to each of 408 sets of genes disrupted by CNVs in patients presenting a particular phenotype ( patient-phenotype groups ) . Genes variant in only two patient-phenotype groups were found to possess significant functional associations using all four of the methods applied , namely HP:0001250 ( Seizures ) ( Fig . 1 ) and HP:0010864 ( Intellectual disability , Severe ) . Significant enrichments using three of the methods were observed in a further 64 patient-phenotype groups , enrichments for two methods for 120 patient-phenotype groups , and for just one method in a further 143 groups . Of the four methods employed , enrichments of phenotypes from mouse-orthologue knockouts ( MGI ) gave the least number of significant results , identifying functional association among affected genes in only 12 phenotype groups including HP:0001250 ( Seizures ) and HP:0000717 ( Autism ) ( S1 Table ) . While the MGI method identified fewest associations , the enriched terms were the most relevant to the particular HPO phenotypes . For example , for patients with Seizures we saw an enrichment of genes whose mouse orthologue knockouts present with , amongst others ( Fig . 1 ) , Absence seizures ( MP:0003216; 6 . 2-fold enrichment; p = 3 x 10–4 ) . Similarly , in patients with HP:0010864 ( Intellectual Disability , Severe ) we see an enrichment of mouse synaptic phenotypes such as Abnormal synaptic transmission ( MP:0003635; 3 . 3-fold enrichment; p = 2 . 0x10–5 ) . This was in contrast with the results for Intellectual Disability , mild ( HP:0001256 ) which was significantly enriched in learning phenotypes in mouse , such as abnormal associative learning ( MP:0002062; p = 3 . 6x10–6 ) . When these two subsets of patients were combined under the more general term of Intellectual Disability ( HP:0001249 ) no mouse phenotypes were significantly associated but many signalling pathways described in KEGG were significantly enriched among the patients , including the MAPK signalling pathway , and Neurotrophin signalling pathway . Other methods provided a larger number of significant results , with enrichments of GO terms found for each of 121 human phenotypes; however these enrichments were generally smaller , and involve less specific categories than those observed using mouse phenotypes ( S1 and S2 Tables , S1 Fig . ) . Additionally , affected genes within each of 189 phenotype groups were associated with particular KEGG pathways ( S3 Table ) , while genes affected within each of 262 phenotype groups showed similarities in their brain spatiotemporal expression patterns , clustering significantly in the BrainSpan expression network ( S4 Table ) . For 186 of 408 patient-phenotype groups , we found functional associations using multiple methods , and of these 177 ( 95% ) phenotype groups identified the same genes using multiple methods , with the number of genes repeatedly identified for these groups ranging from 1 to 355 ( Fig . 2 , S5 Table ) . A central tenet of pathway approaches is that a common phenotype can result from the perturbation of different genes that act within a common molecular pathway . We sought to validate that these functional association approaches were identifying commonly perturbed molecular pathways through protein-protein interactions , arguing that the protein products of genes involved in the same molecular pathway are more likely to directly interact with one another . Considering each of the 177 sets of multiply detected candidate genes and employing the Dapple protein-protein interaction ( PPI ) network[28] , we found that 65 ( 37% ) phenotype-grouped candidate genes showed significant clustering of genes within the PPI network demonstrating that the candidate genes identified for many of these phenotypes work together within the same molecular pathways ( Fig . 2 , S4 Fig . ) To demonstrate the relevance of these phenotype-associated molecular networks beyond the cohort considered here , we looked for genes acting in the same molecular pathways that were affected by de novo CNVs in a second set of patients presenting with the same phenotype . Specifically , given each of the 65 PPI molecular networks perturbed by CNVs in Nijmegen patients presenting with the same specific phenotype , we asked whether the proteins encoded by genes found to be copy number changed in an additional cohort with the same phenotype also interacted within the same molecular networks . For this , we considered patients possessing de novo CNVs that were annotated within the DECIPHER database[29] . Although the DECIPHER patients have not been systematically phenotyped and their presentations denoted using the LDDB dysmorphology terms[30] rather than the HPO phenotypes , 15 LDDB terms used to describe their phenotypes could be mapped equivalently to 15 of the 65 HPO terms for which a PPI was identified in the NIJMEGEN patients ( S7 Table ) . Of these 15 phenotypes , only for Microcephaly was there found to be a sufficient number of genes in both the NIJMEGEN-derived PPI network and DECIPHER patients CNVs to test for interactions . Nonetheless , after 13 DECIPHER patients whose variant genes participated in the NIJMEGEN-derived microcephaly PPI network , the genes variant in the remaining 58 DECIPHER patients with Microcephaly were found to interact with the NIJMEGEN microcephaly PPI network genes significantly more frequently than expected ( p = 0 . 04; Fig . 3B ) , demonstrating recurrently hit phenotype-associated pathways . Most notably , whereas the NIJMEGEN-derived PPI molecular network alone is fractured into four unconnected sets of interacting genes , the interacting genes identified from the DECIPHER patients link three of these disparate groups to form a coherent molecular pathway ( Fig . 3B ) . The PPI network perturbed in 14/27 ( 52% ) of Nijmegen patients and perturbed in 13/71 DECIPHER patients with Microcephaly was able to identify genes interacting with the same network that were perturbed in an additional 30/71 ( 42% ) of DECIPHER patients , implicating this network’s disruption in 57/98 ( 58% ) of all microcephaly patients considered ( S6 and S7 Tables ) . Known developmental syndromes , particularly those involving ID , are frequently identified based upon shared phenotypic characteristics beyond ID , which may reflect the pleiotropic effects of a recurrently mutated gene [31–35] . Moving beyond a mutation in a single gene , we reasoned that if a functional enrichment identified among the copy number variant genes within a given set of patients identifies a common biological pathway perturbed within those patients , then the consequence of perturbing the same pathway may yield a similar set of phenotypes . To investigate this hypothesis , for each significant functional enrichment and the respective patient-phenotype group it was identified in ( S1–S4 Tables ) , we subdivided the patients with that phenotype into those whose variant genes contribute to that specific functional enrichment ( “contributing patients” ) and those patients whose copy number variant genes do not contribute ( “non-contributing patients” ) . Exploiting the consistent and structured phenotyping of the cohort , we then compared the pairwise phenotypic similarity amongst contributing patients to the pairwise similarity between contributing and non-contributing patients ( S5 Fig . ) . Overall , we found a significant excess of instances where contributing patients are more similar to each other than they are to non-contributing patients; p = 4 x 10–4 , one-sided binomial test ( Fig . 4A ) . However , this is highly variable between the different functional genomics resources used to identify the functional enrichment , as well as between phenotypes examined . Only patients whose copy number variant genes showed significantly co-ordinated brain expression patterns within the BrainSpan data were consistently found to be more similar in their overall phenotypes as compared to pairs of patients whose genes were not similarly co-ordinately expressed in the brain ( Fig . 4A and B ) . Considering the remaining 3 , 871 patients without de novo CNVs , patients whose CNVs affected genes co-expressed within BrainSpan continued to show the most significant phenotypic similarity when the analysis was repeated considering the phenotypic similarity amongst patients whose inherited CNVs affected the previously-identified candidate pathway genes . This was also true for phenotypic comparisons involving patients whose CNVs affected genes related to the candidate pathways ( have the same annotation or are co-expressed with or have a PPI with candidate pathway genes ( See Methods ) ) , but here patients whose CNVs affected novel genes with the same GO annotation also demonstrated phenotypic convergence ( S6 Fig . ) . Furthermore , restricting the patient phenotype comparisons to those patients possessing copy number variant genes that contributed to enrichments identified by two different functional resources did not increase the proportion of cases where contributing patients were more similar to each other than to non-contributing patients ( 14% vs 13% , p >0 . 9 , Fig . 4A ) . For those phenotypic comparisons where significantly similar phenotypes were observed amongst patients contributing to a functional enrichment ( p < 0 . 05 , 2-sided Wilcox-rank-sum test; Fig . 4A , blue points ) , we considered whether the functional enrichment was segregating patients based on more fine-scale differences of the phenotype that was associated with the enrichment or whether it reflected co-morbid phenotypic characteristics distinct from the enrichment-associated phenotype . To examine this , we repeated the phenotype-similarity analysis including only the child terms ( subterms ) of the enrichment-associated phenotype term ( Fig . 4C ) . In almost all cases , the distribution of subterms was indistinguishable between patients contributing to the pathway enrichment and non-contributing patients , demonstrating that the phenotypic similarity between patients whose variant genes contribute to the same functional enrichment was produced by common co-morbidities of phenotypes distinct from the enrichment-associated phenotype . Taken together , our findings propose that the copy number variation of genes that contribute to those functional enrichments shared by patients who present with significantly similar phenotypes underlie the broad spectrum of phenotypes presented by these patients as a consequence of the perturbing the same inferred molecular pathway . Finally , since the same KEGG and GO annotations were significantly associated with multiple human phenotypes , we combined patients from multiple patient-phenotype sets ( patients sharing a particular phenotype ) where those phenotypes had been associated with the same GO or KEGG pathway ( Fig . 4D ) . Three GO pathways were significantly associated with fewer than 15 human phenotypes ( ion channel , nutrient reservoir , and peptidase ) ; these identified subsets of patients who are significantly more similar to each other , whereas the remaining three GO pathways ( plasma membrane , receptor , and signal transduction ) were significantly associated with more than 30 human phenotypes and did not identify phenotypically similar patient subsets . Similarly the four KEGG pathways significantly associated with more than 30 human phenotypes failed to identify phenotypically similar patient subsets . However , only five of the thirteen KEGG pathways associated with fewer than 30 human phenotypes identified phenotypically similar patient subsets; these tended to be the more biologically plausible pathways ( eg . Cell motility , Nervous system , and Transport and Catabolism ) . The eight which failed to identify phenotypically similar patient subsets tended to be more general or unexpected pathways ( eg . Glycolysis , Drug , and Cancer; Fig . 4D ) . Pathways significantly enriched in many human phenotypes may reflect biases in CNV occurrence , which have not been completely eliminated by removing genes found in control CNVs ( see Materials and Methods ) .
This study represents the first systematic functional genomics analyses of a systematically and deeply phenotyped cohort of patients presenting with developmental disorders . By grouping patients on the presence of a common phenotype , as defined by a shared HPO term , and applying often-used functional enrichment approaches to the genes affected by those patients’ de novo CNVs , we identified functional enrichments for 329 ( 81% ) of 408 patient-phenotype groups ( S1–S4 Tables ) . For 177 patient-phenotype groups the same genes were identified using more than one approach; and for 65 ( 37% ) of these we found evidence for a significant number of molecular interactions between genes supporting shared molecular pathoetiologies ( Fig . 2 , 3 and 5; S4 Fig . and S6 Table ) . The generality of these pathways was further demonstrated by the ability of the microcephaly PPI network to identify additional pathway members mutated in another cohort with a similar phenotype ( Fig . 3 ) . Exploiting the “evidence of absence” of a phenotype among these patients , we were able to test the phenotypic convergence amongst patients whose variant genes contribute to the same functional enrichment . Overall , we find that there is significant phenotypic convergence providing general support for the “same perturbed molecular pathway , similar resulting phenotype” paradigm , but we note ( i ) that this relationship shows significant variation across the different functional genomics resources used to infer a commonly perturbed molecular pathway among a group of patients , and ( ii ) that these phenotypic convergences result from these patients sharing many distinct phenotypes , rather than sharing a more specific phenotype , suggesting that these pathways are best characterised by their pleiotropic effects ( Fig . 4 ) . Phenotypic convergence amongst patients whose variant gene contributed variant gene contributed to inferred ( GO , expression ) and/or determined ( KEGG , PPI ) molecular pathways was identified from the shared spectrum of distinct phenotypes presented by these patients , indicating common pleiotropic effects arising from the disruption of the inferred molecular pathway . Patients with the same perturbed pathway did not form a more specific phenotypic-subgroup , based upon sharing more specific features ( subterms ) , within the whole group pf patients presenting that phenotype ( Fig . 4C ) . Inevitably , this may in part be a consequence of the phenotypic resolution captured for these patients , but we note that most patient phenotypic clustering based on subterms performed poorly including the more phenotypically-detailed “Abdomen” patient/pathway groups . Irrespectively , our finding of common pleiotropic effects arising from perturbing the same pathway strongly supports broad , systematic patient phenotyping to identify shared underlying molecular pathology [6 , 36] . Systematically combining large-scale molecular and phenotypic variation is at the heart of disease genomics . However , the limitations of attempts to correlate imposed categorisations of both gene function and patient phenotype are obvious; both depend on limits of experimental/diagnostic techniques , prevailing ideas of biologically- or clinically-relevant observations , and motivation to investigate a given gene or patient . Surprisingly , the functional enrichment resource that is arguably the most well-aligned with HPO phenotypes[37] , namely the MGI mouse phenotypes , appeared to perform poorest in this study , both in detecting functional associations among variant genes ( S1 Table ) and in identifying phenotypically homogenous patient groups ( Fig . 4A ) . Importantly , neither the literature-based pathways of the KEGG database nor GO-defined functionality delivered as many functional associations , nor identified as much phenotypic homogeneity within associations , as the most functionally/phenotypically-agnostic approach of correlated gene expression ( BrainSpan; Fig . 2 & 4B ) . Despite the pleiotropic character of the phenotypic convergences , we found that a brain-specific gene expression set ( BrainSpan ) proved more effective than a body-wide expression set ( GTEx; see Materials and Methods; S2 Fig . ) . This may reflect the preponderance of neurological phenotypes in the cohort and/or the value of BrainSpan’s longitudinal expression data . Regardless , these findings bode well for future studies as ever more detailed systematic gene expression maps are promised[38] ( www . brain-map . org ) . Despite current limitations in our ability to map phenotypes between different cohorts/standards , we demonstrated the utility of these networks . Using the Microcephaly PPI network as a “bait” , we were able to identify an additional 51 gene members of this interaction network copy changed amongst DECIPHER Microcephaly patients , and found this network perturbed in 58% of all microcephaly patients considered here ( Fig . 3 ) . The “bait” network ( Fig . 3A ) contained genes such as AKT3 , considered the underlying cause for the microcephaly in patients with the 1q44 microdeletion syndrome[39] , and MAPK1 , involved in neurogenesis[40] and located within the distal 22q11 deletion frequently associated with microcephaly[41] . In addition , the extended network ( Fig . 3B ) contains several genes previously associated with an abnormal head circumference including ACTB in Baraitser-Winter syndrome ( MIM #243310 ) [42] , AKT1 in Proteus syndrome ( MIM #176920 ) [43] , CASK in Mental retardation and microcephaly with pontine and cerebellar hypoplasia ( MIM #300749 ) [44] , and NDE1 in microcephaly and lissencephaly[45 , 46] . Other genes within the combined network are involved in neuronal progenitor cell proliferation , a common mechanism underlying microcephaly[47] ( RAC1[48 , 49] and GNB1[50] ) and neuronal development ( CEBPB[51] , L1CAM[52] , MAPT[53] , PAK2[54] , SPTBN1[55] , and YWHAE[56 , 57] ) . The most common phenotype , Intellectual disability ( ID ) , was observed in 78% of the cohort considered here , and thus is of particular interest . Within the de novo CNVs of the 154 patients presenting with ID , 68 potential candidate genes were identified using enrichments from at least two different methods ( GO , KEGG , or BrainSpan expression ) . Of these 68 genes , the proteins expressed by 33 genes had known interactions with proteins expressed by other candidate genes , far more than would be expected by chance ( p < 1x10–4 ) , with 30 of these genes forming one single interacting cluster ( Fig . 5 ) . This cluster comprises of a selection of genes that have been associated previously with intellectual disability , such as YWHAE [58] , SOS1[59] , and MAP2K2 [60] , and several whose function makes them likely candidates for involvement in ID . For example , CAMK2 encodes a subunit of the Calcium/calmodulin-dependent protein kinase type II that is critical for regulation of synaptic plasticity[61] . This gene has been found to harbor a de novo mutation in a patient with severe intellectual disability[4] , and an intronic SNP ( rs11000787 ) which has been associated with memory performance[62] . In addition , MEF2D is a member of the myocyte enhancer factor-2 family of transcription factors that regulates neuronal development[63] . Mutations in another member of this family , MEF2C , have been observed previously in patients with severe ID[64] . Furthermore , ID patients whose CNVs perturb this network present significantly similar phenotypes as compared to other patients with ID ( p = 0 . 016; Fig . 4A ) . The single interacting cluster of 30 genes in this network potentially explains 31/154 ( 20% ) of patients with ID in the cohort ( Fig . 5 ) , and thus the nature of this molecular convergence warrants further study . Finally , the 826 phenotypes present amongst patients in this cohort do not represent the full spectrum of human phenotypic variation ( the HPO ontology alone contains 10 , 000 unique terms ) . Even the focused phenotyping of developmental abnormalities among the cohort considered here could be significantly enriched through detailed brain imaging , as well as longitudinal and more quantitative phenotyping[36] . Similarly , our focus only on those genes affected by de novo CNVs ignores the influence of the genetic background on phenotype[65] . Nonetheless , the systematic genotyping and phenotyping of these patients has in turn enabled systematic pathway-based genotype/phenotype approaches that identify extensive molecular networks that appear perturbed , often with pleiotropic consequences , thereby giving insight into the more rigorously genotyped and phenotyped future of genomic medicine . These pathways could be used to categorize patients with currently unknown developmental disorders and potentially identify new developmental syndromes .
The patient data were previously described in detail in a manuscript by Vulto-van Silfout et al . [66] , but shall be described here in brief . Four thousand two hundred and ninety seven patients with either intellectual disability , developmental delay , and/or multiple congenital abnormalities were recruited by the Radboud University Nijmegen Medical Centre . Each patient was phenotyped by clinicians using a uniform and standardised clinical form , classified using the Human Phenotype Ontology ( HPO ) terms[12] . More general HPO terms assigned to individuals were imputed from specific terms recorded . Of ∼10 , 000 possible HPO phenotypic terms covering the full spectrum of human phenotypic abnormalities , 1350 terms were assigned to one or more patients within the cohort . DNA samples were mainly taken via peripheral blood and analysed using the Affymetrix 250k Nspl SNP array platform ( 262 , 264 SNPs , 200 Kb resolution ) . CNVs were called where there were at least five or seven consecutive aberrant SNPs , for losses and gains , respectively . Where CNVs were observed , parental DNA was considered in order to determine whether CNVs were de novo , or to determine the mode of inheritance . We focused on the subset of 197 patients who possessed likely-causative de novo CNVs of <5Mb , amongst whom a total of 826 HPO phenotypic terms had been assigned . To demonstrate the utility of the networks identified in this study ( see Results ) , we selected 93 de novo CNVs possessed by 71 patients annotated with a Microcephaly ( London Dysmorphology Database code: 32 . 08 . 05 ) phenotype that were recorded within the DECIPHER ( DatabasE of Chromosomal Imbalance and Phenotype in Human using Ensembl Resources ) database ( S7 Table ) . Merging overlapping ( by at least 1bp ) or bookended CNVs ( losses and gains combined ) yielded 76 CNV regions ( CNVRs ) . From these 76 CNVRs , we removed 8 CNVRs ( representing 13 patients ) that affected genes that already participate in the Microcephaly network we had identified among the Nijmegen cohort ( Fig . 3 ) and removed a further 12 CNVRs that did not affect genes annotated within the protein-protein interaction ( PPI ) database and thus could not be considered . Our final set of DECIPHER CNVs from Microcephaly patients contained 55 CNVRs , overlapping 606 genes that were represented in the PPI database ( S7 Table ) . Phenotypic similarity between patients was calculated using the Goodall3 measure [72] . The Goodall3 measure gives a high weight to the shared presence of rare phenotypes and the shared absence of common phenotypes and was deemed more appropriate than other measures such as semantic similarity ( S3 Fig . ) . For each pair of patients , the phenotypic similarity was calculated as the sum of the weighted similarity ( G ) of the presence/absence of each of all the phenotypes annotated to any of the 197 patients considered , where G is weight by the frequency ( fi ) of the phenotype in the patient population: Gi={1-fi2ifiis present in both patients1− ( 1−fi ) 2ifiis present in neither patient0ifiis present in only one patient For each of the significant functional enrichments , the group of patients sharing the respective HPO term was divided into those patients with variant genes participating in the enrichment ( “contributing patients” ) and those without ( “non-contributing patients” ) . The significance of the difference between the phenotypic similarity amongst contributing patients and between contributing patients and non-contributing patients was evaluated using a two-sided Wilcox-rank-sum test ( S5 Fig . ) . To ensure the test was well-powered , only those cases where there were at least 10 contributing patients and at least 10 non-contributing patients were considered .
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Developmental disorders occur in ∼3% of live births , and exhibit a broad range of abnormalities including: intellectual disability , autism , heart defects , and other neurological and morphological problems . Often , patients are grouped into genetic syndromes which are defined by a specific set of mutations and a common set of abnormalities . However , many mutations are unique to a single patient and many patients present a range of abnormalities which do not fit one of the recognized genetic syndromes , making diagnosis difficult . Using a dataset of 197 patients with systematically described abnormalities , we identified molecular pathways whose disruption was associated with specific abnormalities among many patients . Importantly , patients with mutations in the same pathway often exhibited similar co-morbid symptoms and thus the commonly disrupted pathway appeared responsible for the broad range of shared abnormalities amongst these patients . These findings support the general concept that patients with mutations in distinct genes could be etiologically grouped together through the common pathway that these mutated genes participate in , with a view to improving diagnoses , prognoses and therapeutic outcomes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Gene Networks Underlying Convergent and Pleiotropic Phenotypes in a Large and Systematically-Phenotyped Cohort with Heterogeneous Developmental Disorders
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Gammaherpesviruses such as Epstein-Barr virus ( EBV ) and Kaposi's sarcoma-associated herpesvirus ( KSHV , HHV-8 ) establish lifelong latency in their hosts and are associated with the development of several types of malignancies , including a subset of B cell lymphomas . These viruses are thought to co-opt the process of B cell differentiation to latently infect a fraction of circulating memory B cells , resulting in the establishment of a stable latency setpoint . However , little is known about how this infected memory B cell compartment is maintained throughout the life of the host . We have previously demonstrated that immature and transitional B cells are long-term latency reservoirs for murine gammaherpesvirus 68 ( MHV68 ) , suggesting that infection of developing B cells contributes to the maintenance of lifelong latency . During hematopoiesis , immature and transitional B cells are subject to B cell receptor ( BCR ) -mediated negative selection , which results in the clonal deletion of autoreactive B cells . Interestingly , numerous gammaherpesviruses encode homologs of the anti-apoptotic protein Bcl-2 , suggesting that virus inhibition of apoptosis could subvert clonal deletion . To test this , we quantified latency establishment in mice inoculated with MHV68 vBcl-2 mutants . vBcl-2 mutant viruses displayed a marked decrease in the frequency of immature and transitional B cells harboring viral genome , but this attenuation could be rescued by increased host Bcl-2 expression . Conversely , vBcl-2 mutant virus latency in early B cells and mature B cells , which are not targets of negative selection , was remarkably similar to wild-type virus . Finally , in vivo depletion of developing B cells during chronic infection resulted in decreased mature B cell latency , demonstrating a key role for developing B cells in the maintenance of lifelong latency . Collectively , these findings support a model in which gammaherpesvirus latency in circulating mature B cells is sustained in part through the recurrent infection and vBcl-2-mediated survival of developing B cells .
The human gammaherpesviruses , Epstein-Barr virus ( EBV ) and Kaposi's sarcoma-associated herpesvirus ( KSHV , HHV-8 ) , and the genetically- and pathogenically-related murine gammaherpesvirus 68 ( MHV68 , γHV68 , MuHV-4 ) , establish lifelong latent infections in circulating B cells . B cells are a crucial component of the adaptive immune response as they are capable of mounting responses to an enormous range of antigens through the production of antibodies and the establishment of immunological memory . Hence , maintaining a fully functional and diverse B cell population is critical for protection against a variety of bacterial and viral infections . Although gammaherpesvirus infections have been linked with the development of a considerable number of malignancies including B cell lymphomas and Kaposi's sarcoma , such pathogenic outcomes occur rarely in healthy hosts and have vastly increased prevalence in immunosuppressed populations [1]–[3] . Thus , gammaherpesviruses have evolved a symbiotic relationship with the host immune system in which they are able to maintain lifelong infection in B cells without significantly altering normal B cell function or repertoire . The most widely held model for latency establishment posits that gammaherpesviruses have evolved mechanisms to mimic natural B cell activation pathways , such that infection of naïve follicular B cells results in their activation and subsequent differentiation to memory B cells [4] . The model contends that lifelong infection is maintained because latent virus is indefinitely retained in this long-lived pool of circulating , resting memory B cells . Work from Thorley-Lawson's group has provided important in vivo support for this concept by demonstrating that in chronically infected individuals EBV genome is maintained in a frequency of circulating memory B cells that , while variant among individuals , remains stable over time , suggesting that B cell homeostatic mechanisms maintain a lifelong latency setpoint [5] . Similarly , during chronic infection MHV68 is primarily restricted to class-switched memory B cells [6] , [7] and is maintained at a stable frequency over time [8] . While work with both EBV and MHV68 support the basic concept that virus-driven mature B cell differentiation contributes to lifelong latency , it remains unclear how memory B cell infection is maintained at a steady setpoint . The two most prevalent hypotheses hold that maintenance of the infected memory B cell pool occurs via reactivation of latent virus and reseeding naïve B cells , with subsequent virus-driven differentiation to memory B cells [9] , [10] , or via homeostatic proliferation , with virus episome replication and segregation to daughter cells [5] . However , one intriguing alternate possibility is that lifelong latency is facilitated by continual infection of newly generated developing B cells , which subsequently follow normal B cell maturation pathways . In support of this concept , newly formed splenic CD21−CD23− B cells have been reported to carry MHV68 genome [11] , [12] , and we have recently demonstrated that developing B cells harboring MHV68 genome are present in both the bone marrow ( pro-B/pre-B and immature B ) and the spleen ( transitional B ) throughout chronic infection [13] . However , the lifespan of these cells is only 24 to 72 hours; thus , these findings suggest that ( a ) MHV68 recurrently infects developing B cells or ( b ) MHV68 indefinitely extends the life of developing B cells . Because hematopoiesis results in the daily generation of new immature B cells which in turn maintain the mature B cell population [14]–[18] , recurrent or stable infection of these early stage cells could allow gammaherpesviruses to continually access the memory B cell compartment . During B cell maturation , the stochastic process of V ( D ) J recombination results in randomly generated B cell receptors ( BCRs ) on developing B cells . To guard the host against the generation of functional autoreactive mature B cells , immature and transitional B cells must navigate through multiple negative selection checkpoints . In the processes of central tolerance in the bone marrow and peripheral tolerance in the spleen , B cells that react with self-antigen are eliminated through apoptotic clonal deletion , are made anergic , or are subjected to further BCR editing [19]–[25] . BCR binding to self-antigen triggers the apoptotic death of immature and transitional B cells due in part to the low expression of host anti-apoptotic proteins Bcl-2 , Bcl-XL and A1 in these cells [26]–[31] . Consistent with this , enforced expression of host Bcl-2 or Bcl-XL in vivo allows the survival of autoreactive immature and transitional B cells [25] , [32]–[34] . Notably , several gammaherpesviruses encode orthologs of host anti-apoptotic proteins . For example , EBV BHRF1 , EBV BALF1 , and KSHV ORF16 all encode proteins with homology to Bcl-2 , and KSHV K13 encodes a protein with homology to the human FLICE inhibitory protein ( FLIP ) [35]–[39] . Similarly , MHV68 M11 encodes a Bcl-2 ortholog ( vBcl-2 ) [40] , [41] that is expressed during latency [12] , [42] . While the specific molecular role that MHV68 vBcl-2 plays in B cell infection has not been determined , it is capable of blocking Fas- , TNFα- , Sindbis virus- and dexamethasone-induced apoptosis [41] , [43]–[45] , as well as rapamycin- and starvation-mediated autophagy [46] , [47] . In vivo , MHV68 M11 mutants have demonstrated no significant defects during acute infection and only minor defects during latency [43] , [48]–[50] . Thus , EBV , KSHV and MHV68 all encode vBcl-2 orthologs that retain anti-apoptotic activity . However , it is unknown whether any of these proteins play a role in promoting the survival of developing B cells . To further define the role that gammaherpesvirus Bcl-2 orthologs play during chronic infection , we tested whether MHV68 vBcl-2 can promote the survival of developing B cells that undergo BCR-mediated selection . Using MHV68 mutant viruses , we found that vBcl-2 played a critical role in infection of immature and transitional B cells in vivo which could be complemented by host Bcl-2 . Further , we found that ectopically-expressed vBcl-2 protected immature B cells from BCR-mediated apoptosis . Finally , by depleting developing B cells during chronic MHV68 infection in vivo , we uncovered a role for developing B cells in the lifelong maintenance of MHV68 latency in circulating mature B cells .
Clonal deletion of self-reactive developing B cells is one of the core mechanisms utilized to enforce B cell tolerance . Transitional B cells are thought to be the primary target of clonal deletion in vivo , with this process resulting in the apoptotic death of a significant portion of the transitional B cell population [15] , [24] , [27] , [30] , [51] . Previous work from our laboratory has demonstrated that , following inoculation of wild-type mice , MHV68 maintains latency in a stable frequency of transitional B cells throughout chronic infection [13] . Because these cells have a high rate of turnover and undergo BCR-mediated negative selection , we questioned whether the virus could provide surrogate anti-apoptotic signals to facilitate the survival of infected cells . To test whether the MHV68 vBcl-2 protein played a role in transitional B cell infection , C57BL/6J ( B6 ) mice were inoculated with either wild-type MHV68 or a MHV68 mutant virus deficient in vBcl-2 expression ( MHV68 . vBcl2stop ) , and the frequency of latently infection transitional B cells was assessed by PCR . At day 15 post-intranasal ( i . n . ) inoculation , spleens were harvested and total CD19+AA4+ transitional B cells were isolated using flow cytometry ( Fig . 1A ) . Although the transitional B cell population in wild-type mice can be further subclassified into T1 , T2 and T3 B cells based on surface CD21 and CD23 expression [15] , we have previously demonstrated that all three populations are infected by MHV68 [13]; thus for experiments here we examined total transitional B cell infection . At 15 days post-inoculation , both the percentage of transitional B cells in the spleen and the absolute number of splenocytes were similar between the two viruses ( Table 1 ) . To determine the frequency of cells harboring viral genome , we performed limiting dilution nested PCR analysis , which allows the specific detection of a single copy of viral genome in a background of up to 50 , 000 uninfected cells [13] , [52] , [53] . Strikingly , mice inoculated with MHV68 . vBcl2stop displayed a 23-fold decrease in the frequency of infected transitional B cells compared to mice inoculated with wild-type MHV68 ( MHV68 1 in 590; MHV68 . vBcl2stop 1 in 13 , 500 ) ( Fig . 1B ) . This phenotype was not confined to early latency , as MHV68 vBcl-2 mutants were also attenuated in transitional B cells during long-term latency ( Fig . S1 ) . Although we postulated that the large reduction in MHV68 . vBcl2stop-infected transitional B cells was due to the inability of this mutant virus to block BCR-mediated apoptosis , an alternative hypothesis was that the reduction instead resulted from a low level of virus reactivating from latency – a process that is known to be reduced in MHV68 vBcl-2 mutants [49] , [50] and could conceivably be critical for re-seeding the transitional B cell population . To control for this possibility , we performed identical experiments using a MHV68 mutated in the viral cyclin D ortholog ( vCycD ) . Like the vBcl-2 mutant , the vCycD mutant virus ( MHV68 . vCycD . LacZ ) undergoes normal acute replication and latency establishment in whole splenocytes and peritoneal cells , but exhibits a low efficiency of reactivation from latently infected cells [50] , [54] . However , in contrast to the vBcl-2 mutant virus , the frequency of transitional B cells infected with MHV68 . vCycD . LacZ was similar to that of wild-type MHV68 ( MHV68 1 in 590; MHV68 . vCycD . LacZ 1 in 620 ) ( Fig . 1B ) , demonstrating that the decreased frequency of infected transitional B cells in the absence of vBcl-2 is not due to decreased infection secondary to reactivation . Together these data demonstrated that MHV68 vBcl-2 is critical for latent infection of transitional B cells in vivo , and suggested the possibility that vBcl-2 could promote the survival of transitional B cells that are induced to undergo apoptosis as a result of BCR-mediated negative selection . To further explore this possibility , we determined whether loss of MHV68 vBcl-2 expression similarly reduced infection of other B cells that are subjected to BCR-mediated selection events . During early bone marrow hematopoiesis , pro-B and pre-B cells undergo immunoglobulin gene rearrangement and thus do not express a completed cell surface BCR and are not subjected to BCR-mediated selection . In contrast however , in the final stage of bone marrow hematopoiesis immature B cells , which have completed the process of immunoglobulin gene rearrangement , express complete cell surface BCRs and are required to pass a key central tolerance selection checkpoint in which cells that recognize self-antigen are susceptible to clonal deletion [17] . To determine whether reduced MHV68 . vBcl2stop infection was indeed a feature of cells undergoing BCR-mediated clonal deletion , we quantified infection in B cell subsets that do ( immature B , transitional B ) or do not ( pro-B/pre-B , mature B ) , undergo selection . Fifteen days after inoculation of wild-type B6 mice with MHV68 or MHV68 . vBcl2stop virus , bone marrow cells and splenocytes were harvested , and purified populations of B cells were isolated using flow cytometric sorting ( Fig . 2A ) . Pro-B/pre-B cells ( CD19+AA4+IgM− ) and immature B cells ( CD19+AA4+IgM+ ) were isolated from the bone marrow , and transitional B cells ( CD19+AA4+ ) and mature B cells ( CD19+AA4− ) were isolated from the spleen . Total bone marrow and splenocyte cell numbers and percentages of each B cells subset were similar for wild-type and vBcl-2 mutant virus infections ( Table 1 ) . The frequency of cells harboring viral genome in each sorted population was determined using limited dilution nested PCR analyses ( Figs . 2B and 2C ) . While loss of vBcl-2 expression had no apparent effect on infection of the pro-B/pre-B cell population , infection of immature B cells and transitional B cells was significantly attenuated in mice inoculated with the vBcl-2 mutant virus ( immature 4 . 3-fold reduced , transitional 23-fold reduced ) . Furthermore , infection of the bulk mature B cell population in the spleen was not significantly altered in the absence of vBcl-2 expression . Notably , the significantly reduced frequencies of infected immature B cells in the bone marrow and transitional B cells in the spleen was not a reflection of decreased total infection , as the vBcl-2 mutant virus displays near wild-type virus frequencies of infection in bulk splenocytes [50] and bulk bone marrow cells ( Fig . S2 ) . Thus , these data demonstrate that vBcl-2 plays a key role specifically in B cell populations that are susceptible to BCR-mediated clonal deletion . Further , these results suggest the possibility that vBcl-2 could promote the survival of MHV68-infected developing B cells and thereby allow those cells to bypass key tolerance selection checkpoints . Based on the preferential requirement of vBcl-2 in B cells susceptible to clonal deletion , we hypothesized that vBcl-2 blocks BCR-mediated induction of the pro-apoptotic pathway . However , it is notable that in addition to its anti-apoptotic functions , vBcl-2 binds with high affinity to Beclin-1 [46] , [47] and blocks the induction of autophagy [46] , [47] , [49] . Thus , it was conceivable that either or both vBcl-2 functions played crucial roles during infection of developing B cells . Previous work using mutagenesis screens defined independent domains within vBcl-2 that are critical for each function – including a BH2 domain required for anti-apoptotic function and an α1 domain critical for anti-autophagic function – and facilitated the generation of specific loss-of-function MHV68 mutants [49] . To define the requirement of each activity in transitional B cells , we inoculated B6 mice with MHV68 , MHV68 . vBcl2 . ΔBH2 ( loss of anti-apoptosis function , normal anti-autophagy function ) or MHV68 . vBcl2 . Δα1 ( loss of anti-autophagy function , normal anti-apoptosis function ) and performed limiting dilution nested PCR assays on sorted transitional B cells ( CD19+AA4+ ) and control mature B cells ( CD19+AA4− ) at 16 days post-inoculation ( Figs . 3A and 3B ) . In support of our hypothesis , MHV68 . vBcl2 . ΔBH2 infection of transitional B cells was reduced 21-fold compared to mice infected with wild-type MHV68 . Strikingly though , the frequency of transitional B cell infection was similarly reduced ( 14-fold ) in mice infected with MHV68 . vBcl2 . Δα1 . In contrast , the frequencies of mature B cells that harbored viral genome were remarkably similar for all infection groups . Importantly , no significant differences in spleen cell numbers or percentages of B cell populations were observed among groups ( Table 1 ) . Thus , these data demonstrate that both the BH2 domain and the α1 domain of vBcl-2 are important for latent infection of transitional B cells , and suggest that actively blocking both apoptosis and autophagy in cells susceptible to clonal deletion is a key facet of MHV68 infection in vivo . The work described above supported the conclusion that a primary function of vBcl-2 during MHV68 infection is to block the apoptosis of developing B cells . This supposition is consistent with data demonstrating that developing B cells are selectively susceptible to apoptosis due to low levels of host Bcl-2 expression [28] , [55] . However , one alternative possibility was that MHV68 vBcl-2 mutant viruses are , either directly or indirectly , comprised in their ability to infect developing B cells . To distinguish these two possibilities , we performed complementation experiments in genetically mutated mice that express host Bcl-2 at a higher level than wild-type mice in developing B cells . New Zealand Black ( NZB ) mice spontaneously develop a lupus-like syndrome , characterized by the production of pathogenic auto-antibodies , in large part because transitional B cells from these mice are resistant to BCR-mediated apoptosis , allowing autoreactive B cells to breach B cell tolerance checkpoints [55] , [56] . The resistance of autoreactive transitional B cells to clonal deletion has been shown to correlate with elevated levels of Bcl-2 expression [55] . To confirm this phenotype , we sorted transitional ( CD19+AA4+ ) and mature ( CD19+AA4− ) B cells from the spleens of naïve wild-type B6 and NZB mice and western blotted for host Bcl-2 ( Fig . 4A ) . Indeed , transitional B cells isolated from NZB mice expressed Bcl-2 at a substantially higher level than transitional B cells from B6 mice , and at a level equivalent to B6 and NZB mature B cell populations , which are both resistant to BCR-mediated clonal deletion . To test whether increased expression of host Bcl-2 in transitional B cells complemented the loss of vBcl-2 anti-apoptotic activity , we performed limiting dilution nested viral genome PCR assays on transitional and mature B cells isolated from the spleens of NZB mice 16 days after inoculation with MHV68 or MHV68 . vBcl2 . ΔBH2 ( Fig . 4B ) . Interestingly , following inoculation of NZB mice , the frequency of transitional B cells carrying MHV68 . vBcl2 . ΔBH2 genome was not significantly different from that of wild-type MHV68 . Similar levels of infection between the two groups were also observed in mature B cells . These results stand in stark contrast to those from wild-type B6 mice ( summarized in Fig . 4C ) : While the frequency of transitional B cells harboring MHV68 . vBcl2 . ΔBH2 genome was reduced 21-fold in B6 mice ( 1 in 920 for MHV68 , 1 in 19 , 860 for MHV68 . vBcl2 . ΔBH2 ) , the frequency of infection was negligibly reduced in NZB mice ( 1 in 100 for MHV68 , 1 in 190 for MHV68 . vBcl2 . ΔBH2 ) . It is notable that , consistent with previous reports examining MHV68 infection of lupus-prone mice [57] , the frequency of viral genome positive cells was higher for both the transitional and mature B cell populations isolated from NZB mice as compared to B6 mice ( Fig . 4C ) . However , preformed infectious virus was undetectable in splenocytes from NZB mice , demonstrating that this result is not a reflection of enhanced lytic replication in these mice ( Fig . S3 ) . Collectively , these results demonstrate that the attenuation of an MHV68 vBcl-2 BH2 mutant virus in transitional B cells can be rescued by host Bcl-2 expression , and accordingly , that the vBcl-2 BH2 mutant is competent for transitional B cell infection . Thus , these results strongly support the hypothesis that the MHV68 vBcl-2 specifically promotes the survival of developing B cell populations that are susceptible to clonal deletion . To more directly test whether vBcl-2 could block BCR-mediated apoptosis of immature B cells , we generated stable immature B cells lines that expressed MHV68 vBcl-2 or host Bcl-2 . WEHI-231 is a murine IgM+ B cell line that displays the phenotype of immature B cells and has been widely used for in vitro studies of B cell selection and tolerance mechanisms , including the induction of BCR-mediated apoptosis [58] , [59] . To generate WEHI-231 cell lines that ectopically expressed vBcl-2 or host Bcl-2 , we engineered murine stem cell viruses ( MSCV ) that carried genes encoding full-length murine Bcl-2 or full-length MHV68 vBcl-2 fused with a C-terminal HA tag . The MSCV retroviral expression system has been extensively utilized to transduce mammalian cells with target genes of interest [60] , [61] . Following generation of recombinant MSCV stocks , viral particles were applied to cultured WEHI-231 cells , and stable cell lines carrying empty vector ( EV ) , host Bcl-2 ( Bcl-2 ) , or MHV68 vBcl-2 ( M11 . 1 and M11 . 2 ) were generated by antibiotic selection and subcloning . To verify the expression level of transduced genes in the engineered cell lines , we performed western blots on whole cell lysates from each line using antibodies directed toward murine Bcl-2 ( Fig . 5A ) or HA ( Fig . 5B ) . While the WEHI . Bcl-2 cell line expressed an increased level of Bcl-2 compared to control WEHI-231 cells , Bcl-2 expression in the other cell lines was unchanged , indicating that introduction of other MSCV vectors had no effect on host Bcl-2 expression . Both WEHI . M11 . 1 and WEHI . M11 . 2 effectively expressed HA-tagged vBcl-2 , although the expression level was slightly increased in the M11 . 2 line . Similar results were obtained by immunofluorescent microscopy ( Fig . 6 ) , demonstrating greatly enhanced expression of host Bcl-2 in the WEHI . Bcl-2 line and ectopic expression of vBcl-2 in both WEHI . M11 lines . Importantly , both Bcl-2 and vBcl-2 localized to mitochondrial compartments , as indicated by co-staining with MitoTracker Red . To test whether vBcl-2 could block the BCR-mediated apoptosis pathway , we cultured each cell line with or without anti-IgM for 16 hours then assayed the cleavage-based activation of the key pro-apoptosis enzymes caspase-9 ( Fig . 7A ) , caspase-6 ( Fig . 7A ) , and caspase-3 ( Fig . 7B ) . Although faint levels of the active , cleaved forms of all three caspases were detectable in unstimulated WEHI cells , their levels were enhanced nearly 10-fold in cells treated with anti-IgM . Because cleaved caspase-9 is a direct downstream product of Apaf-1 oligomerization and apoptosome formation , these results demonstrate that the pro-apoptotic Apaf-1 pathway was induced in BCR-stimulated WEHI cells . Identical results were obtained in the control WEHI line carrying empty vector ( EV ) . In contrast , activation of all three caspases was completely blocked in WEHI cells over-expressing host Bcl-2 . Similarly , all three cleaved caspase products were vastly reduced in both WEHI lines expressing vBcl-2 ( M11 . 1 , M11 . 2 ) . As expected , activated caspases were not induced in control A20 mature B cells that express IgG . These results demonstrate that MHV68 vBcl-2 can block BCR-mediated induction of the pro-apoptotic apoptosome/effector caspase pathway in immature B cells . To further confirm these results , we used annexin V staining to test the ability of vBcl-2 to block the induction of apoptosis at a cellular level . In viable cells , phosphatidlyserine ( PS ) localizes to the inner face of the plasma membrane , but in the early stages of apoptosis , PS translocates to the outer face of the membrane . Because annexin V binds to PS , the use of fluorescently-labeled annexin V , in conjunction with a dye to detect membrane permeability , provides a convenient means to detect cells undergoing apoptosis . To determine whether vBcl-2 could block the induction of immature B cell apoptosis following BCR signaling , we cultured WEHI cell lines with or without anti-IgM for 16 hours , and then co-stained with annexin V and the nucleic acid stain SYTOX Blue . Actinomycin D ( ActD ) treatment of WEHI . EV cells was also included as a positive control for induction of apoptosis . ActD inhibits RNA synthesis and is thus a potent inducer of apoptosis via induction of p53 and disruption of mitochondrial membrane potential [62]–[65] . For all cell samples , the percent of cells in early stage apoptosis was quantified by flow cytometric analysis ( Fig . 8A ) . Cells were considered to be in the early stage of apoptosis if they retained an intact membrane ( SYTOX Blue− ) but displayed PS on the cell surface ( annexin V+ ) . As expected , all nonstimulated WEHI cell lines displayed a low background level of apoptosis ( <10% ) , as indicated by negative staining for annexin V ( Fig . 8B ) . In contrast , following IgM stimulation 40% of WEHI cells and 52% of control WEHI . EV cells were annexin V+ and SYTOX Blue− , indicating that they were in the early apoptotic stage . These results were similar to the percent of WEHI . EV cells in early apoptosis following ActD treatment ( 67% ) , demonstrating that BCR stimulation strongly induced cellular apoptosis in both the parental and empty vector control WEHI cell lines . WEHI cells that over-expressed host Bcl-2 were completely protected from BCR-induced apoptosis ( 8% for nontreated , 6% for IgM-treated ) . Similarly , WEHI cells that expressed vBcl-2 were almost completely protected from apoptosis ( 4% and 5% for untreated M11 . 1 and M11 . 2 , 9% for IgM-treated ) . Thus , these data directly demonstrate that MHV68 vBcl-2 can block the induction of BCR-mediated apoptosis in immature B cells . Previous work from our laboratory demonstrated that developing B cells carry latent MVH68 throughout chronic infection , implicating this population as a previously unrecognized reservoir for long-term gammaherpesvirus latency [13] . Work presented here further demonstrates that MHV68 vBcl-2 plays a key role in developing B cell infection and that it can block BCR-mediated apoptosis of immature B cells . Because these cells are short-lived and have a high rate of turnover , these findings cumulatively suggest that MHV68 may actively promote the survival of developing B cells in order to take advantage of the normal homeostatic mechanisms that maintain the mature circulating B cell population . In theory , such a strategy would facilitate the recurrent generation of new latently infected mature B cells and thus serve to maintain lifelong latency in the mature B cell compartment . To determine whether recurrent infection of developing B cells is critical for the maintenance of lifelong MHV68 latency , we undertook experiments to deplete developing B cells at the beginning of , or during , a course of MHV68 infection . Because no cell surface markers are known to be solely expressed on developing B cells , we utilized the in vivo administration of anti-IL-7 antibody as a means to transiently deplete these cells during MHV68 infection . Interleukin-7 ( IL-7 ) is required for B cell development in the mouse , and in the absence of IL-7 developing B cells do not progress past the pro-B cell stage [66] , [67] . In contrast , mature B cells do not require IL-7 for their survival . Thus , transient in vivo antibody neutralization of IL-7 results in a marked reduction of developing B cells , including transitional B cells in the spleen , with little or no effect on mature lymphocyte populations [66] , [68] . We first examined the contribution of developing B cells to the establishment phase of latency in the mature B cell compartment . Previous reports have shown that 14 day intraperitoneal ( i . p . ) administration of the murine IgG2b M25 clone of anti-IL-7 neutralizing antibody is sufficient to significantly deplete developing B cells in vivo [66] . Thus , for initial experiments , naïve B6 mice were injected i . p . with 2 mg of anti-IL-7 every other day for 14 days . Control mice were injected with 2 mg isotype control antibody ( FLAG-M1 IgG2b ) or PBS . To confirm that developing B cells were effectively depleted but that adaptive immune cells remained , splenocytes from control and anti-IL-7-treated mice were analyzed at the end of the depletion period . While the percentage of mature B ( CD19+AA4− ) and mature T ( CD4+ or CD8+ ) cells were remarkably similar across treatment groups , we observed an 84% depletion ( 3 . 8% isotype , 0 . 6% anti-IL-7 ) of the transitional B cell population following two weeks of anti-IL-7 treatment ( Fig . S4 ) . At this time point , the remaining mice in each group were inoculated i . n . with 104 PFU MHV68 . To prevent renewed generation of developing B cells following infection , every other day anti-IL-7 treatments were continued for the final 15 days of the experiment . By 15 days post-inoculation , lytic replication is no longer detectable and latency establishment is at its peak ( Fig . 9A ) . At experiment termination , splenocytes were harvested and pooled from 3 mice per treatment group , and flow cytometric sorting was performed to isolate naïve ( CD19+AA4−IgM+ ) , germinal center ( CD19+AA4−IgM−CD38lo ) , and memory ( CD19+AA4−IgM−CD38hi ) B cells for MHV68 latency analyses . Pooled cell suspensions were simultaneously analyzed to confirm developing B cell depletion . At 15 days post-virus inoculation ( a total of 29 days of antibody administration ) , greater than 91% of splenic transitional B cells were depleted ( Table S1 ) , while mature T cell populations ( CD4+ T cells , CD8+ T cells ) and mature B cell populations ( naïve B cells , germinal center B cells , memory B cells ) remained normal ( Tables S1 and S2 ) . Subsequently , naïve , germinal center , and memory B cell populations were sorted ( Fig . S4 ) and analyzed for the presence of viral genome by limiting dilution nested PCR ( Fig . 10A ) . Despite the nearly complete depletion of developing B cells during early infection , the frequencies of naïve , germinal center and memory B cells harboring viral genome in the anti-IL-7 treatment group were nearly identical to that of mock and isotype control groups ( Fig . 10B ) . Because we did not observe 100% depletion of developing B cells , we cannot preclude with certainty the possibility that a low level of developing B cells is sufficient to impact mature B cell latency . However , the finding that early mature B cell latency was completely unaltered in the absence of greater than 95% of the developing B cell population strongly suggests that developing B cells do not play a significant role in the establishment phase of MHV68 latency . Furthermore , these experiments demonstrate that transient IL-7 depletion does not significantly impact T cell control of MHV68 latency , since it is well-established that loss of T cell effector function results in increased numbers of latently infected cells [52] , [69]–[73] . Previous work from our laboratory and others has demonstrated that the establishment phase of latency is fundamentally different from the maintenance phase of latency with regard to infected cell composition and , presumably , the molecular profile of viral gene expression [6]–[8] . Notably though , MHV68 infection is maintained in a stable frequency of immature and transitional B cells over time [13] , suggesting that infection of these cells may play a key role in facilitating lifelong latency . To determine whether developing B cells contribute to the maintenance phase of latency in mature B cells , we performed IL-7 depletion experiments after the establishment of chronic infection . For these experiments , B6 mice were infected i . n . with 104 PFU of MHV68 , then housed untouched for 28 days , allowing time for the virus to set up stable latency . Beginning on day 28 , anti-IL-7 was administered every other day for 30 days ( Fig . 9A ) . At 58 days post-inoculation , splenocytes were harvested and stained , and flow cytometric analysis and sorting was performed . Following this 30 day depletion regimen , the percentage of transitional B cells was reduced greater than 87% ( 4 . 0% mock and isotype , 0 . 5% anti-IL7 ) , but importantly , the percentages and absolute numbers of mature B cells and T cells were unaffected ( Fig . 9B and Tables S1 , S2 ) . To determine whether developing B cell depletion altered the maintenance of mature B cell latency , we performed limiting dilution nested viral genome PCR on sorted naïve , germinal center and memory B cells from each treatment group ( Fig . 10A ) . As expected , in the control groups the overall frequency of infection in each population dropped significantly from 15 days to 58 days ( Fig . 10B ) , owing to the contraction of the early expansion phase of latency and the establishment of stable long-term infection [7] . Interestingly , short-term depletion of the developing B cell population during the stable maintenance of latency led to a statistically significant decline in the overall frequencies of infection in the naïve and germinal center B cell populations ( 2 . 8-fold for naïve , 4 . 2-fold for germinal center ) and a more subtle decline of infection in the memory B cell population ( 2 . 0-fold ) . These data stand in clear contrast to depletions during the establishment phase of latency , suggesting that the maintenance of long-term latency in mature B cells requires a fundamentally different virological process than early stage infection . These results for the first time provide a clear link between infection of developing B cell populations and latency in the mature B cell compartment .
Host proteins of the Bcl-2 family play a major role in regulating B cell survival , especially during clonal deletion . The pro-apoptotic Bcl-2 family proteins Bak , Bax , and Bim have been shown to mediate the apoptotic death of self-reactive B cells following BCR stimulation with antigen [8] , [13] , [86]–[88] . Conversely , overexpression of anti-apoptotic proteins Bcl-2 or Bcl-XL prevents BCR-mediated cell death [25] , [32]–[34] , [55] . Thus , our observations that the MHV68 vBcl-2 mutants displayed a significant defect in immature and transitional B cell infection are consistent with the conclusion that vBcl-2 plays an anti-apoptotic role similar to host Bcl-2 in these cell populations . This conclusion is further supported by our complementation experiments in NZB mice , which showed that increased expression of host Bcl-2 in developing B cells completely negated the attenuated phenotype of the vBcl-2 BH2 mutant virus in these cells . Finally , our experiments using WEHI-231 B cells directly demonstrated for the first time that vBcl-2 could block the apoptosis of immature B cells that were stimulated through the BCR . Thus , we speculate that the decline in frequency of genome positive immature and transitional B cells that occurs in the absence of vBcl-2 expression is due to a decrease in the number of infected cells surviving clonal deletion . It is noteworthy that our findings do not rule out a role for the anti-autophagy function of vBcl-2 in developing B cells . Indeed , our experiments with the vBcl-2 α1 mutant strongly suggest that MHV68 vBcl-2 blockade of autophagy also plays a critical role in infection of developing B cells . This is consistent with previous reports demonstrating that autophagy of WEHI-231 cells and primary splenic B cells is induced by BCR stimulation [89] , and that the autophagy pathway may serve as a backup mechanism for cell death when apoptosis is blocked [90] . A natural extension of this conclusion is that autophagy plays a key and underappreciated role in B cell selection . Thus blocking both apoptosis and autophagy may be requisite for survival of cells that are otherwise destined for clonal deletion . Our previous demonstration that immature and transitional B cells carry viral genome throughout chronic infection [13] strongly supported a key role for developing B cells during lifelong latency , but did not address whether a linkage exists between developing B cell infection and the peripheral mature B cell latency reservoir . Does infection of developing B cells directly contribute to the dynamic maintenance of latency in circulating mature B cells ? Or instead is it an autonomous event , unrelated to peripheral B cell infection ? In work presented here , we gained insight into this question by depleting developing B cells in vivo then assessing the extent of latent infection in mature B cell subpopulations . Interestingly , developing B cell depletion from 28 to 58 dpi resulted in a pronounced and statistically significant decrease in naïve and germinal center B cell infection , demonstrating that developing B cells are required for the maintenance of peripheral mature B cell latency . Depleted mice also demonstrated a highly reproducible , but smaller decrease in the frequency of infected memory B cells , likely owing to the relative longevity of memory B cells [91]–[94] . Importantly , these results provide the first clear demonstration of a potential direct link between the infection of developing B cells and stability of the major latency reservoir of circulating mature B cells , and strongly suggest that the maintenance of lifelong latency is a dynamic process that involves constant reseeding of the mature B cell reservoir . Interestingly , depletion of developing B cells prior to and during the first 16 days of infection had no effect on latency in any of the mature B cell subpopulations . These results demonstrate that developing B cells do not contribute to the early establishment of latency in the mature B cell compartment . This finding is notable because it strongly implies that different virological mechanisms operate in vivo during establishment versus maintenance of latency . Consistent with this conclusion , the frequency of latent MHV68 infection peaks at 16–20 dpi during the “expansion phase” of latency , then gradually decreases until it reaches a stable level at 42–49 dpi [52] , [53] , [95] , [96] . Similarly , the percentage of latently infected cells that reactivate ex vivo is highest at 16 dpi and decreases over time [52] , [53] . In light of our results , it is reasonable to speculate that this transition from an active form of latency to a more quiescent form of latency may reflect a conversion from a majority of mature B cells that were directly infected by free virus during acute replication to mature B cells that arose from differentiation of infected developing B cells . Notably , Thorley-Lawson and colleagues have proposed an analogous concept for EBV , wherein direct infection of memory B cells during acute EBV results in an active latency growth program and subsequent cytotoxic T cell targeting , whereas virus-driven maturation of naïve B cells sets up a quiescent latency program that facilitates life-long infection [4] . While further experiments will be required to unravel these complexities , our results clearly indicate that the stable maintenance of long-term latency is a dynamic process that is distinct from early latency and requires an ongoing contribution from developing B cells . To date , it is unclear whether human gammaherpesviruses infect developing B cell populations as part of their natural life cycle in healthy individuals . However , both EBV and KSHV genomes have been detected in the bone marrow and progenitor cells of humans in the context of disease . For example , EBV has been detected in the bone marrow of patients with EBV-associated hemophagocytic lymphohistiocytosis ( EBV-HLH ) [77] , [78] and both EBV and KSHV have been detected in the bone marrow of AIDS patients [74] , [75] . Further , EBV-associated lymphoproliferative disease following allogeneic bone marrow hematopoietic stem cell ( HSC ) transplantation is almost always of donor origin [82] , [97] , [98] . Consistent with the possibility of a progenitor cell source of gammaherpesvirus infection , KSHV has been detected in circulating human CD34+ hematopoietic progenitor cells ( HPCs ) of KS patients [99] and in morphologically immature cells in the bone marrow of transplant recipients [76] . Additionally , several reports have demonstrated the presence of EBV+ B cells , presumed to be of progenitor cell origin , arising from long-term human bone marrow cultures of healthy donors [100] , [101] and hematologic patients [102] . Cumulatively , these reports provide substantial support for the concept that the human gammaherpesviruses can infect developing B cells in the bone marrow or in circulation . Nevertheless , a great deal of additional work will be required to comprehensively define the role of precursor B cells during a normal course of EBV or KSHV infection . It is also noteworthy that several recent reports have correlated high numbers of circulating transitional B cells with high EBV loads in patients at risk for the development of EBV-associated B cell lymphomas . For example , it is now widely recognized that EBV and malaria co-infection correlate with a high incidence of endemic Burkitt's B cell lymphoma in African children [103] , [104] . Although the synergistic interplay of these two pathogens during oncogenesis is poorly understood , a recent report demonstrated that infants from a malaria-endemic region of Kenya display normal levels of naïve ( IgD+CD27− ) and classical memory ( IgD−CD27+ ) B cells , reduced numbers of non-class switched memory ( IgD+CD27+ ) B cells , but expanded numbers of immature transitional ( CD10+CD34− ) B cells [105] . Interestingly , this population of children also exhibits increased EBV loads in accordance with earlier ages of infection [106] . Likewise , patients with chronic HIV infections frequently display increased EBV loads [107] and are at high risk for the development of EBV-associated B cell lymphoma , and a recent study linked high EBV loads in chronic HIV patients with an increased frequency of circulating immature or transitional B cells [108] . At minimum , these studies provide correlative evidence of a link between high numbers of developing B cells and enhanced EBV infection , and may suggest that transitional B cells serve as a conventional EBV reservoir that greatly expands during particular types of immune dysfunction . Our finding that vBcl-2 promotes the survival of immature and transitional B cells during MHV68 infection may provide an important clue to the long-speculated potential link between gammaherpesvirus infections and autoimmune disease . For example , numerous groups have published reports providing circumstantial evidence of a causal relationship between EBV infection and the development of , among others , multiple sclerosis and systemic lupus erythematosus ( reviewed in [109] , [110] ) . Nevertheless , this relationship has been seriously questioned due to the incongruous ubiquity of EBV with the relatively rarity of autoimmune diseases . However , on a teleological basis it is reasonable to speculate that if indeed gammaherpesviruses promote survival and maturation of B cells with autoreactive BCRs , then these viruses would also have a means to prevent autoreactive BCRs from signaling as a means to simultaneously protect the host and facilitate long-term latency . Thus , as with gammaherpesvirus-associated tumors , the development of autoimmune disease may represent an anomalous consequence of gammaherpesvirus infection , likely resulting from synergism with disease-promoting secondary factors such as host genetics or pathogen co-infection . In support of the multifactorial nature of any potential link between gammaherpesviruses and autoimmune disease , several conflicting reports have indicated that MHV68 both suppresses [57] , [111] , [112] and exacerbates [113] , [114] murine autoimmune diseases . In light of our demonstration that MHV68 ( a ) blocks BCR-mediated apoptosis of immature B cells and ( b ) promotes the survival of developing B cell subpopulations that are known to undergo autoreactive BCR-mediated clonal deletion , a potential link between gammaherpesvirus infection and the survival of B cells with autoreactive BCRs warrants further exploration . The work presented here represents a substantial step forward in the understanding of the in vivo role of a gammaherpesvirus-encoded Bcl-2 ortholog . The finding that viruses deficient in vBcl-2 function were most significantly attenuated in those developing B cell populations that are required to surmount tolerance selection checkpoints strongly suggests that the virus alters normal B cell development outcomes as a means to promote long-term survival . Consistent with this conclusion , in vivo depletion of developing B cells during long-term latency resulted in reduced infection in mature B cells , supporting the possibility of a direct link between precursor B cell infection and the stability of lifelong latency in circulating mature B cells . A great deal of further work will be required to determine whether a normal course of gammaherpesvirus infection promotes the simultaneous survival and inactivation of autoreactive B cells , and whether in rare scenarios co-factors can play the role of key intermediary between gammaherpesvirus infection of developing B cells and development of autoimmune disease .
Wild-type C57Bl/6J or NZB mice age 7–10 weeks purchased from Jackson Laboratory ( Bar Harbor , Main ) were used for experiments presented here . Mice were housed at University of Florida in accordance with all federal and university guidelines . Mice were anesthetized with isofluorane and infected intranasally ( i . n . ) with 104 PFU of virus in 30 µl serum-free DMEM . MHV68 strain WUMS ( ATCC VR1465 ) , MHV68 . vBcl2stop [50] , MHV68 . vBcl2ΔBH [49] , and MHV68 . vBcl2Δα1 [49] were used for inoculations . At indicated time points mice were sacrificed by exposure to inhalation anesthetic . All animal experiments were performed in strict accordance with Federal and University guidelines . Specifically , we adhered to the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health and the American Veterinary Medical Association Guidelines on Euthanasia . The animal protocol was approved by the Institutional Animal Care and Use Committee at the University of Florida ( study number 201105767 ) . To obtain splenocyte and bone marrow cell suspensions , spleens , femurs , and tibias were harvested and single cell suspensions were prepared by homogenizing spleens and flushing each bone with 5 mls of DMEM . For spleen samples red blood cell lysis ( 144 mM NH4Cl and 17 mM Tris , pH 7 . 2 ) was carried out for 5 minutes at 37°C prior to staining . Harvested cells were then suspended in blocking buffer ( PBS , 5% bovine serum albumin , 10% normal rat serum , and purified anti-mouse CD16/CD32 [Fc block; clone 2 . 4G2; BD Biosciences] ) for 30 minutes on ice prior to staining with antibodies . Limiting-dilution assays to determine the frequency of transitional and mature B cells reactivating from latency or containing performed infectious virus were performed as previously described [13] , [52] , [88] . Briefly , transitional and mature B cell populations were serially diluted two-fold and plated onto MEF monolayers in 96-well plates . Twelve dilutions were plated per sample , and 24 wells were plated per dilution . Wells were microscopically scored for cytopathic effect ( CPE ) following a three week incubation period . To detect preformed infectious virus , parallel samples of mechanically disrupted cells were plated onto MEF monolayers . This process kills >99% of live cells , while leaving preformed infection virus intact . Data points are the average of two or three independent experiments , each consisting of pooled spleens from three mice , and are presented as the percentage of wells per dilution that scored positive for viral CPE+/− standard error . LDPCR was used to determine the frequencies of cells positive for MHV68 genome , as previously described [13] , [52] , [115] . Briefly , cell samples were serially diluted threefold in a background of uninfected RAW 264 . 7 murine macrophages . A total of 1×104 or 5×104 cells were plated in a 96-well PCR plate at 12 wells per dilution . 10 , 1 , or 0 . 1 copies of a MHV68 ORF72 plasmid in a background of RAW 264 . 7 cells , and RAW 264 . 7 cells only were included on all plates for controls . Cells were lysed with proteinase K at 56°C for 8 hours . Two rounds of nested PCR were then performed using primers specific for MHV68 ORF72 , and 195 bp bands resolved using a 3% agarose gel . Unless otherwise indicated , data points are the average of three to five independent experiments , each consisting of pooled spleens from three to five wild-type C57Bl/6 mice . Data are presented as the mean percentage of wells per dilution that were positive for viral genome +/− standard error . On graphs , the dashed line at 63 . 2% indicates the point at which one viral genome-positive cell per reaction is predicted to occur . The x axis shows the numbers of cells per reaction; the y axis shows the percentages of 12 reactions positive for viral genome . B cell lines WEHI-231 , WEHI empty vector , WEHI Bcl-2 , WEHI M11 . 1 , WEHI M11 . 2 , and A20 were maintained in RPMI-1640 containing 10% fetal bovine serum ( FBS ) , 100 U/mL penicillin , 100 mg/mL streptomycin , and 0 . 05 mM 2-mercaptoethanol with 10% CO2 , at 37°C . 0 . 025 µg/mL puromycin was added to culture media of WEHI-231 cell lines carrying Murine Stem Cell Virus ( MSCV ) vectors in order to maintain selection . The MSCV retro viral vector packaging cell line BOSC23 was cultured in complete Dulbecco's modified Eagle's medium ( DMEM ) supplanted with 10% FCS , 100 U/mL penicillin , and 100 mg/mL streptomycin and incubated at 5% CO2 , 37°C . vBcl-2 and host Bcl-2 were cloned into murine stem cell virus ( MSCV ) retroviral vectors ( Clontech ) . To detect M11 expression , a hemagglutinin ( HA ) epitope tag was added to the C-terminus of M11 . The MSCV Retroviral Expression System ( Clontech ) was used to generate WEHI empty vector ( WEHI . EV ) , WEHI M11 ( WEHI . M11 . 1 and WEHI . M11 . 2 ) , and WEHI Bcl-2 ( WEHI . Bcl2 ) cell lines according to the manufacturer's protocols . Briefly , retroviral stocks were generated by transfecting BOSC23 packaging cells with 8 µg DNA ( pMSCV M11 , pMSCV bcl-2 , or pMSCV empty vector ) using Lipofectamine2000 ( Invitrogen ) . Viral supernatants were collected at 48 hours and 72 hours post-transfection and filtered through a 0 . 45 µm nylon filter . The viral supernatants were treated with 6 µg/mL polybrene and were then added to WEHI-231 cells seeded in 60 mm dishes at 1×106 cells per dish . Twenty four hours post-infection 0 . 025 µg/mL puromycin was added to cultures and selection was carried out continuously . Western Blots and immunofluorescence microscopy , as described below , were used to confirm expression of HA ( M11 ) and Bcl-2 . For immunofluorescence assays , 1×105 WEHI cells were washed with PBS and incubated with MitoTacker Red for 30 min at 37°C . Following incubation , cells were washed twice with PBS . Cells were then fixed with ice cold MeOH for 15 min at −20°C , then pelleted and resuspended in 300 µl PBS . The cell suspension was then fixed to microscope slides via cytocentrifugation using a Cytopro cytospin at 400 RPM for 5 min at room temperature . Next , cells were blocked with 5% normal goat serum ( NGS ) for 1 hour at room temperature to prevent non-specific antibody binding , then incubated with the primary antibodies rabbit anti-BCL-2 , rabbit anti-HA or the IgG isotype control in 2% NGS in PBS overnight . Cells were washed three times with PBS and then incubated with secondary antibody Alexa Fluor 488 goat anti-rabbit IgG ( Molecular Probes , Inc . ) for 1 hour at room temperature , then washed and then treated with DAPI . Images were captured with Leica software using a Leica laser confocal microscope ( TCS SP2 ABOS laser scanning spectral confocal ) with 63× objective at 4 times zoom . Cell lysates were prepared using a 1∶1 ratio of PBS and Laemmli buffer with 2-mercaptoethanol and heating for 5 minutes in a boiling water bath . Total protein per µL of sample was quantitated using Thermo Scientific NanoDrop 2000 . Equal amounts of total cellular protein from each sample were separated using SDS-PAGE on 15% acrylamide gels , followed by immunoblotting . Membranes were blocked in a 10% milk–TBS–Tween 20 solution , followed by incubation with primary antibody ( anti-HA-tag [Cell Signaling Technology] , anti-Bcl-2 [Cell Signaling Technology] , rabbit anti-caspase-3 , -6 , or -9 [Cell Signaling Technology] , or anti-actin clone c4 [Millipore] ) . Blots were then incubated with goat anti-mouse IgG HRP ( Millipore ) or goat anti-rabbit IgG HRP ( Abcam ) . Antibody-labeled protein bands were detected using Western Lightning Plus-ECL Enhanced Chemiluminescence Substrate ( Perkin Elmer ) . Densitometry was performed using Bio-Rad Gel Doc XR system using Quantity One 4 . 6 . 9 software ( Bio-Rad ) . For flow cytometric annexin V assays , WEHI cell lines and A20 cells were plated at 2 . 5×105 cells/mL with 2 mL total volume in 6 well plates . Cells were incubated for 16 hours in the absence or presence of 20 µg/ml goat anti-mouse IgM , μ chain specific ( Jackson ImmunoResearch Laboratories ) or 40 nM Actinomycin D ( Sigma ) . Following a 16 hour incubation , cells were washed in cold PBS and resuspended in 100 µl binding buffer , then incubated on ice for 15 minutes with 10 µl of Annexin V-FITC ( BD Biosciences ) . Following Annexin V staining , cells were washed and resuspended in 400 µl binding buffer and 0 . 5 µl SYTOX Blue ( Life Technologies ) . Cells were incubated an additional 5 minutes at room temperature before analysis on a LSR II ( Becton Dickinson ) flow cytometer . Data were analyzed using FACS Diva software ( Becton Dickinson ) . FACS data were analyzed using FACSDiva ( BD Biosciences ) and FloJo . All other data were analyzed using GraphPad Prism software ( GraphPad Software , San Diego , CA ) . The frequencies of cells positive for viral genome , reactivating ex vivo , and containing preformed virus were determined from the nonlinear regression analysis of sigmoidal dose response best-fit curve data . Based on Poisson distributions , the frequency at which at least one event in a given population is present occurs at the point where the regression analysis line intersects 63 . 2% . Calculation of statistical significance was determined by Student's t test of paired cell dilution results .
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Gammaherpesviruses such as Epstein-Barr virus and Kaposi's sarcoma herpesvirus are widespread pathogens that establish lifelong infections in a dormant state termed latency . Although most gammaherpesvirus infections are asymptomatic , infection of some individuals leads to the development of B cell lymphoma or other cancers . It is well known that during latency these viruses reside in mature B cells of the immune system; however , little is known about how this reservoir is maintained for life . Using murine gammaherpesvirus 68 infection of mice as a model to study gammaherpesvirus infections inside a living host , we have previously demonstrated that gammaherpesviruses can infect early precursors of B cells . In normal situations , the differentiation of such precursors into mature B cells is a tightly regulated process that leads to the death of cells that react inappropriately to host tissues . Here though , we demonstrate that a gammaherpesvirus protein called vBcl-2 can block the death of infected precursor B cells , and that vBcl-2 is critical for infection of these cells . Finally , we show that depleting precursor B cells reduces mature B cell latency . Together , these data suggest that vBcl-2 proteins play a key role in lifelong gammaherpesvirus latency and may be a potent target for future drug development .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"immune",
"cells",
"viruses",
"and",
"cancer",
"immunology",
"host-pathogen",
"interaction",
"microbiology",
"lymphoid",
"organs",
"epstein-barr",
"virus",
"infectious",
"mononucleosis",
"animal",
"models",
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"infection",
"infectious",
"diseases",
"biology",
"immune",
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"cells",
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"persistence",
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"bone",
"marrow",
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"viral",
"diseases",
"autoimmunity"
] |
2014
|
A Gammaherpesvirus Bcl-2 Ortholog Blocks B Cell Receptor-Mediated Apoptosis and Promotes the Survival of Developing B Cells In Vivo
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Cryo-electron microscopy permits 3-D structures of viral pathogens to be determined in remarkable detail . In particular , the protein containers encapsulating viral genomes have been determined to high resolution using symmetry averaging techniques that exploit the icosahedral architecture seen in many viruses . By contrast , structure determination of asymmetric components remains a challenge , and novel analysis methods are required to reveal such features and characterize their functional roles during infection . Motivated by the important , cooperative roles of viral genomes in the assembly of single-stranded RNA viruses , we have developed a new analysis method that reveals the asymmetric structural organization of viral genomes in proximity to the capsid in such viruses . The method uses geometric constraints on genome organization , formulated based on knowledge of icosahedrally-averaged reconstructions and the roles of the RNA-capsid protein contacts , to analyse cryo-electron tomographic data . We apply this method to the low-resolution tomographic data of a model virus and infer the unique asymmetric organization of its genome in contact with the protein shell of the capsid . This opens unprecedented opportunities to analyse viral genomes , revealing conserved structural features and mechanisms that can be targeted in antiviral drug design .
Viruses are remarkable examples of symmetry and self-assembly at the nanoscale . The protein containers that encapsulate most viral genomes are formed from just a few different protein building blocks that self-assemble into particles with icosahedral symmetry , and can be described in terms of icosahedral surface lattices [1] . This geometry minimizes the amount of the genome fragment needed to code for the viral capsid , while maximizing its volume/surface area ratio; the principle of genetic economy [2] . Symmetry therefore plays a pivotal role in understanding virus structure . Symmetry averaging techniques have been used to determine viral capsid structures at atomic resolution by X-ray crystallography , and by reconstruction of such structures at medium resolution by cryo-electron microscopy ( cryo-EM ) . However , not all viral components are organized with icosahedral symmetry . Cryo-EM can be used to refine such asymmetric structures provided that they are large enough in mass terms to contribute significantly to the image [3 , 4] . However , asymmetric viral components normally contribute too weakly to the images obtained by cryo-EM to allow the refinement of an asymmetric model [5] . Note , in crystals of viral particles , the asymmetric features of the individual viruses usually do not dictate crystal packing contacts , and are therefore averaged out by the lattice . The important functional roles of such viral components in the viral life cycle are therefore difficult to characterize . An example is the single-copy of maturation protein ( MP , also called A-protein ) in bacteriophage MS2 that is hypothesized to replace a protein dimer in the capsid [6] . It attaches to the bacterial receptor during the infection to facilitate genome extraction . The asymmetric organization of the viral genome inside a capsid is also difficult to reconstruct . Indeed , MS2 is typical in that the high resolution crystal structure lacks density for the ∼3 . 7kb genome [7 , 8] , but cryo-EM reconstructions from both our group and others show extensive density for the RNA [6 , 9–12] . This difference arises because of technical aspects of the ways the EM and X-ray data are collected . We demonstrate here that a better understanding of the asymmetric organization of the viral genome within the capsid can be achieved if specifics about the contacts between capsid protein ( CP ) and the packaged genome are factored into an analysis of tomographic data . Recently we have shown that a number of positive-sense single-stranded ( ss ) RNA viruses encode dispersed , degenerate sequence/structure elements within their genomes that bind their cognate coat proteins specifically during assembly , facilitating capsid assembly efficiency [13–17] . These packaging signals ( PSs ) can have dramatic effects on the kinetics and fidelity of virion assembly [18] . There are widespread contacts between genomic RNA and capsid protein in picornaviruses , e . g . rhinovirus [19] , and preliminary in vivo experiments for human parechovirus 1 suggest that they function as PSs ( ongoing work with collaborators ) . The requirement for the PSs to contact the coat proteins of the viral capsid at specific positions in the capsid imposes a constraint on the conformation of the genome within each viral particle , that we are exploiting here to analyse tomograms of the packaged genomes . In particular , we exploit knowledge of the PS positions with reference to the icosahedrally-averaged RNA cages that have been observed in a large number of viruses in proximity to capsid , to formulate constraints on the connections between the PSs . For example , if PSs are located at the vertices of these cages , as in the model system we are considering here , then the RNA organization in proximity to capsid can be modelled as connected paths along the edges of the RNA cage [15 , 20] . If the majority of the potential binding sites are occupied by a PS in every particle , as is expected , for example , if such contacts are vital in triggering a conformational change in the protein building block with which they are in complex , then this path has the mathematical properties of a Hamiltonian path . In this paper , we will discuss explicitly an example for which the constraint set is given by Hamiltonian paths . However , a similar approach can be adopted also for other viruses that violate some of the assumptions relating to our model system . For example , if PSs are stem-loops positioned along the edges of the polyhedral RNA cage , such as in Satellite Tobacco Mosaic Virus ( STMV ) [21] , then constraints have to be formulated in terms of paths that permit edges to be transversed twice in opposite directions . The library of all possible paths with that property would then replace the library of Hamiltonian paths we are using for our model system here . Moreover , it is possible that only a fraction of the potential binding sites are occupied by PSs . For example , this might happen if PSs facilitate CP-CP interactions rather than CP quasi-conformer switching , as is the case for STNV [16 , 22] . In this case , the constraint set corresponds to all paths on the polyhedral cage that connect subsets of the potential binding sites corresponding to the number of the PSs: these are therefore also not Hamiltonian paths . The overall strategy , however , would remain the same: deducing information from tomographic data using an appropriate constraint set formulated in terms of paths that encode information on the specifics of the RNA-CP contacts ( PSs ) and their positions relative to the ordered genome segments in the averaged structures . Our previous modelling and the symmetry averaged structures of a large number of viruses from different families are consistent with the concept of such ordered genome segments in many viruses , including Picornaviridae [23] , Leviviridae [9 , 11] , Nodaviridae [24] , Bromoviridae [25 , 26] , Tymoviridae [27] , Comoviridae [28] and satellite viruses [29–31] . Importantly , this asymmetric distribution of viral genomes within a virion may also be an essential factor in the extrusion/uncoating of these genomes as the first step in subsequent infection [6 , 32–37] . The analysis presented here provides a novel way of deriving information on such asymmetric genome organizations , thus contributing to the understanding of such events . Revealing RNA-protein contacts in molecular detail is a recent and novel challenge to our understanding of basic virus biology . In pursuit of this goal we recently used the association of MS2 phage particles to its natural receptor , a bacterial pilus , to create highly asymmetric complexes that could be subjected to asymmetric structure determination . This led to completion of a reconstruction using reduced ( five-fold vs . icosahedral ) symmetry averaging [12] and subsequently to a tomographic reconstruction of the whole virion using alignment and averaging of thousands of single particle tomograms [6] . The former result confirmed the presence of extensive RNA density , and the latter revealed its asymmetric structure; a first for any ssRNA virus . This suggests that the MP occupies a two-fold position in the otherwise icosahedral coat protein lattice , presumably replacing the normal CP dimer at that site . Unfortunately , the resolution of the asymmetric tomographic reconstruction is very low ( 39Å ) and the molecular details are still unclear . It is therefore important to develop new analysis techniques that are able to reveal such genome organizations based on a range of data from different techniques , including the low resolution information contained in tomographic data . We introduce here a new method that uses information from icosahedrally-averaged maps , as well as knowledge of the contact sites between genomic RNA and CP to analyse the low resolution , tomographic density maps via a constraint optimization technique revealing the putative asymmetric genome organization of bacteriophage MS2 . As we describe in detail here , the constraint set for the analysis of MS2 is derived from circular Hamiltonian paths connecting the PS contact sites , and similar constraints are likely to apply also to other Leviviridae [9] . For other viruses , in which occupation of the majority of the PS binding sites is likely due to their function in assembly , and for which the PSs are positioned at the vertices of the RNA cage corresponding to the icosahedrally-averaged map of the genome in proximity to capsid , the constraint set is also given by Hamiltonian paths . However , the set of Hamiltonian paths would be distinct from the one used for our model system if the numbers of binding sites and the connectivity between them differ . We are providing detailed instructions on how to modify our code ( freely available at http://hprna . github . io/ ) to accommodate such alterations . If there is evidence that the 5′ and 3′ ends are in proximity in the packaged genome as in our model system , then the set of constraints can be reduced to only the circular Hamiltonian paths; otherwise , the full set of Hamiltonian paths has to be taken into account . Our code includes a setting that allows switching between these options , to compute either circular or non-circular Hamiltonian path constraint sets as required . Note that this method also applies if some of the potential binding sites remain unoccupied in random positions across the ensemble of particles used to generate the tomographic data , as such random mistakes would not be reinforced during averaging over different particles: hence it is sufficient that the majority of PS binding sites are occupied . Note that in the case of insufficient information being available to decide a priori between multiple constraint sets ( stemming from different assumptions on the specifics of the PS-mediated assembly scenario ) , the tomogram could also be interrogated against the different possible options . This could give an indication , perhaps in combination with additional experimental insights , as to which of the proposed mechanisms is most likely to occur . The main purpose of this paper is to demonstrate that the method of using constraint sets , inspired by insights into the roles of PSs , can indeed result in a better understanding of tomographic data , and perhaps even reveal the asymmetric organization of the packaged genome , as in the example discussed here . In order to demonstrate this for a model system , the specifics of that system must be built into the formulation of the constraint set . However , as we argue above , the method of interrogating tomographic data via constraint sets inspired by PS-mediated assembly mechanisms is more generally applicable to wider classes of viruses .
We illustrate this procedure here for the model system bacteriophage MS2 . MS2 has a quasi-equivalent T = 3 capsid formed from 89 non-covalent CP dimers , comprising 29 symmetric ones ( C/C ) located at the particle two-fold axes , and 60 asymmetric ones ( A/B ) organized in groups of five around the capsid five-fold axes , and one MP that replaces a C/C dimer , see Fig . 1A . RNA PSs in the genome have been shown to act as allosteric regulators of the CP-dimer conformation , PS binding favouring formation of the A/B dimer [38 , 39] . Thus , in an ideal case , we would expect to find 60 PSs within the genome . PSs are highly degenerate in nucleotide sequence . We have identified all the PSs in both MS2 and the related phage GA via a new analysis method based on biochemical RNA-CP binding and SELEX data [15] . In the icosahedrally-averaged MS2 cryo-EM map [11] the ∼3 . 7 kb long RNA genome appears inside the capsid as two concentric shells with density connections at the particle five-fold axes . This arrangement reflects the contacts that the genomic RNA makes between PSs and the CP layer , which appear as the outer shell , whilst the inner shell is the consequence of RNA segments that do not bind to CPs but extend into the interior of the capsid . The start and end points of these segments are located at the same five-fold vertex in the capsid [11] . Therefore , every PS is connected to two other PSs in the outer RNA shell , and hence the RNA in the outer shell , i . e . disregarding fragments extended into the interior , forms a connected path . If the path were disconnected , PSs at different five-fold vertices would have to be connected directly via RNA in the capsid interior , which is not consistent with the cryo-EM analysis in Toropova et al . [11] . The averaged outer shell density ( Fig . 1A ) is in the form of a polyhedral cage ( Fig . 1B ) , positioned such that its vertices are in contact with the 60 asymmetric dimers ( see yellow circles in the contact map in Fig . 1D ) . The RNA outer shell is intimately associated with the inside surface of the CP shell , as is also seen in the asymmetric reconstruction ( Fig . 1C ) . The positions of the PSs in the genome determined earlier [15] suggest that the connections between PSs are single-stranded . The connected path described by the RNA in the outer shell is therefore a Hamiltonian path on that polyhedral RNA shell , i . e . a path that meets all vertices ( aka PS positions ) . In particular , we determined all possible ways in which the RNA can be positioned in the icosahedrally-averaged density of the outer shell by computing all possible Hamiltonian paths on the polyhedron in Fig . 1B . Note that for viruses with different polyhedral RNA organizations the same method can be applied by computation of the Hamiltonian paths on the corresponding polyhedral density . Moreover , since Hamiltonian path computations only depend on the topology of the polyhedron , i . e . the network of connections between vertices irrespective of the lengths and orientations of the edges , the same library of Hamiltonian paths can be used for wider classes of viruses , such as those studied by van den Worm et al . [9] or bacteriophage GA [15] . In the case of bacteriophage MS2 , additional biochemical information showed that regions close to the 5′ and 3′ ends of the genomic RNA were bound to the MP [40] , which was positioned adjacent to one of the particle five-fold axes , replacing one of the CP dimers on a two-fold axis in the protein shell . This circularization reduces the number of possible Hamiltonian paths for the RNA . In particular , filtering out all those Hamiltonian paths with end points at the same five-fold axis , reduced the number to only 66 [20] . Since abstract paths have no directionality to them , each could potentially be realized by the RNA in two different ways by interchanging the positions of 5′ and 3′ ends , resulting in 132 path solutions . Since the resolution of the averaged tomogram , obtained via alignment and averaging of individual tomograms , was not sufficient to unambiguously identify the location of the MP , and the binding sites of the RNA were difficult to identify , we bookmarked all paths which started and finished within the eight five-fold axes closest to MP . This was a very conservative overestimate , which ensured that no possible path was missed in our analysis . Each of these ( Hamiltonian ) paths could potentially start at any of the five-fold vertices . In total , we therefore obtained a library of 8*5*132 = 5280 possible paths for the genomic RNA in the outer RNA shell . As mentioned above , this library can be applied to a wide range of RNA viruses , covering all those with a polyhedral RNA organization topologically equivalent to that of MS2 . The polyhedron describing the averaged density was given in terms of two types of edges ( cf . Fig . 1B&D ) , 60 short and 30 long ones , and it had 60 vertices ( cf . yellow circles in Fig . 1D ) . Each path in the library was therefore given as a sequence of 60 edges on the polyhedral shell , which were a mixture of short and long edges depending on the path . Each path provided information on which edges are simultaneously occupied or unoccupied , and hence correlated occupancy information on different edges . The library of putative path organizations was used as a set of constraints in the analysis of the asymmetric electron density for the outer RNA shell , which we isolated from the tomogram as described in Methods . Note that any path in the library provided information on which edges were likely to be occupied , given that occupation of some of the edges—or the lack thereof—could be confirmed based on the tomogram . The first step was therefore to determine a subset of the 90 edges of the averaged map ( with reference to the polyhedron in Fig . 1B ) that were likely occupied or unoccupied given the density distribution of the tomogram . We excluded all short edges as they were too short to distinguish unambiguously whether density represented the RNA-CP contact ( i . e . PS ) positioned at the vertex , or a connection between two PSs along a short edge . We moreover disregarded the five long edges ( see S1 Fig ) around the MP , as it was not possible to ascertain whether density in these regions arose from the MP , genomic RNA , or a combination of both . As discussed in Methods , we attributed tomographic density to each of the 25 long edges of the polyhedral cage representing the icosahedrally-averaged density considered in this analysis and fitted it to a normal distribution . A ranking of the level of density associated with these edges was achieved using the mean of the fitted normal distribution . This method was used because outliers in the noisy , sparse dataset had less influence on the mean of the fitted distribution than they did with a simple arithmetic mean . Using the fitted mean , four connections stood apart from the others , with mean densities of 2 . 6–2 . 9 , see Fig . 2 , suggesting that these four edge connections were likely occupied by RNA in the virion . These were denoted as “occupied” connections , and were used as constraints in the analysis of the asymmetric structure . To determine which connections could be classed “unoccupied” , we used the skew parameter of the sampled distributions to examine smearing of density . Skewness characterizes the balance of a distribution to either side of the peak density . As expected , the group of connections classed “occupied” above had a skew between 0 . 1–0 . 3 . Negatively skewed connections were disregarded from the analysis , because a negative skew meant that there were only a very limited number of high-density points , which made up the cumulative density . Because of their low copy numbers , small fluctuations in sampling made a big difference to the overall density , and we therefore did not want to make a judgement of occupancy based upon these data . Using the skew parameter , the remaining data were therefore separated into distinct groups . The five data points shown in the red circle in Fig . 2 , with mean values between 1 . 5–1 . 8 , were adjudged “non-occupied” , i . e . characterized by an absence of density corresponding to RNA . There were thus nine constraints on RNA organization that were used to compare the asymmetric structure with the library of all possible Hamiltonian path organizations: four long edges were deemed occupied , and five non-occupied . Only five members of the library of all possible Hamiltonian paths were consistent with these nine constraints . In Fig . 3 we display the occupation of long edges with reference to the two five-fold vertices they connect , following the numbering scheme of vertices given in Fig . 1D . Note that the paths match for 13 of the 30 long edges , suggesting that the structure common to all paths is likely to be a prevalent feature in different viral particles . Each path was a roadmap of connectivity between RNA-CP contacts . In order to decide if any of these putative RNA organizations was more likely to occur than another , we used the following criterion: We associated with each option a density distribution by ascribing density to occupied edges in proportion to their lengths and computed the density obtained by averaging around the five-fold axis adjacent to MP . We used this as a characteristic to benchmark against the five-fold averaged density determined experimentally [12] ( Fig . 4H , adapted from [20] ) . Path 4 ( Fig . 5A ) closely matched ( Fig . 4F ) this distribution , whereas the other paths did not . This strongly suggested that Path 4 was indeed the correct model for the organization of the RNA in MS2 . Remarkably , Path 4 is also consistent with results of two independent studies: the assembly pathways determined via kinetic modelling of capsid self-assembly [20] , and the PS positions identified via a bioinformatics analysis of RNA SELEX data [15] . Our analysis here represents a completely independent reconfirmation that the organization of the viral genome in proximity to capsid is highly constrained and likely identical in every viral particle .
The analysis method introduced here has for the first time identified the conformational path taken by a viral genome in proximity to its capsid from the low-resolution density map of an asymmetric , averaged tomogram . Previously , a model of the asymmetric genome organization in the plant satellite virus STMV has been built [41] . That work relied on the icosahedrally-averaged crystal structure which revealed ∼70% of the viral genome to be in contact with the protein shell via a series of dsRNA segments ∼9 bp long [30 , 42 , 43] . The X-ray structure provided the first definition of RNA PSs [21] . In addition to the X-ray density the modelling used predictions of the most likely secondary structure elements within the genome to identify the sequences forming the double-stranded segments [44] . Ours is the first direct analysis of an asymmetric map containing RNA density . The method introduced here can be used to analyse any asymmetric dataset of a viral genome organization , provided that a distinct shell of density is seen in proximity to capsid in the averaged cryo-EM density , the contact sites between genomic RNA and capsid protein are known , and information regarding their positions and function can be used to formulate a constraint set on the connectivity between the PSs . Insights into PSs are becoming available for a number of ssRNA viruses via the use of CLIP-SEQ techniques [45] . In addition , there is a growing body of work directed at obtaining asymmetric structures for this class of viruses in order to understand how their genomes are released during infection . Our approach is therefore likely to provide important insights into genome organization in wider groups of RNA viruses . In particular , many RNA viruses show order in the organizations of their genomes in icosahedrally-averaged cryo-EM and X-ray structures [46] , for example Bean Pod Mottle Virus [47] , STMV [30] and Pariacoto virus [48] . In such cases , constraint sets in terms of paths with appropriate combinatorial properties can be used to map the putative asymmetric organization of their genomes into the corresponding symmetrically averaged densities and hence provide information on connectivity between the RNA-CP contact sites . A better understanding of the asymmetric organization of viral genomes is vital if we are to properly understand the functional roles of genomes in RNA viruses . Recent research has revealed that far from being a passenger in the assembly of the viral particle , genomes critically enhance the efficiency of virus assembly via multiple dispersed , sequence-specific contacts with capsid protein [14] . These PSs act collectively in a cooperative manner [18 , 49] , and their relative placement in the tertiary structure of the genome is important for their function . In particular , it is the relative affinities of the PSs for CP at defined positions in the packaged genome that impact on the geometries of the assembly intermediates , i . e . on the structures of the partially assembled protein shells on pathway to capsid . For the virus discussed here , it had previously been shown that this interplay of PS affinities and capsid geometry results in a highly ordered genome organization in proximity to capsid . It has moreover been established that the same overall organization of the packaged genome occurs in an evolutionarily related virus , GA [9 , 15] , suggesting that there is a selective advantage for a specific genome organization in this family of viruses . This advantage can be explained in terms of assembly pathways: since PSs are instrumental in recruiting CP to the growing nucleus during PS-mediated self-assembly , the positions of the PS-CP contacts impact on the geometry of the assembly intermediates and hence on the assembly pathways . For the conserved genome organization identified in MS2 and GA earlier [15] , this corresponds to an assembly pathway through the most stable intermediates , i . e . those forming a maximal number of CP-CP bonds [20] . This example illustrates that structural information on genome organization obtained via the method introduced here has important implications for our understanding of the functional roles of viral genomes in virus assembly . More broadly , the method applies to any virus for which RNA-protein contacts are important for virus assembly , i . e . all viruses that follow a PS-mediated assembly process [14] . PSs are known to exist in a number of viral families including those infecting humans , e . g . alphaviruses [50] , and plants [51] , so this method is applicable to wider groups of RNA viruses . We note that the exact mechanism by which PSs act to enhance virus assembly can vary . For example , for MS2 the PS-CP contacts trigger an allosteric switch between the two types of protein building blocks required for productive capsid formation , while for STNV PSs promote formation of the coat protein capsomere [22] , a trimer , by overcoming electrostatic repulsions between protein building blocks allowing increased ordering of the N-terminal RNA-binding domain . In both those cases the PSs form stem-loops in contrast to the dsRNA regions of STMV . In each case , however , PS-RNA interactions bias assembly towards a subset of the possible assembly pathways due to differential PS-CP affinities [18] . Specific PS binding moreover enhances assembly efficiency by triggering a collapse in the hydrodynamic radius of the genome below the inner radius of the virus protein shell [52] , enabling the assembly of the protein shell around the compacted genome . Knowledge of the precise locations of the PSs and connectivity between them , which is provided by the analysis presented here , is therefore an important component in understanding the mechanisms by which viruses achieve the observed assembly fidelity and efficiency in vivo . This , in turn , is a prerequisite for the development of novel antiviral strategies that target virus assembly . As demonstrated in [18] , drugs interrupting PS-CP interactions can slow down the assembly process and decrease viral yield via misencapsidation of cellular RNAs . Moreover , a better understanding of conserved features in the genome organization within a viral family provides novel insights into the selective pressures on viral evolution . The method described here enables the identification of such features , and therefore also has profound implications for our understanding of viral evolution .
The analysis was based on an asymmetric averaged tomogram of MS2 ( Fig . 1C ) [6] , obtained by imaging mature MS2 bound to its natural receptor , the F-pilus of E . coli . A total of 22 tomograms were taken with 2374 bound viral particles . The 1500 best correlating virion subtomograms ( 63% of the total ) were normalized , low-pass Fourier filtered to 30Å , and then averaged to produce a structure at 39Å resolution . The data was presented as a density map of 643 pixels , sampled to 9 . 12Å per pixel ( EMD-2365 ) . A difference map between the asymmetric EM reconstruction [6] and the X-ray structure of the protein capsid ( PDBID 2MS2 ) was determined as follows: the protein structure was filtered to 39Å resolution to match the EM data; then the pixel size and orientation of the two maps were made equivalent by trilinear interpolation of the reduced-resolution X-ray structure with Chimera [53] . Radial plots compared the distribution of density in the protein map and the tomogram , with the pilus/MP complex masked away for the calculation . The radial distributions were , as expected , similar in the radial ranges corresponding to CP , but different elsewhere at radial levels corresponding to viral RNA ( which is organized as a two-shell architecture , see [11] ) and the 44kDa single-copy MP . Note that the radial distributions were not identical in the area overlapping with CP—this was due to the low resolution of the map , as CP density could not easily be accounted for in the asymmetric map . Therefore , a contour mask of the tomogram with the protein map was used to sample the low-resolution map , and used to eliminate the protein density via the UCSF Chimera mask routine [53] , rather than a direct subtraction of the normalized maps . A mask of 0 . 5σ best isolated the RNA whilst excluding protein . Finally , two icosahedral masks were applied: the inner core of RNA was masked away under radius 80Å , and an outside mask of radius 120Å removed noise resulting from masking artifacts and the pilus/MP complex . The resultant pruned density contained information about ( i ) the outer RNA shell in contact with CP , ( ii ) MP , and ( iii ) potential traces of CP lying within the shell that were not captured by the masking process . A difference map was created between the icosahedrally-averaged map [11] and the asymmetric structure [6] . We based our analysis on density map EMD-1431 of mature MS2 , which was calculated using single particle analysis of 9 , 335 separate images , equating to ∼560 , 000 sample points with icosahedral averaging [11] . We used a procedure analogous to the one described above for the tomogram to isolate the RNA . The protein structure was filtered to 9 . 5Å resolution , with a grid spacing of 1 . 26Å , to match the symmetric map , and normalization of the resultant protein map to the CP area of the symmetric map was performed . The resampled filtered protein was then subtracted from the symmetric map , yielding a symmetric cage of RNA with a polyhedral shape as in Fig . 1B . The outer shell of RNA was isolated by icosahedral masking with vertex radii of 80Å and 120Å . The resulting map for the outer RNA shell in the icosahedrally-averaged map was aligned with that for the asymmetric RNA organization in the tomogram by reference to the X-ray protein structure used to create each difference map , via UCSF Chimera [53] . After normalization , the aligned maps had similar average , standard deviation and maximum density values . The UCSF Chimera Segment Map tool [54] was used to perform a ( watershed ) segmentation on the symmetric RNA cage density , which partitioned the polyhedral density into segments attributed to its edges . Each long edge of the cage in Fig . 1B was represented by three segments as shown in S2 Fig . The same watershed segmentation was applied to the asymmetric RNA outer shell map . Hence pixels from the asymmetric RNA map were associated with defined segments on the polyhedral shell , and each connection thus had a density profile associated with it . We decided to make a very conservative decision on how much data to include , and thus only used the density encoded by the middle segment to represent a long edge . This was because the short segments close to the polyhedral vertices , as well as the short edges themselves , might have contained density corresponding to the RNA-CP contact ( i . e . PS ) located at a polyhedral vertex bordering the edge , which could have distorted the analysis . Moreover , connections between PS positions adjacent to the MP/pilus ( see S1 Fig ) were discarded as they may have contained unmasked MP density . To determine which long edges were occupied , we analysed the density distributions as follows . We computed fitted normal distributions using the norm . fit function from the scipy . stats python library , since for a sparse dataset the mean of a fitted normal distribution is less affected by outliers than the raw data . The normal fitting function automatically calculated the best positioning of a unimodal normal distribution for the dataset . Connections occupied in the RNA density were expected to have a substantially higher mean density than unoccupied connections . Moreover , skews of the distributions were computed via scipy . stats . skew . If a distribution representing density for a connection was negatively skewed , it could not be unambiguously classified as occupied or non-occupied , as this suggested smearing of density . We therefore did not place any constraints on edges with negatively skewed distributions .
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Viruses are responsible for devastating illnesses in humans and cause significant commercial losses in livestock and crops . Their genetic material is transported into their host organisms via protein containers , called viral capsids , that act as Trojan horses: they release their cargo into the cells of their hosts , hijacking their molecular machinery for the production of progeny viruses . Imaging techniques exploiting the symmetric structures of viral capsids have been used to determine details of their organization to atomic resolution , opening up the possibility to design anti-viral agents against specific surface structures . In many viruses the genomes take on specific organizations as a consequence of their roles in capsid formation . In order to design an additional class of anti-viral drugs that interfere with this process , it is important to understand the asymmetric organization of the genome inside viral capsids . This is currently a challenge , as the averaging techniques used to achieve high resolution structures of the protein containers cannot be used . We present a new approach and demonstrate its predictive power here for a test virus . This paves the way for a better understanding of the functional roles of viral RNAs in virus assembly and their exploitation in anti-viral drug design .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[] |
2015
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Asymmetric Genome Organization in an RNA Virus Revealed via Graph-Theoretical Analysis of Tomographic Data
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Root-knot nematodes ( RKN ) are obligatory plant parasitic worms that establish and maintain an intimate relationship with their host plants . During a compatible interaction , RKN induce the redifferentiation of root cells into multinucleate and hypertrophied giant cells essential for nematode growth and reproduction . These metabolically active feeding cells constitute the exclusive source of nutrients for the nematode . Detailed analysis of glutathione ( GSH ) and homoglutathione ( hGSH ) metabolism demonstrated the importance of these compounds for the success of nematode infection in Medicago truncatula . We reported quantification of GSH and hGSH and gene expression analysis showing that ( h ) GSH metabolism in neoformed gall organs differs from that in uninfected roots . Depletion of ( h ) GSH content impaired nematode egg mass formation and modified the sex ratio . In addition , gene expression and metabolomic analyses showed a substantial modification of starch and γ-aminobutyrate metabolism and of malate and glucose content in ( h ) GSH-depleted galls . Interestingly , these modifications did not occur in ( h ) GSH-depleted roots . These various results suggest that ( h ) GSH have a key role in the regulation of giant cell metabolism . The discovery of these specific plant regulatory elements could lead to the development of new pest management strategies against nematodes .
Glutathione ( GSH ) is a tripeptide , γ-glutamyl-cysteinyl-glycine , present in a wide range of organisms . It is a low molecular weight thiol which in plants is involved in antioxidant defense , detoxification of xenobiotics and tolerance to abiotic and biotic stresses [1] . GSH regulates the expression of stress defense genes and is involved in plant resistance to oomycete and bacterial pathogens and insect herbivores [2]–[4] . GSH is also involved in organ development and its role in seed maturation and root and leaf growth has been established [5]–[7] . In certain legumes , a GSH homolog , homoglutathione ( hGSH ) , is also present instead of , or in addition to , GSH [8]–[10] . The synthesis of GSH is a two-step process . In the first step , γ-glutamylcysteine synthetase ( γ-ECS ) produces the dipeptide γ-glutamylcysteine ( γ-EC ) from L-glutamic acid and L-cysteine and regulates the accumulation of GSH and hGSH [ ( h ) GSH] . The formation of GSH and hGSH is determined by the substrate specificity of the enzyme catalyzing the second step . Glutathione synthetase ( GSHS ) catalyses the addition of glycine to γ-EC , whereas homoglutathione synthetase ( hGSHS ) catalyses the addition of β-alanine to γ-EC . In the model legume Medicago truncatula , we have shown that ( h ) GSH deficiency alters the nitrogen fixing symbiotic interaction and reduces the formation of root nodules [11] . The transcriptomic response of ( h ) GSH-deficient plants to Sinorhizobium meliloti infection showed a downregulation of genes involved in meristem formation and an increased expression of several genes involved in the early plant defense reaction against abiotic or biotic stresses [12] . Thus ( h ) GSH may regulate both nodule neoformation and the plant defense response during symbiosis [12] . Plant-parasitic nematodes that infect M . truncatula and other legumes have emerged as models for studying the molecular dialogue during plant-nematode interactions and investigating whether beneficial plant symbionts and biotrophic pathogens induce distinct or overlapping regulatory pathways [13]–[17] . Root-knot nematodes ( RKN , Meloidogyne spp . ) are obligate root pathogens that interact with their hosts in a remarkable manner . During a compatible interaction , infective second stage RKN juvenile ( J2 ) migrate intercellularly towards the vascular cylinder and induce the redifferentiation of root cells into specialized nematode feeding cells named giant cells ( GCs ) . GCs are hypertrophied and multinucleate . They are the result of successive nuclear division without cell division and isotropic growth [18] . Mature GCs are metabolically very active , and act as transfer cells between vascular tissues and RKN . They are the sole source of nutrients for the feeding nematode and are thus essential for nematode growth and development [19] . Hyperplasia of neighboring cells ( NCs ) leads to the gall , the characteristic symptom of RKN infection . Once sedentarized , J2 molt three times to reach the adult stage . The reproduction of M . incognita is parthenogenetic: males migrate from the root and are not required for reproduction whereas the pear-shaped females produce and extrude eggs in a gelatinous matrix onto the root surface . The formation of both nodule and gall requires root cell dedifferentiation and modification of their cell cycle [20] , [21] . Moreover , both nematodes and rhizobia seem to actively modulate the host plant defense , so as to allow the compatible interaction [22] , [23] . The modifications to the plant defense and organogenesis observed in these plant-microbe interactions led us to analyze ( h ) GSH metabolism in galls . We studied the involvement of these tripeptides in the M . incognita development cycle in M . truncatula and tested for modifications of gall metabolism under ( h ) GSH deficiency .
The development cycle of M . incognita in M . truncatula is 6–7 weeks long . We analyzed ( h ) GSH metabolism during the RKN life cycle . First , the expression of M . truncatula γECS , GSHS and hGSHS genes was evaluated by qRT-PCR ( Figure 1A ) . The expression of γECS and hGSHS was significantly lower in galls than in uninfected roots from 2 wpi ( Figure 1B and D ) . In contrast , no significant difference in the expression of GSHS was observed between galls and uninfected roots ( Figure 1C ) . We tested whether the changes in the expression of the genes involved in ( h ) GSH synthesis correlated with the GSH and hGSH pools ( Figure 2A ) . The quantification of ( h ) GSH pools by HPLC analysis ( Figure 2 ) showed that hGSH was significantly less abundant in galls than in uninfected roots during the first two wpi corresponding to the period of GC formation ( Figure 2A ) . By contrast , the GSH pool was significantly larger in galls than in uninfected roots 3 and 5 weeks post infection ( wpi ) with 4 fold-higher level in mature galls 5 wpi ( Figure 2B ) . To assess the involvement of ( h ) GSH in the plant-nematode interaction , we analyzed the production of egg masses by the nematode in ( h ) GSH-depleted plants . The plant ( h ) GSH pool was depleted pharmacologically with L-buthionine-[S–R]-sulfoximine ( BSO ) , a specific inhibitor of ( h ) GSH synthesis . The effect of BSO treatment on nematode fitness was analyzed by treatment with 1 mM BSO supplemented with 1% resorcinol , a compound shown to induce solute uptake in nematodes [24] . No difference in nematode reproduction was observed between BSO-treated nematodes and controls ( Figure S1 ) . Treatment with 0 . 1 mM BSO applied one week before infection led to an 85% reduction of total ( h ) GSH in roots as previously described [11] . The primary root of each control and ( h ) GSH-depleted plants was then inoculated with M . incognita and the production of egg masses at 7 wpi was used as a measure of nematode reproduction efficiency ( Figure 3 ) . A mean of 23 egg masses was produced in control plants at 7 wpi ( Figure 3A ) . BSO treatment led to a 75% reduction in the ( h ) GSH content and a 95% diminution of egg mass production in ( h ) GSH-depleted plants relative to control plants . To verify that this reduction in egg mass production was related to the decrease in ( h ) GSH content and not to another secondary effect of BSO , RNAi was used to deplete ( h ) GSH in M . truncatula roots of composite plants [25] . The transgenic roots carrying the γecs-RNAi construct were compared with transgenic roots expressing an RNAi construct for the Green Fluorescent Protein ( GFP ) as a control . The number of egg masses and the ( h ) GSH content of composite plants were analyzed for each individual root at 7 wpi ( Figure 3B ) . Both ( h ) GSH content and the number of egg masses were significantly lower in the γecs-RNAi roots than the control gfp-RNAi plants . These experiments demonstrate that the reduction in ( h ) GSH content in galls correlates with a decrease in nematode egg mass production . As pharmacological and genetic ( h ) GSH depletion resulted in similarly impaired nematode reproduction , we mainly used BSO treatment to produce sufficient amounts of homogeneous material for further experiments . However , the major results of ( h ) GSH depletion were confirmed on genetically-modified material . To determine whether the reduction of egg masses was linked to a delay or an arrest in nematode development , galls were dissected at 4 and 7 wpi and the number of nematodes at each developmental stage ( juvenile , male and female ) was counted ( Figure 4 ) . At 4 wpi , an average number of 27 nematodes were detected per control plant whereas only 18 nematodes were observed in each ( h ) GSH-depleted root , suggesting that nematode infection is affected by ( h ) GSH depletion . Thirteen of the nematodes were at the female stage in control galls . In contrast , no female was observed in ( h ) GSH-depleted galls: almost all nematodes were at the juvenile stage and few males were identified in ( h ) GSH-depleted galls ( Figure 4 ) . Under genetic ( h ) GSH depletion , a significant lower number of nematodes at the female stage was also observed in the γecs-RNAi roots than in the gfp-RNAi control ones ( Figure S2A ) . Moreover , the proportion of males was also significantly increased in γecs-RNAi roots ( Figure S2B ) . At 7 wpi , the proportion of females was much lower in ( h ) GSH-depleted galls ( 23% ) than in control galls ( 90% ) and more than half of the nematodes were still juvenile; ( h ) GSH-depleted galls also contained a large proportion of males ( 23% vs 0 . 1% in controls ) ( Figure 4 ) . Thus , the ( h ) GSH depletion substantially reduced the number of females per gall ( from 27 for controls to 2 . 3 for ( h ) GSH-depleted galls ) consistent with its effects on egg mass formation . In addition , the numbers of nematodes in ( h ) GSH-depleted galls at 7 wpi shows that juveniles present at 4 wpi mostly molted into males , or were eliminated from the gall . The dissection analysis showed that nematode development was impaired at four wpi as no female was detected in ( h ) GSH-depleted plants at this time point . To test the effect of ( h ) GSH deficiency on the formation of GC , molecular and cellular analyses were performed at 2 wpi ( Figure 5 ) . First , the expression of marker genes involved in GC development was evaluated by qRT-PCR ( Figure 5A ) . The establishment of RKN infestation is associated with the suppression of plant defense responses and the induction of genes encoding proteins involved in both cell wall and DNA metabolism [22] . We therefore studied the expression of the defense-related genes , Pathogenesis-Related 1 protein and patatin , of expansin and of histone H3 . During the interaction between M . truncatula and M . incognita , the expression of both Pathogenesis-Related 1 protein and patatin was significantly weaker in galls at 2 wpi than in uninfected controls; however , the expression of both expansin and histone was higher in galls than controls . No significant difference was observed between the expression of these four marker genes in ( h ) GSH-depleted galls and that in the controls . GC morphology was analyzed to detect potential morphological effects ( Figures 5B and 5C ) . Microscopic analysis at 2 and 3 wpi revealed GCs with dense cytoplasm , multiple small vacuoles and nuclei observed in both ( h ) GSH-depleted galls and control galls ( Figures 5B , 5C and Figure S3 ) . Thus , there was no significant molecular or cellular difference between ( h ) GSH-depleted galls and control galls strongly suggesting that GC ontogenesis was unaffected by ( h ) GSH depletion . Depletion of ( h ) GSH was thus associated with impaired nematode development and in particular the absence of females at 4 wpi . We performed a metabolomic analysis of control and ( h ) GSH-depleted roots and galls at 3 wpi to assess primary metabolic effects . We investigated the major compounds of the primary metabolism in roots and galls through an untargeted proton Nuclear Magnetic Resonance ( 1H-NMR ) analysis approach . Eighteen primary and secondary metabolites were identified in the 1H-NMR spectra of each extract ( Figure S4 ) after peak assignment using chemical shift reported in the literature and metabolomic databases , with assistance from 2D NMR and/or by spiking samples with commercial compounds . Eighteen additional metabolites remained unidentified . Clear differences between uninfected roots and galls were obvious on visual inspection of spectra and were confirmed by quantification of metabolites . Eighteen of the 37 quantified metabolites were related to sugar , organic acid and amino acid metabolism ( Table 1 ) . Starch , an important sugar reservoir in nematode-induced syncytia [26] , was assayed enzymatically . Principal component analysis ( PCA ) was used to provide an overview of sample grouping and metabolic differences between uninfected roots and galls: we used a matrix containing the data for the 18 identified and quantified polar metabolites plus starch ( Figure 6 ) . The first principal component ( PC1 ) of the score plots ( Figure 6A ) , explaining 56% of the total variability , clearly separated galls ( on the negative side ) from uninfected roots ( on the positive side ) . The loading analysis ( Figure 6B ) suggested that the major metabolites contributing to this separation along PC1 were sucrose , trehalose , malate , fumarate , six amino acids ( aspartate ( Asp ) , glutamate ( Glu ) , isoleucine ( Ile ) , phenylalanine ( Phe ) , tyrosine ( Tyr ) and valine ( Val ) ) and trigonelline on the negative side and glyoxylate on the positive side . PCA score plot also showed that the second principal component ( PC2 ) , explaining 17% of the total variability , clearly separated ( h ) GSH-depleted ( on the negative side ) from control galls ( on the positive side ) ( Figure 6A ) . Observation of PC2 loading ( Figure 6B ) suggested that this separation along PC2 mainly involved γ-aminobutyrate ( GABA ) , Ile , Val , Glu , Asp and Asn on the negative side and glucose , starch and proline-betaine on the positive side . The PCA was confirmed by univariate analyses of metabolite data ( Table 1 ) . Relative to control roots , galls exhibited a significantly higher content of starch , sugars ( sucrose , glucose ) , organic acids ( malate , fumarate ) and amino acids ( Phe , Tyr , Val , Glu , Asp ) . However , the increase in amounts of these metabolites was not related to a similar modification of the expression of primary metabolism genes , the expression of which was maintained ( Sucrose synthase 1 , ADP-glucose pyrophosphorylase , starch synthase , α 1–4 glucan phosphorylase , pyruvate kinase ) or even decreased ( cell wall-invertase , mitochondrial malate dehydrogenase , malate synthase , phosphoenolpyruvate carboxylase , phosphoenolpyruvate carboxykinase ) in galls ( Figure 7 ) . Interestingly , the asparagine ( Asn ) content of control galls was significantly lower than that of control roots ( Table 1 ) . This was related to a significant decrease in expression of the asparagine synthetase and an increase in that of asparaginase ( Figure 7 ) . Proline-betaine , production of which in plants is related to the water stress response , accumulated significantly more in galls than control roots ( Table 1 ) . Trigonelline , another aminated compound related to secondary metabolism and potentially involved in salt-stress response [27] , was also more abundant in galls than control roots ( Table 1 ) . Finally , trehalose accumulation may also be related to a modification of the osmotic status in galls [28] . We used these metabolite and gene expression data to establish a metabolic pathway scaffold ( sucrose and starch metabolism , glycolysis and the tricarboxylic cycle connected branch points toward organic acid and amino acid synthesis ) highlighting the significant differences observed between roots and galls ( Figure 8A ) . Generally , there is little correlation between increased accumulation of quantified metabolites and the expression of the associated primary metabolism genes . Depletion of ( h ) GSH modified the metabolism of roots and galls in different ways . Most metabolites in roots were not significantly modified by ( h ) GSH-depletion . PCA analysis of the 18 identified and quantified polar metabolites plus starch showed that ( h ) GSH-depleted and control uninfected roots had a similar composition of polar metabolites ( Figure 6A ) . Significant variations were observed only for the hydrophobic amino acids Ile , Phe and Tyr , for trigonelline and for starch ( Table 1 ) . Indeed , the starch content was decreased 3-fold and starch synthase was significantly down regulated by ( h ) GSH depletion , suggesting that starch metabolism in roots is regulated by ( h ) GSH content or metabolism . Unlike the findings for uninfected roots , ( h ) GSH depletion had substantial effects on the metabolism of galls ( Figure 6 ) . The content of nine metabolites differed significantly between ( h ) GSH-depleted galls and control galls ( Table 1 ) . Starch and glucose contents were significantly lower in ( h ) GSH-depleted galls , whereas that of sucrose was not significantly different . With the exception of malate , the abundance of which was significantly decreased , the organic acid content of galls was not significantly affected by ( h ) GSH depletion . In the γecs-RNAi galls , starch , glucose and malate contents were also significantly lower than in the control gfp-RNAi galls ( Table S1 ) . Consistent with these findings , the relative expression in galls of most genes involved in the metabolism of sugars and organic acids was not significantly modified by ( h ) GSH depletion . The amino acids content was slightly increased by ( h ) GSH depletion , with the exception of Asn which was increased two-fold to the range of that found in roots ( Table 1 ) . This increase in Asn content was associated with a significant decrease in asparaginase gene expression and a two-fold increase in asparagine synthetase gene expression associated with ( h ) GSH depletion ( Figure 7 ) . A similar trend was also observed for proline-betaine , the content of which in ( h ) GSH-depleted galls was close to that in uninfected roots . Thus , our data indicate that ( h ) GSH depletion partially reversed the effect of nematode infection on starch , glucose and Asn metabolism , and on proline-betaine accumulation . Interestingly , GABA , a compound associated with biotic and abiotic stresses [29] , was markedly more abundant in ( h ) GSH-depleted than control galls . The significant differences between control and ( h ) GSH-depleted galls are summarized in a metabolic pathway scaffold ( Figure 8B ) . As observed for the comparison between galls and uninfected roots , differences in metabolite contents were more marked than the differences between gene expression levels . This implies post-transcriptional regulatory mechanisms , such as post-translational modifications or metabolic controls , in the metabolic modifications associated with ( h ) GSH depletion of galls .
M . truncatula roots contain two low molecular weight thiols , GSH and hGSH [9] . The ( h ) GSH content is significantly higher in galls than in roots at later stages of gall functioning . Surprisingly , γECS transcript level was lower in galls than in roots whereas this gene should regulate the level of ( h ) GSH . The post-transcriptional regulation of γECS [33] , [34] may explain the discrepancy between γECS transcript level and GSH accumulation . ( h ) GSH accumulation has been observed in several developmental conditions involving endoreduplication and enhanced metabolic capacity such as in symbiotic nitrogen fixation [9] and in trichomes [35] , both physiological modifications also occurring during gall formation and function [18] , [22] , [36] . In addition , the accumulation of GSH in galls may be caused by the nematode , as a GSHS has been identified amongst the proteins secreted by M . incognita [37] . Finally , ( h ) GSH accumulation is also associated with the nematode secreting multiple redox- and ( h ) GSH-regulated proteins , including thioredoxin , glutathione peroxidases and glutathione-S-transferases , required for the completion of nematode life cycle [37] , [38] . Indeed , the control of the plant cell redox status through the modification of the ( h ) GSH content may be a key regulator of the GC effectiveness . We show here that root ( h ) GSH deficiency strongly impairs nematode reproduction . This reduction of egg masses seems to be largely a consequence of the nematode sex ratio in galls . At 7 wpi , galls in ( h ) GSH-depleted plants harbored only one third as many nematodes as controls , suggesting that most juveniles developed into males and therefore migrated from the gall to soil such that they were not found in the gall by dissection . An hypothesis might be that BSO would be involved in direct impairment of GSH production in nematodes [39] , [40] and thus modify their development and egg mass production . Analysis of M . incognita genome using Caenorhabditis elegans γECS and GSHS sequences shows that the GSH biosynthesis genes are present in M . incognita . Moreover , HPLC analysis shows that GSH is produced in M . incognita J2 larvae ( unpublished data ) . The effect of GSH depletion on M . incognita development could not be directly tested as it is a plant obligatory parasite . However , data provided on WormBase ( http://www . wormbase . org ) showed that GSH does not play a major role in both development and health in C . Elegans . GSH depletion induced by γECS-RNAi or gene deletion is not larval or embryonic lethal and does not induce slow growth and female sterility [41]–[43] . Finally , the lower egg mass production , the modifications of the nematode sex-ratio and metabolite contents observed in both BSO-treated plants and transgenic roots expressing a plant specific γECS-RNAi construct show that these modifications are not linked to direct impairment of nematode function by BSO . During symbiosis between M . truncatula and S . meliloti , the ( h ) GSH depletion reduces the formation of nodule meristems [11] . Transcriptomic analysis evidences the involvement of ( h ) GSH regulation both in plant development and defense responses [12] . In contrast , under similar conditions , the development of the feeding site was not significantly affected and the expression of defense-related and development-related genes was not modified . Therefore , M . incognita is able to manipulate plant metabolism under ( h ) GSH depletion to avoid the defense and developmental phenotype observed during the establishment of nitrogen-fixing symbiosis . Root and gall metabolomic profiling showed that most of the analyzed metabolites were significantly more abundant in galls than in uninfected roots . These modifications , and the analysis of the expression of numerous genes involved in primary metabolism , indicate that the gall metabolism differs substantially from that in uninfected roots . One of the striking differences concerning general metabolite accumulation is the significantly lower Asn content in galls than in roots . This , and the associated upregulation of asparaginase and the down regulation of asparagine synthase , shows that nitrogen metabolism is modified in galls . Asn is the major nitrogen transporting compound in temperate legumes such as Medicago [44] , [45] . The primary site of Asn synthesis is the root and it follows that , through loading into the xylem , Asn is the principal nitrogen source for amino acids and protein synthesis in leaves . Thus , the decrease in Asn content upon nematode infection is likely to result in nitrogen deprivation for the plant . This metabolic modification may thus reduce nitrogen supply to leaves and increase carbon and nitrogen accumulation in galls . Our findings show that gall metabolism involves the fine-tuning of metabolism involving both the up regulation of some metabolic pathways and the down regulation of others , so as to enhance nutriment availability for the nematodes . Analysis of metabolite contents shows that ( h ) GSH depletion significantly affect gall metabolism . A significant difference in metabolite content between control and ( h ) GSH-depleted galls was detected for half of the metabolites quantified . In contrast , ( h ) GSH depletion did not significantly modify the content of the major primary metabolites in uninfected roots . This result is in agreement with our previous findings that a 85% depletion of ( h ) GSH does not significantly affect root growth [11] . The metabolic modifications observed in ( h ) GSH-depleted galls include a significant reduction of malate ( 40% ) , glucose ( 60% ) and starch ( 84% ) . Starch accumulation during the interaction between A . thaliana and the parasitic nematode Heterodera schachtii is crucial for the nematode infection and development . It may serve as long- and short-term carbohydrate storage for the feeding needs of the parasites [26] . Glucose and malate are likely substrates and probably essential for nematode nutrition . Thus , the diminution of these three metabolites under ( h ) GSH depletion may impair nematode carbohydrate nutrition . The development of M . incognita juveniles into males rather than females has previously been observed under unfavorable nematode feeding conditions such as low concentrations of sucrose in the growth medium , defoliation and complete removal of the host plant above-ground parts [46]–[48] . These conditions also trigger carbon starvation of the galls . Carbohydrate nutrition deficiency has been also involved in the modification of sex ratio and development of cyst nematode [49] . The development of M . incognita juveniles into males rather than females in ( h ) GSH-depleted galls is similar to that observed during carbohydrate deficiency . This is consistent with ( h ) GSH being involved in the modulation of nematode differentiation through regulation of gall carbon metabolism . Interestingly , GABA was specifically detected in ( h ) GSH-depleted galls . In plants , GABA accumulates in response to abiotic and biotic stresses [50] . During biotic stress induced by invertebrate pests , GABA accumulation in plant tissues reduces the feeding capacity of the pests [51] . Strikingly , the reproduction of Meloidogyne hapla is affected by GABA accumulation: egg mass production by M . hapla infecting transgenic plants accumulating GABA is lower than that by the pests infecting control plants [52] . Thus , the accumulation of GABA in ( h ) GSH-depleted galls may also contribute to the altered nematode reproduction . The substantial primary metabolite modifications in ( h ) GSH-depleted galls with reference to control galls were not associated with corresponding modification in the expression of primary metabolism genes . This suggests that ( h ) GSH regulates gall metabolism at levels other than transcriptional . Redox state and GSH affect the function of many enzymes through post-translational modifications such as disulfide bond reduction and cysteine glutathionylation [53] . For instance , thioredoxins and glutaredoxins , which are involved in the formation/reduction of disulfide bonds between proteins , have been implicated in the regulation of chloroplast metabolism [54] , [55] . ADP glucose pyrophosphorylase , a key enzyme in the biosynthesis of starch was also shown to be redox regulated [56] , [57] . Cysteine glutathionylation is an important regulatory mechanism of photosynthetic metabolism [58] . More generally , in vivo control of many glycolytic and/or TCA cycle enzymes by disulfide-dithiol interconversions ( NAD-dependent GAPDH , citrate synthase , PPi-dependent phosphofructokinase , PEPC kinase , etc ) has been reported in plants [59] . Thus , a redox-based control of the gall metabolism by ( h ) GSH may be proposed to explain our results . We cannot exclude that GSH may also be used as a nutrient by the nematode as the GSH content was strongly increased in mature galls compared to roots . However , the impact of ( h ) GSH depletion on gall metabolism is not in favour of a trophic role for ( h ) GSH . Moreover , during nitrogen fixing symbiosis in which GSH is not used as nutrient to feed the bacteroids , modifications of the ( h ) GSH content affects the nitrogen-fixing capacity of the nodule also showing the regulatory role of glutathione in this interaction [60] . In conclusion , we report that ( h ) GSH metabolism differs between galls and uninfected roots . A deficiency in ( h ) GSH impairs nematode reproduction by mainly altering its sex determination . This alteration in sex ratio is associated with modifications in the gall metabolism under ( h ) GSH depletion which have been shown to impair nematode development . Thus , we reveal a completely new role of ( h ) GSH in this biotrophic interaction . Interestingly , these modifications in metabolite content do not seem to occur in ( h ) GSH-depleted roots suggesting that ( h ) GSH depletion provokes metabolism modifications specific to the gall . Therefore , the reduction of ( h ) GSH availability in galls is a potentially useful strategy for pest management .
M . truncatula ecotype A17 was used for all the experiments . Sterilized seeds were germinated for 3 days onto 0 . 4% agar at 14°C . Seedlings were plated onto modified Fahraeus medium with 2 mM nitrogen [25] with 1 . 4% agar and grown for 7 days before infection . Plants were germinated in the presence or absence of 0 . 1 mM L-buthionine sulfoximine ( BSO ) . For nematode infection , 100 surface-sterilized freshly hatched M . incognita J2 larvae were added on each one week old seedling as previously described [13] . One infection per plant was performed on the primary root . For BSO treatment , nematodes were incubated for 4 hours in M9 buffer ( 43 . 6 mM Na2HPO4 , 22 mM KH2PO4 , 2 . 1 mM NaCl , 4 . 7 mM NH4Cl ) with 1% resorcinol and 1 mM BSO and with 1% resorcinol as control . The gall corresponds to one infection point and contains multiple GCs . After infection , plants were grown 3 weeks onto Fahraeus medium with 2 mM nitrogen in the presence or absence of BSO ( 0 . 1 mM ) in a growth chamber with a day temperature of 23°C and night temperature of 20°C and with a photo-period of 16 h . Then , plants were transferred in soil mixture ( 30% vermiculite-70% fine gravel ) until the end of the experiment . As reference samples , uninfected , primary root fragments of similar age were collected from seedlings grown under the same conditions . For gall dissection , galls were digested in a mixture of 30% Pectinex ( Novozymes , Bagsvaerd , Denmark ) and 15% Celluclast BG ( Novozymes , Bagsvaerd , Denmark ) for 12 h , dissected and nematode development stages were analyzed under a stereomicroscope . For metabolite and gene expression analyses , biological samples of galls and roots were harvested at different time points post-infection , frozen and ground in liquid nitrogen and stored at −80°C . One biological sample was issued from 20 galls or roots from 20 plants . Thiols were extracted with perchloric acid , derivatized with monobromobimane , and quantified after separation on reverse-phase HPLC as described previously [61] . Commercial GSH ( Sigma , St . Quentin , France ) and γ-EC ( Promochem , Molsheim , France ) were used as standards . The hGSH used as a standard was synthesized by Neosystem ( Strasbourg , France ) . Total RNA of galls and uninfected root fragments were reverse-transcribed using the OmniScript cDNA Synthesis Kit ( Qiagen , Courtaboeuf , France ) . Quantitative PCR reactions were performed using a DNA Engine Opticon 2 Continuous Fluorescence Detection system ( MJ Research , Waltham , USA ) and a qPCR MasterMix Plus for SYBR green I ( Eurogentec , Angers , France ) . In each reaction , 5 µl of 100 fold-diluted cDNA and 0 . 3 µM primer ( sequences used are described in Table S2 ) were used . The PCR conditions were 50°C for 5 min , 95°C for 10 min , followed by 40 cycles of 95°C for 30 s , 60°C for 1 min . Each reaction was performed in triplicate and the results represented the mean of three independent biological experiments . The specificity of the amplification was confirmed by a single peak in a dissociation curve at the end of the PCR reaction . Data were quantified by using Opticon Monitor 2 ( MJ Research , Waltham , USA ) and normalized with the 2−ΔΔCT method [62] . Two constitutively expressed genes Mtc27 ( TC106535 ) and 40S Ribosomal Protein S8 ( TC100533 ) were the endogenous controls [63] . The use of these housekeeping genes were validated by using the GeNorm VBA applet for MS Excel which determines the most stable housekeeping genes from a set of tested genes in a given cDNA sample panel [64] . PCR reactions for each of the three biological replicates were performed in technical triplicate . The absence of genomic DNA contaminations in the RNA samples was tested by PCR analysis of all samples using oligonucleotides bordering an intron in M . truncatula GSHS gene . To generate the γ-ECS-RNAi construct , a 502-bp region was amplified from the cDNA using gene-specific primers ( Supplemental Table S2 on line ) and cloned into the pDONR207 vector , subcloned in pENTR4 and integrated into the RNAi vector pK7GWIWG2DII , ( 0 ) [65]containing kanamycin resistance and the p35S:eGFP for selection and screening . M . truncatula plants ( A17 ) were transformed with A . rhizogenes containing precedent construct as described previously [25] and transformed roots were selected by resistance to kanamycin and screening of eGFP . Control plants were transformed with A . rhizogenes containing the pKGWIWG2DII , ( 0 ) vector containing an eGFP DNA fragment to rule out the potential side effects linked to plant transformation or the RNAi vector . Polar metabolites were quantified using 1H-NMR of polar extracts . For the preparation of extracts and NMR acquisition parameters , special care was taken to allow absolute quantification of individual metabolites . Briefly , polar metabolites were extracted on lyophilized powder ( 30 mg DW per biological replicate ) with an ethanol–water series at 80°C as described previously [66] . The lyophilized extracts were titrated with KOD to pH 6 in 100 mM potassium phosphate buffer in D2O and lyophilized again . Each dried titrated extract was solubilized in 0 . 5 mL D2O with ( trimethylsilyl ) propionic-2 , 2 , 3 , 3-d4 acid ( TSP ) sodium salt ( 0 . 01% final concentration ) for chemical shift calibration and ethylene diamine tetraacetic acid ( EDTA ) disodium salt ( 0 . 5 mM final concentration ) . 1H-NMR spectra were recorded at 500 . 162 MHz on a Bruker Avance spectrometer ( Bruker , Karlsruhe , Germany ) using a 5-mm dual 13C-1H cryoprobe and an electronic reference for quantification [66] . Sixty-four scans of 32 K data points each were acquired with a 90° pulse angle , a 6000 Hz spectral width , a 2 . 73 s acquisition time and a 25 s recycle delay . Preliminary data processing was conducted with TOPSPIN 1 . 3 software ( Bruker Biospin , Wissembourg , France ) . The assignments of metabolites in the NMR spectra were made by comparing the proton chemical shifts with literature [66]–[68] or metabolomic database values ( MeRy-B 2009 , HMDB ) , by comparison with spectra of authentic compounds recorded under the same solvent conditions and/or by spiking the samples . For assignment purposes , 1H-1H COSY , 1H-13C HSQC and 1H-13C HMBC 2D NMR spectra were acquired for selected samples . The metabolite concentrations were calculated using AMIX ( version 3 . 9 . 1 , Bruker ) and Excel ( Microsoft , Redmond , WA , USA ) softwares . The metabolites were quantified using the glucose calibration curve and the proton amount corresponding to each resonance for all compounds . The metabolite concentrations were calculated from concentrations in the NMR tube and sample dry weight . The 15 1H-NMR spectra of the data set were converted into JCAMP-DX format and deposited with associated metadata into the Metabolomics Repository of Bordeaux MeRy-B ( http://www . cbib . u-bordeaux2 . fr/MERYB/projects/home . php ? R=0&project_id=28 ) . To explore the metabolite multidimensional data set , we used principal component analysis ( PCA ) on mean-centered data scaled to unit variance ( MATLAB version 7 . 4 . 0 , the MathWorks Inc , Natick MA ) . Starch was recovered from the insoluble fraction of the extracts used for polar metabolite extraction after ethanol–water series at 80°C ( see above , Moing et al . 2004 ) . Insoluble residues were incubated for 1 h , at 55°C , in a 0 . 5 ml reaction medium containing 0 . 1 M sodium acetate , and 1 . 25 mg amyloglucosidase ( Sigma-Aldrich , Saint-Quentin Fallavier , France ) . Reaction was stopped for 5 min at 100°C . Supernatants were collected and evaporated over night under vacuum . Dry residues were taken up with 0 . 5 ml of 0 . 3 M Hepes , pH 7 . 5 , and 30 mM MgSO4 . Glucose , issued from starch hydrolysis , was measured as followed: 200 to 400 µl of samples were mixed with a reaction medium containing 0 . 3 M Hepes , pH 7 . 5 , 30 mM MgSO4 , 2 . 5 mM ATP , and 2 mM NAD . Initial OD was red at 340 nm . Next , 2 Units of both hexokinase ( Sigma-Aldrich , Saint-Quentin Fallavier , France ) and glucose-6-phosphate dehydrogenase from Leuconostoc mesenteroides ( Sigma-Aldrich , Saint-Quentin Fallavier , France ) were added , and samples were incubated for 1 h , at room temperature in the dark . Final OD was red at 340 nm . The difference between the final and initial OD was used to calculate the glucose content . Starch was expressed as nmol of glucose equivalent per dry weight unit . Malate was quantified by ionic chromatography and conductimetry . Separation was performed on an IonPac AS 11 column ( 4×250 mm , Dionex , Sunnyvale , CA , USA ) and a IonPac AG11 guard column ( 4×50 mm , Dionex ) with a NaOH gradient including 16% of methanol . Calibration was performed with commercial standards using gravimetric method . DNA sequences were analyzed using BLAST [69] against the databases of the NCBI ( http://blast . ncbi . nlm . nih . gov/ ) , MtGI ( http://compbio . dfci . harvard . edu/cgi-bin/tgi/gimain . pl ? gudb=medicago ) and the IMGAG ( http://www . medicago . org/genome/ ) . The accession numbers of the genes used in this study are indicated in the Supplemental Table S2 . All the data presented are given as means with the standard error of three or four independent biological experiments . The significance of the results was tested using Student t-test ( P value ≤0 . 05 ) .
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Parasitic nematodes are microscopic worms that cause major diseases of plants , animals and humans . During compatible interactions , root-knot nematodes ( RKN ) induce the formation of galls in which redifferentiation of root cells into multinucleate and hypertrophied giant cells is essential for nematode growth and reproduction . The importance of glutathione ( GSH ) , a major antioxidant molecule involved in plant development , in plant microbe interaction and in abiotic stress response , was analyzed during the plant-RKN interaction . Our analyses demonstrated that the gall development and functioning are characterized by an adapted GSH metabolism and that depletion of GSH content impairs nematode reproduction and modified sex ratio . This phenotype is linked to specific modifications of carbon metabolism which do not occur in uninfected roots indicating a peculiar metabolism of this neoformed organ . This first metabolomic analysis during the plant-RKN interaction highlights the regulatory role played by GSH in this pathogenic interaction and completes our vision of the role of GSH during plant-pathogen interactions . RKN sex ratio modification has previously been observed under unfavorable nematode feeding conditions suggesting that the GSH-redox system could be a general sensor of gall fitness in natural conditions .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"plant",
"science",
"plant",
"biology",
"plant",
"pathology",
"biology"
] |
2012
|
(Homo)glutathione Deficiency Impairs Root-knot Nematode Development in Medicago truncatula
|
Nucleoside hydrolases ( NHs ) show homology among parasite protozoa , fungi and bacteria . They are vital protagonists in the establishment of early infection and , therefore , are excellent candidates for the pathogen recognition by adaptive immune responses . Immune protection against NHs would prevent disease at the early infection of several pathogens . We have identified the domain of the NH of L . donovani ( NH36 ) responsible for its immunogenicity and protective efficacy against murine visceral leishmaniasis ( VL ) . Using recombinant generated peptides covering the whole NH36 sequence and saponin we demonstrate that protection against L . chagasi is related to its C-terminal domain ( amino-acids 199–314 ) and is mediated mainly by a CD4+ T cell driven response with a lower contribution of CD8+ T cells . Immunization with this peptide exceeds in 36 . 73±12 . 33% the protective response induced by the cognate NH36 protein . Increases in IgM , IgG2a , IgG1 and IgG2b antibodies , CD4+ T cell proportions , IFN-γ secretion , ratios of IFN-γ/IL-10 producing CD4+ and CD8+ T cells and percents of antibody binding inhibition by synthetic predicted epitopes were detected in F3 vaccinated mice . The increases in DTH and in ratios of TNFα/IL-10 CD4+ producing cells were however the strong correlates of protection which was confirmed by in vivo depletion with monoclonal antibodies , algorithm predicted CD4 and CD8 epitopes and a pronounced decrease in parasite load ( 90 . 5–88 . 23%; p = 0 . 011 ) that was long-lasting . No decrease in parasite load was detected after vaccination with the N-domain of NH36 , in spite of the induction of IFN-γ/IL-10 expression by CD4+ T cells after challenge . Both peptides reduced the size of footpad lesions , but only the C-domain reduced the parasite load of mice challenged with L . amazonensis . The identification of the target of the immune response to NH36 represents a basis for the rationale development of a bivalent vaccine against leishmaniasis and for multivalent vaccines against NHs-dependent pathogens .
In recent years , Nucleoside hydrolases ( NHs ) of trypanosomatid protozoa have emerged as strong phylogenetic markers of the Leishmania genus [1] , [2] and vital protagonists of pathways for parasite replication and establishment of infection . The purine-dependent protozoa: Crithidia fasciculata [3] , Trypanosoma brucei [4] , Trypanosoma cruzi [5] , Leishmania major [6] , Leishmania donovani [7] , [8] and Leishmania infantum [2] like most protozoan parasites , are deficient in de novo synthesis of purines . NHs cleave the N-glycosidic linkage of imported nucleosides making the purines available for further parasite DNA synthesis . NHs activities have also been described in bacteria and fungi [9] , [10] , [11] but not in mammals [11] , which have alternative pathways . Since NHs are expressed in the early stages of infection , they are excellent candidate targets for pathogen recognition by adaptive immune responses . NHs of Leishmania have been described in the parasite stages which infect the mammal host [1] , [2] , [6] , [7] , [8] and in the exosporium membrane of Bacillus anthracis being important for anthrax transmission [10] . Vaccines against NHs would then prevent the replication of many different pathogens at the very first stage of their life-cycle and thus prevent infection , mild disease , severe disease and death while vaccine with antigens present in later stages of the parasite cycle would only protect from severe disease and death [12] . The NH of L . donovani shows significant homology to the sequences of L . major ( 95% ) [7] , L . chagasi ( 99% ) , L . infantum ( 99% ) , L . tropica ( 97% ) , L . mexicana ( 93% ) , L . braziliensis ( 84% ) [13] , T . brucei ( 27% ) and Crithidia fasciculata ( 80% ) [7] and shares 68% identity with Haemophylus influenzae and 30% identity and conserved motifs with Bacillus anthracis [10] , [13] . Identification of the immunogenic molecular domain of the NH of one pathogen should allow the rational design development of a cross-protective subunit or synthetic vaccine and this would explain the protection generated by NH of Leishmania donovani against infections by other leishmanias [14]–[17] . However , the role of the Nucleoside hydrolases in the induction of immunoprotective CD4+ T cell driven or CD8+ T cell-mediated cytotoxic immune response has never before been systematically examined in the context of parasitic diseases . We developed the first licensed second generation vaccine against visceral leishmaniasis [18]–[21] that has already reduced the incidence of the human and canine disease in endemic areas [22] . Its main component is the Nucleoside hydrolase of Leishmania donovani ( NH36 ) which was specifically recognized by sera of patients of human VL [23] and by most anti-FML monoclonal antibodies [24] . According to the guidelines of WHO [12] , NH36 was first identified as a powerful antigen present in the early stages of the parasite infection . Its NH nature and degree of identity to other Leishmanias NHs was only disclosed after molecular cloning [8] . In its native form it protected mice from infection by L . donovani [25] and was also identified by polyclonal antibodies among promastigote exo-antigens [7] . In its recombinant or DNA formulations it protected mice from infection by L . chagasi , L . mexicana [14] , [15] , L . amazonensis [16] and L . major [17] and dogs from infection by L . chagasi [26] indicating the potential use of its sequence in protection against both leishmaniasis . As a bivalent vaccine , it induced a TH1 immune response mediated by IFN-γ-producing CD4+ T cells which led to a 88% prophylaxis against visceral leishmaniasis ( VL ) [14] , 65–81% against tegumentary leishmaniasis ( TL ) [14] , [16] , [17] and 91% immunotherapy against VL [27] . Also , higher proportions of CD4+-NH36 specific lymphocytes and higher levels of IFN-γ , IL-2 were found in NH36-vaccinated dogs than in untreated controls [26] . NH36 is composed of a 314 amino acid sequence [7] . In order to map the domain which is the target of the adaptive immunity , three recombinant fragment proteins representing the amino acids 1–103 ( F1 , N-terminal domain ) , 104–198 ( F2 , central domain ) and 199–314 ( F3 , C-terminal domain ) were generated and used for the stimulation of splenocytes of NH36 vaccinated mice , which secreted IFN-γ and TNF-α after stimulation with the F3 followed by the F1 fragment , confirming the induction of a cellular protective TH1 immune response [28] . An effective subunit vaccine against VL must include T cell epitopes capable of eliciting protective immune responses , since progressive suppression of the cellular immunity is one of the main signs of the disease . Synthetic vaccines based on short peptides which represent immunogenic epitopes are able to impair and even exceeded the protective potential of the native cognate whole protein [29] and they can also induce universal T cell responses , which are related to many human HLA-DR allotypes and to diverse mice genetic backgrounds [30] , [31] . In this investigation , we vaccinated mice with the F1 , F2 and F3 recombinant peptides and saponin in order to identify the NH36 protective epitopes recognized by antibodies and by MHC class I and II restricted T cells and then move on to develop a Nucleoside hydrolase based synthetic vaccine against VL . We identified the C-terminal domain of the Nucleoside hydrolase NH36 as being responsible for the adaptive immunity and vaccine-induced protective efficacy .
All mouse studies followed the guidelines set by the National Institutes of Health , USA and the Institutional Animal Care and Use Committee approved the animal protocols ( Biophysics Institute-UFRJ , Brazil , protocol IMPPG-007 ) . NH36 is composed of 314 aminoacids ( EMBL , Genbank and DDJB data bases , access number AY007193 ) . Three fragments of the NH36 antigen composed respectively , of the amino acid sequences 1–103 ( F1 ) , 104–198 ( F2 ) and 199–314 ( F3 ) were cloned in the pET28 plasmid system . Fragments were amplified by PCR with the Platinum Taq High Fidelity DNA polymerase ( Invitrogen ) and oligonucleotides containing the NcoI and XhoI restriction sites , cloned into the pMOS vector ( GE ) for sequencing confirmation and further cloned into pET 28b . The recombinant proteins were expressed in E . coli Bl21DE3 cells and purified in a Ni-NTA column ( Qiagen ) . To improve protein expression , F2 was further cloned in the pET28a . The NH36 protein amino acid sequence was analyzed using epitope prediction algorithms based on MHC-binding motifs . Epitopes for antibodies and CD4+ lymphocytes were defined by the Protean Pad program based on the A . Sette algorithm for the H2d haplotype of Balb/c mice ( IAd and IEd alleles ) and epitopes for CD8+ T cells ( H2 Ld haplotype ) , by the HLA peptide motif search ( http://bimas . dcrt . nih . gov/molbio/hla_bind/ ) and the SYFPEITHI ( http://www . syfpeithi . de/ ) programs . Female Balb/c mice , 8-week-old , were vaccinated at weekly intervals , by the sc route , with 3 doses of 100 µg of NH36 , F1 , F2 or F3 recombinant proteins and 100 µg of SIGMA saponin [32] . On week 4 , mice were challenged with 3×107 L . chagasi amastigotes . Fifteen days after infection , mice were euthanized with ether and the parasite load was evaluated in Giemsa-stained liver smears and expressed in LDU values ( Leishman Donovan units of Stauber = number of amastigotes per 600 liver cell nuclei/mg of liver weight ) as described [32] . The increase in total body weight and liver/corporal relative weight were also recorded as clinical signs of VL . In order to assess the possible generation of long-term protection 8-week-old female Balb/c mice were vaccinated at weekly intervals , by the sc route , with 3 doses of 100 µg of F1 , F2 or F3 recombinant proteins and 100 µg saponin , challenged with 3×107 L . chagasi amastigotes on week 4 and euthanized 28 days after infection for evaluation of their liver parasite load . Seven days after immunization and 15 days after infection with Leishmania chagasi , antibodies of sera were measured in sera by an ELISA assay against NH36 recombinant protein as previously described [33] , using 2 µg antigen per well and goat anti-mouse IgG ( Sigma ) or goat anti-mouse IgG1 , IgG2a , IgG2b , IgG3 , IgM and IgA horseradish peroxidase conjugated antibodies ( Southern , Biotechnology Associates , Birmingham , AL , USA ) in a 1∶1000 dilution in blocking buffer . The reaction was developed with O-phenyldiamine ( Sigma ) , interrupted with 1 N sulfuric acid , and monitored at 492 ηm . Each individual serum was analyzed in triplicate in double-blind tests . Positive and negative control sera were included in each test . Results were expressed as the mean of the absorbance values ( 492 ηm ) of the 1/100 diluted sera of each animal . To determine the immunodominance of the sequences predicted to be antibody epitopes of NH36 by the Protean Pad program , the synthetic peptides were obtained and solubilized in DMSO . The FML antigen ( 2 µg/well ) was solubilized in carbonate buffer ( pH 9 . 6 ) , and used to coat flat-bottom 96-well plates for 1 h at 37°C and overnight at 4°C [33] . Plates were washed with blocking buffer and incubated for 1 h at 37°C with a pool of sera of healthy dogs vaccinated with the FML-based licensed vaccine ( Leishmune ) ( n = 10 ) in the presence or absence of each one of the synthetic peptides diluted in blocking buffer ( 0 . 5 to 0 . 0002 mM ) . Antibodies were detected using peroxidase-labeled protein-A ( Kirkegaard & Perry Laboratories , Gaithersburg , Maryland ) at a 1∶16000 dilution , in blocking buffer and the reaction was developed with O-phenyldiamine ( Sigma ) , interrupted with 1 N sulfuric acid , and monitored at 492 ηm . The absorbency values of sera pre-incubated with peptides at 0 . 125 mM was compared to that of total sera with no pre-incubation and expressed as percent of antibody binding inhibition . Sera were analyzed in triplicate . Positive and negative control sera were included in each test . Seven days after immunization and 15 days after infection with Leishmania chagasi , the intradermal response against L . donovani lysate ( IDR ) was measured in the footpads as described earlier [32] . Briefly , mice were injected intradermally , in the right hind footpad , with 107 freeze-thawed stationary phase Leishmania donovani promastigotes in 0 . 1 ml sterile saline solution . The footpad thicknesses were measured with a Mitutoyo apparatus , both before and 0 , 24 and 48 h after injection . Injecting each animal with 0 . 1 ml saline in the left hind footpad served as control . At each measurement , the values of the saline control were subtracted from the reaction due to Leishmania antigen . Previous experiments carried out in Balb/c mice and CB hamsters demonstrated that 24 h after inoculation saline treated footpads returned to base levels [32] , [34] . All further analyses of cellular immune responses were carried out using 106 splenocytes after 5 days of in vitro culturing at 37°C and 5% CO2 in RPMI medium and/or 5 µg of recombinant NH36 . Flow cytometry analysis ( FACS analysis ) in a FACScalibur apparatus was performed after splenocyte immunostaining with anti-CD4 ( clone GK1 . 5 ) or anti-CD8-FITC ( clone 53–6 . 7 ) monoclonal antibodies ( R&D systems , Inc ) . Secretions of IFN-γ and TNF-α were evaluated in the supernatants of in vitro cultured splenocytes with an ELISA assay , using the Biotin Rat anti-mouse IFN-γ ( clone XMG1 . 2 ) , the purified Rat anti-mouse IFN-γ ( clone R4-6A2 ) and the Mouse TNF ELISA Set II kit ( BD Bioscience Pharmingen ) according to the manufacturer's instructions . The intracellular production of IFN-γ , TNF-α and IL-10 cytokines by CD4+ and CD8+ T cells was determined using 10 mg/ml brefeldin ( SIGMA ) for 4 h at 37°C and 5% CO2 followed by washing with FACS buffer ( 2% Fetal Calf serum , 0 . 1% Na Azide in PBS ) . Cells were labeled for 20 min . at 4°C in the dark with rat anti-mouse CD4FITC and CD8FITC ( R&D systems ) in FACS buffer ( 1/100 ) . After that they were fixed with 4% paraformaldehyde , washed and treated with FACS buffer with 0 . 5% saponin ( SIGMA ) for 20 min . at room temperature and then further stained with IFN-γAPC , TNFPE and IL-10PE monoclonal antibodies ( BD-Pharmingen ) , 1/100 diluted in FACS buffer with 0 . 5% saponin for 20 min . , and finally washed and resupended in FACS buffer . For both the FACS and ICS methods , 30 , 000 cells were analyzed by flow cytometry on a Becton Dickinson FACScalibur apparatus , and further analyzed using WinMDI ( Windows Multiple Document Interface Flow Cytometry Application ) Version 2 . 8 software . In vivo depletion of CD4+ or CD8+ T cells was performed by treating NH36 and F3-vaccinated mice with GK1 . 5 or 53 . 6 . 7 rat IgG MAb on days 2 , 4 and 6 before challenge and on day 7 after challenge . Control mice received the NH36sap and F3sap vaccines and 0 . 05 ml of rat serum ip , equivalent to 0 . 25 mg of IgG , or nude mice ascitic fluids containing 0 . 25 mg of anti-CD4+ and/or anti-CD8+ antibodies . As determined by FACS analyses , the efficacy of depletion of CD4+ or CD8+ spleen cells before challenge was of 99 . 94% or 96% in anti-CD4+ or anti-CD8+ treated mice , respectively . The efficacy of depletion treatment was monitored by the increase in liver parasite load and liver relative weight , 15 days after infection . Female Balb/c mice , 8-week-old , were vaccinated at weekly intervals , by the sc route , with 3 doses of 100 µg of NH36 , F1 , F2 or F3 recombinant proteins and 100 µg of SIGMA saponin [32] . On week 4 , mice were challenged in the right hind footpad with 105 L . amazonensis ( PH 8 strain ) metacyclic promastigotes [17] which had been isolated from hamsters and maintained in Schneider's axenic media for 3 successive passages . Measurements of the infected footpad thicknesses were performed weekly with a Mitutoyo apparatus and the thickness values of the non-infected left footpads were substracted from them . The total number of parasites in footpad lesions was determined after sacrifice by Real Time PCR as modified from Manna et al . , [35] using the primers of Leishmania chagasi ( Primer forward: 5′GGCGTTCTGCGAAAACCG3′; Primer reverse 5′AAAATGGCATTTTCGGGCC3′ and Probe 5′TGGGTGCAGAAATCCCGTTCA3′ ) on DNA isolated from promastigotes of L . amazonensis ( PH 8 ) and the Taq man system . Briefly , for sample collection , 100 µl of PBS were injected and recovered from each infected footpad . Only 1 µl of each suspension was used for amplification by RTPCR . The normal distribution of values of each variable was assessed by the Anderson Darling A2 test ( Analyze-it ) . Means of normally distributed variables were compared by ANOVA analysis simple factorial test and by one way ANOVA-Tukey's honestly significant difference ( Tukey's HSD ) post-hoc method ( SPSS for Windows ) . When necessary the confidence interval ( 95% CI ) was also used . Means of non-normally distributed variables were compared by Kruskall Wallis and Mann Whitney non-parametrical tests ( Analyze-it ) . Correlation coefficient analysis was determined on a Pearson bivariate , two tailed test of significance ( SPSS for windows ) .
Mice were immunized with NH36 , F1 , F2 or F3 proteins and saponin ( NH36sap; F1sap , F2sap and F3sap vaccines , respectively ) , challenged with amastigotes of Leishmania chagasi on week 4 and euthanized on week 6 ( Figure 1A ) . The humoral response assayed by ELISA disclosed higher antibody levels to NH36 in the sera of vaccinated animals when compared to saline controls after immunization ( p<0 . 004 ) and after challenge ( p = 0 . 001 ) ( Figures 1B and C ) . The F3sap vaccine induced IgG levels as high as NH36sap . The IgM and IgG2a levels induced by the F3sap vaccine were as high as the ones elicited by NH36 and F1sap vaccines ( Figure 1B ) . The F2 vaccine induced only IgG2b and IgG1 , to the same extent as the other vaccines . After challenge ( Figure 1C ) only the IgG1 ( p = 0 . 039 ) and IgM ( p = 0 . 003 ) responses were lower . The F1sap increased the IgA and IgG and the F3sap , the IgG , IgG2a and IgG3 responses ( Figure 1C ) . The IgG2a level induced by the F3sap vaccine were 70% and 34% higher than those of F2sap and F1sap vaccines , respectively , suggesting that NH36 B cell epitopes for IgG2a antibodies are located mainly in the F3 fragment followed by the F1 fragment . The algorithm program predicted three B-cell epitopes in F3 , only one in F1 , one between F1 and F2 and one in F2 ( Figure 2 and Table 1 ) and the inhibition of antibody-binding assay was chiefly induced by the synthetic epitopes of F3 ( 18 . 82–31 . 40% ) ( Table 1 ) confirming its superiority for the induction of the humoral immune response . The cell-mediated immune response induced by immunization was initially assessed by the IDR for the leishmanial antigen , a strong correlate for protection against human and animal VL that was higher in vaccinated animals than in controls prior to ( Figure 3A ) and after challenge ( Figure 3B ) ( p<0 . 0001 in both cases ) . After immunization , the F3sap vaccine induced the highest footpad swelling ( p<0 . 05 ) , followed by the NH36sap ( p<0 . 05 ) ( Figure 3A ) . After challenge , the IDR responses were enhanced ( p<0 . 0001 ) mainly by the NH36sap which was as potent as the F3sap vaccine ( p>0 . 05 ) at 24 h after injection ( Figure 3B ) . The preponderance of the F3sap vaccine was recovered ( p<0 . 05 ) 48 h after injection and its best immunogenic properties confirmed ( Figure 3B ) . The proportions of anti-NH36-specific CD4+ and CD8+ lymphocytes in spleens were analyzed by FACS ( fluorescence activated cell sorting ) ( Figure 4A and B ) . After immunization , the splenic CD4+ T cell proportions ( Figure 4A ) remained unaltered . After challenge , on the other hand , the F3 , F1 and NH36 sap vaccines showed CD4+ T cell proportions increased compared to the saline controls ( p<0 . 05 ) and the F2sap vaccine ( p<0 . 05 ) . The best performance was achieved by the F3 vaccine with higher proportions of CD4+ T cells than the NH36 vaccine ( p<0 . 05 ) . Of note and as expected due to the progress of VL , after challenge , the CD4+T cell proportions were decreased in saline controls ( 22% , p<0 . 05 ) ( Figure 4A ) . The CD8+ T cell proportions ( Figure 4B ) that remained unaltered after immunization were , on the other hand , increased by all vaccine treatments after infection ( p<0 . 0001 ) compared to their respective values before infection ( p<0 . 05 ) and to the saline control ( p<0 . 05 ) ( Figure 4B ) . The levels of cytokines were measured in supernatants of lymphocytes upon in vitro stimulation with recombinant NH36 ( Table 2 ) . After immunization , and compared to the saline controls ( IC95%–1 . 27 to 9 . 20 ηg/ml ) , higher concentrations of IFN-γ were detected only in the NH36sap vaccinated mice ( mean = 20 . 61 ηg/ml ) . After infection on the other hand , the F1 ( mean = 12 . 35 ηg/ml ) , F2 ( mean = 9 . 30 ηg/ml ) and F3 ( mean = 21 . 84 ηg/ml ) vaccines were superior to saline controls ( IC95%–1 . 65 to 8 . 10 ηg/ml ) and the F1sap and F3sap vaccine showed higher IFN-γ levels than the NH36sap vaccine ( 0 . 08–11 . 11 ηg/ml ) ( Table 2 ) . As detected for IFN-γ , the TNF-α levels after immunization ( Table 2 ) only increased in the supernatants of NH36sap treated mice ( mean = 114 . 77 pg/ml ) when compared to the saline injected controls ( IC95%–9 . 20 to 87 . 88 ηg/ml ) . After infection , the TNF-α secretion which correlates to the IFN-γ secretion ( p<0 . 0001 ) also showed the highest values in the F3sap and F1sap vaccinated individuals ( 447 . 44 pg/ml and 431 . 40 pg/ml , respectively , not shown ) . This experiment was the only one in the whole investigation in which neither the ANOVA-Tukey's HSD nor the Kruskall Wallis-Mann Whitney tests disclosed any significant differences . For this reason we used the IC95% for analysis . The expressions of IFN-γ , TNF-α and IL-10 were also studied by the ICS ( intracellular cytokine staining ) approach . In order to characterize the potential TH1 response generated by vaccination with the NH36 peptides we show the results as ratios of IFN-γ/IL-10 and TNF-α/IL-10 CD4+ and CD8+ producing cells ( Figure 5 ) . Our analysis disclosed the predominance of the F3 domain of the Nucleoside hydrolase which induced the highest TH1 response after immunization , which was sustained after challenge . Indeed , after immunization , the ratios of IFN-γ/IL-10 CD4 producing cells increased significantly ( p<0 . 009 ) mainly in F3sap vaccinated mice compared to those of mice vaccinated with F2sap ( p<0 . 05 ) while no differences were found in CD8+ T cells . After challenge , the ratios of IFN-γ/IL-10 CD4+ T cells also showed significant increases ( p<0 . 0001 ) . The F3sap vaccinated mice showed a 65% increase compared to saline controls and enhancements compared to all other vaccines ( p<0 . 05 ) except for the F1sap which itself showed a 32% increase over saline controls ( p<0 . 05 ) . The CD8+ IFN-γ/IL-10 producing cells also showed differences ( p<0 . 031 ) mainly due to the increase in F3 vaccinated mice ( p<0 . 05 ) ( Figure 5 ) . Furthermore , the TNF-α/IL-10 CD4+ response after challenge was stronger than the IFN-γ/IL-10 CD4+ response ( p<0 . 0001 ) . Indeed , the TNF-α/IL-10 CD4+ ratios of the F3sap vaccinated mice showed a 29% increase compared to the IFN-γ/IL-10 CD4+ ratios for the same group ( p<0 . 0001 ) . Also , different from what detected for IFN-γ , both the NH36 and the F3sap vaccinated mice showed TNF-α/IL-10 CD4+ ratios higher than those of saline controls , F2 and F1 vaccinated animals ( p<0 . 05 ) . Additionally the F3 vaccine ratio was 22% greater than that of the NH36 vaccine ( p<0 . 05 ) ( Figure 5 ) . Finally , the TNF-α/IL-10 CD8+ producing cells were only increased in the F3 vaccinated mice ( p<0 . 05 ) . Our results indicate that the response induced by the F3 peptide ( C-terminal domain ) overcomes the one induced by the cognate NH36 protein suggesting that it holds the main NH36 sequences responsible for the TH1 immune response . The TNF-α/IL-10 ratio also suggests , in the F3 sequence , the presence of more epitopes interacting with CD4+ than with CD8+ T cells ( the mean of CD4 = 1 . 71 falls outside the IC95% of CD8 = 1 . 12–1 . 62 ) . This is not the case for the NH36sap vaccine which stimulates similar proportions of both subsets of T cells ( the mean of CD4 = 1 . 3 is included in the IC95% of CD8 = 1 . 02–1 . 54 ) . The in vivo depletion assay with anti-CD4+ and anti-CD8+ monoclonal antibodies ( Figure 6 ) on mice immunized with NH36sap and F3sap vaccines confirmed the results of ICS . When compared to the saline control ( mean = 1402 . 9 LDU ) a 90 . 5% reduction was obtained with the F3sap vaccine ( mean = 132 . 56 LDU ) ( Figure 6B ) while only 65% was obtained after vaccination with the NH36 sap vaccine ( mean = 478 . 95 LDU ) ( p<0 . 05 ) ( Figure 6A ) , indicating that the F3sap vaccine induced a 25 . 2% increase in protective efficacy against mice VL . In correlation to what was detected for the TNF-α/IL-10 ratios after infection ( Figure 5 ) , in NH36sap vaccinated mice , the anti-CD4+ treatment induced 59 . 5% , and the anti-CD8+ , 52% of the total LDU counts of mice treated with both antibodies simultaneously , indicating a similar degree of contribution of CD4+ and CD8+ T cells ( Figure 6A; p>0 . 05 ) to the vaccine induced protection . Also in correlation with the results of TNF-α/IL-10 ratios ( Figure 5 ) , protection due to the F3sap vaccine was mainly mediated by the CD4+ T cells ( p<0 . 05 ) with a lesser contribution by CD8+ cells , since treatment with anti-CD4+ or antiCD8+ antibodies led to increases in susceptibility of 59 . 0% and 29 . 5% , respectively ( Figure 6B ) . Coincidentally , enhanced liver/body relative weight ( hepatomegaly ) , was promoted in NH36 vaccinated mice treated with anti-CD4+ MAb or anti-CD4+ plus anti CD8 + Mabs together ( Figure 6C ) and in the F3sap vaccinated mice treated with anti-CD4+ antibodies alone ( Figure 6D ) . These results confirm that while the NH36sap global protection is mediated by CD4+ and CD8+ lymphocytes , the contribution to immune response of the F3 protein is mainly mediated by CD4+ T cells with a minor contribution of CD8+ T cells . Regarding the parasitological assessment of infection and as expected from the results of the humoral and cellular immune responses , significant differences were found ( p = 0 . 011 ) and the F3 vaccine induced the highest efficacy with a 88 . 23% parasite load reduction ( p<0 . 05 ) ( Figure 7 ) . The reduction due to F3 vaccine was not significantly different from that due to the NH36 vaccine ( 37 . 06% ) , which in spite of that , exhibited more than 1000 LDU in 2 of 6 vaccinated mice ( Figure 7 ) . The F3sap vaccine also induced a 20 . 9% reduction ( p<0 . 05 ) of the liver/body relative weight ( not shown ) . The F1 vaccine , on the other hand , did not provide protection ( Figure 7 ) in spite of the results of the antibody , FACS , ICS and cytokine analyses . Epitope prediction programs disclosed three H2-Ld peptide nonamers for CD8+ lymphocytes in NH36 ( Figure 2 ) . The YPPEFKTKL CD8+ epitope is located in F1 fragment and the SPVAEFNVF and DPEAAHIVF epitopes in the F2 fragment . Among the epitopes for CD4+ lymphocytes , the peptides ELLAITTVVGNQ ( IAd allele ) and FRYPRPKHCHTQ ( IEd allele ) with the highest predicted affinity , are located in F1 and F3 , respectively ( Figure 2 ) while two peptides with lower affinity are located in F3 , one in F1 and one in F2 . Aiming to identify the NH36 domain responsible for the NH36 cross-protection to other infections caused by Leishmania species [14] , [16] , [17] , we also assayed the protective efficacy of NH36 and its fragments in the TL model . Vaccinated mice were challenged with infective L amazonesis promastigotes on their footpads . Significant differences in footpad sizes were detected until week 6 after infection ( p<0 . 0001 ) ( Figure 8A ) . The NH36sap , F1sap and F3sap vaccines reduced lesion sizes in comparison to the F2sap vaccine ( p<0 . 05 ) and to the saline treated controls ( p<0 . 05 ) . Furthermore , the parasite load evaluation in footpad lesions coming from Leishmania amazonensis DNA dosage by Real Time PCR performed on week 6 after infection , disclosed , in agreement to what has already been described for protection against L . chagasi ( Figures 6 and 7 ) that only the F3 fragment ( C-terminal domain ) was effective against L . amazonensis infection ( Figure 8B ) . Indeed , significant differences were found in the parasite load ( p = 0 . 039 ) . Despite the spontaneous negativation of 5 of the 10 untreated controls , the F3sap vaccine significantly reduced the parasite load to zero in all mice promoting 100% reduction of parasite load ( p<0 . 05 ) when compared to the untreated controls ( mean = 9 . 87 promastigotes ) and to the F2 vaccinated mice ( mean = 42 . 6 promastigotes ) . In both the VL and TL models , the C-terminal domain of NH36 ( F3 ) is the main target of the immunity and protective efficacy against the pathogen infection with a minor immunogenic contribution detected in the N-terminal domain ( F1 ) . Although in some variables ( anti-NH36 antibodies , ratio of TNF-α/IL-10 CD4 producing cells , footpad swelling in vaccination against L . amazonensis ) no significant differences were found between the effects of the NH36 and the F3sap vaccines , in many others , the superiority of the F3 over the NH36 vaccine was evident . We calculated the increment in the immunoprotective effect of the F3 vaccine taking in consideration all the variables that showed significant differences between the two formulations ( Table 3 ) . We found that the F3 vaccine developed a 36 . 73% higher average protective effect than the NH36 vaccine . Furthermore , the possible long-term protection generated by the F3sap vaccine was assayed in Balb/c mice submitted to 3 weekly interval vaccinations with either F1 , F2 or F3 peptides in saponin formulations and challenged , 4 weeks after completing all vaccinations . The results of parasite load evaluation are summarized in Figure 9 and disclosed a 97 . 5% level of protection generated only by the F3 vaccine compared to the saline controls ( p<0 . 05 ) and the F2sap vaccine ( p<0 . 01 ) revealing that the C-terminal domain of NH36 includes the epitopes of the Nucleoside hydrolase NH36 involved in the induction of long-term protection against VL .
Our study has disclosed very reliable information about immunoprotection against VL . As expected for the protection generation , significant inverse correlations were found between the decrease of both liver LDU and liver/body relative weight and the increases of IDR ( −p = 0 . 049 ) and ratios of TNF-α/IL-10 CD4+ producing cells ( −p = 0 . 014 ) . Accordingly , we demonstrated that the F3 peptide vaccine was capable of increasing the IDR and the ratios of TNF-α/IL-10 CD4+ T cells and of decreasing the parasite load and hepatomegaly . Thus , in our model and confirming previous results [36]–[43] , the increase of IDR and the ratio of TNF-α-CD4+ producing cells are the immunological parameters correlated with protection against VL . Also similar to what has already been reported [44] , [45] the ratios of IFN-γ/IL-10 producing CD4 T cells were not correlated to the decrease of LDU or hepatomegaly ( p>0 . 05 ) , but were correlated to the increase of IDR , CD4+ T cells and IgG , IgG2a and IgG2b antibodies ( p<0 . 023 for all variables ) . Therefore , in our model , the increase in IFN-γ producing cells was not a correlate for protection and the F1 vaccine which indeed promoted these increases did not give protection . The epitope prediction programs disclosed the CD8+ epitope YPPEFKTKL in F1 and the SPVAEFNVF and DPEAAHIVF CD8+ epitopes in F2 while no CD8+ epitope was found in the F3 fragment . In agreement to that , the ICS and in vivo depletion assays disclosed that protection generated by the F3 vaccine is predominantly mediated by CD4+ T cells , suggesting that the CD8+ stimulating activity of the NH36 vaccine is related to those epitopes located in the F1 and/or F2 sequences . Furthermore , the epitopes with the highest predicted affinity for CD4+ lymphocytes , are located in F1 and F3 , while the two lower affinity CD4 peptides are located in F3 . Epitope prediction therefore , suggested the strongest capability of F3 for CD4+ T cell mediated protection and antibody synthesis . After challenge , and as described before [28] increased levels of IFN-γ and TNF-α were secreted by mice vaccinated with F1 and F3 peptides but not with the NH36 protein . Our results correlate to the presence of 3 important CD4+ T cell epitopes in F3 . They correspond to a sequence of 14 , 12 and 14 amino acids , respectively , making a 40 amino acid potent sequence . For each vaccine dose containing NH36 ( 314 amino acids ) these 40 amino acids represent only 12 . 7% of the main active component . On the other hand , they represent a 34 . 8% of the 115 amino acid sequence of peptide F3 meaning that the F3 vaccine has a 2 . 7 enrichment of the main active component . This might explain the earlier induction of IFN-γ and TNF-α by F3sap vaccine , its strongest efficacy ( 88–90 . 55% of reduction of parasite load ) and the lower potential of the NH36 vaccine for generation of DTH , IFN-γ/IL-10 ratio of CD4+ and CD8+ T cells as well as the reduction of hepatomegaly and parasite load detected in this ( 37 . 06% and 65 . 90% ) and in previous investigations ( 67 . 80–79 . 00% ) , respectively [14] , [25] . There is an increase also in the ratio of TNFα/IL-10 but not of IFN-γ/IL-10 CD4+ producing cells in NH36 vaccinated mice after challenge that was not detected by the cytokine ELISA assay . This might be due to the higher sensitivity of the ICS technique . Another possible reason for that would be the sequence of events involved in the CD4+ T cell differentiation [46] . TNF-α is considered to be the most ubiquitous cytokine and it is produced by most activated CD4+ T cells [reviewed in 46] generated under conditions that favor TH1-cell differentiation . It proved to be important in protection against VL [36]–[43] . Optimal protection would be achieved by having a population of multifunctional T cells that can mediate an effector function quickly and have a reservoir of memory T cells that secrete IL-2 , TNF-α or both . Once CD4+ T cells have developed into IFN+-TNF+-IL-2+ T cells they have three potential fates: they can persist as memory or effector T cells , they can further differentiate into less functional T cells or they can die following activation [46] . The model for effector and memory CD4+ T-cell differentiation of Seder [46] involves the earliest secretion of TNF-α followed by IL-2 , by TNF-α and IL-2 and by the later IFN-γ-TNF-α-IL-2 secretion in CD4+ cells that can persist as memory or effector T cells . The finding of TNF-α producing cells in mice vaccinated with NH36sap and challenged could indicate the existence of an early effector cell-response generated by the vaccine . On the other hand , mice vaccinated with the F3 peptide that contains a higher density of the immunoprotective epitopes show a more advanced stage of CD4+ T cell differentiation with a more intense and suggestive combined secretion of IFN-γ and TNF-α that indicates the optimized effector function of CD4 T cells and the potential generation of long-term memory T cells . Therefore , our results might indicate the presence of an early TNF-α secreting response by CD4+ T cells of mice vaccinated with the less potent NH36 vaccine and the presence of single-TNF-α and/or double TNF-α-IFN-γ producers in mice vaccinated with the most potent F3 fragment . The percents of cell producing IFN-γ or potential double TNF-α-IFN-γ producers are much lower in NH36 mice and yet not significantly different from the saline control . In agreement with the results of ICS , the ELISA assay of splenocyte supernatants after infection , which probably correspond to multiple different cells , shows that the F3 , not the NH36 , induced an increase in IFN-γ secretion . In our study the ICS was carried out by the independent labeling of the T cell populations secreting IFN-γ , TNF-α and IL-10 and not by multiparameter cytometry . In order to establish if the increase in TNF-α and IFN-γ producing T cells caused by the F3 vaccination treatment is due to TH1 multifunctional T cell differentiation [46] , [47] or if it is the result of the secretion by distinct independent T cells , a further multiparameter cytometry analysis will be necessary . Our preliminary experimental results of mice challenged one month after vaccination however suggest the existence of memory T cells and the induction of long-term protection by F3 vaccine . Indeed , 97 . 5% of parasite load reduction was detected disclosing that the vaccine is able to generate both effector and memory T cells responsible for the immunoprotective response . Further experiments with challenges performed after one month of complete vaccination should bring relevant information on the extension of the long-term protection generated by the F3 fragment . Vaccines eliciting a high frequency of single-positive IFN-γ producing cells may be limited in their ability to provide durable protection [46] , [47] . Most vaccine studies for infections requiring TH1 responses measure the frequency of IFN-γ producing cells as the primary immune correlate of protection . Although IFN-γ is clearly necessary , using it as a single immune parameter may not always be sufficient to predict protection [47] . TNF-α is another effector cytokine that can mediate control of intracellular infections . Indeed , IFN-γ and TNF-α synergize in their capacity to mediate killing of pathogens [47] . As described in our investigation for the F3 vaccine mediated protection against L . chagasi , Darrah et al . [47] reported that vaccine-elicited protection against L . major was completely abrogated upon depletion of CD4+ T cells . Also , depletion of IFN-γ or TNF-α at the time of infection abolished vaccine mediated protection [47] . The total frequency of antigen-specific IFN-γ+ cells was not predictive of vaccine-elicited protection . In contrast , the analysis showed a correlation between the frequency of multifunctional ( IFN-γ , IL-2 and TNF-α triple-positive ) CD4+ T cells and the degree of protection [47] . In our investigation , the analysis of the cell-mediated immune response confirmed the epitope prediction analysis indicating that protection induced by NH36 vaccine is mediated by equal proportions of CD4+ and CD8+ T cells and it is even extended by protection generated by F3 vaccine which is mediated predominantly by CD4+ with a minor contribution by CD8+ T cells . This is an outstanding property of the C-terminal domain of NH36 considering the difficulties to obtain CD4+ mediated immune protection against protozoa infections [30] . The CD8+ T cell contribution of the NH36 vaccine might be related to the CD8+ epitopes predicted for the F1 sequence . NH36 is a strong phylogenetic marker for the Leishmania genus [1] , [2] and the finding of 93–99% of homology between the NHs amino acid sequences of L . donovani , L . major [7] , L . chagasi , L . infantum , L . mexicana , L . amazonensis and L . tropica [7] , [13] explains the previously detected cross-protection [14] , [16] , [17] . Vaccination with NH36 of L . donovani promoted an 88% reduction of the L . chagasi parasite load [14] and induced a 65% , 80 . 4% and 97% reduction of the skin lesion sizes or parasite loads of mice with tegumentary leishmaniasis by L . mexicana [14] , L . amazonensis [16] and L . major [17] , respectively . We showed that while reduction of the lesion size due to L . amazonensis infection was promoted by immunization with either the F1 or F3 of NH36 , in agreement with our findings on modulation of infection by L . chagasi , the reduction of parasite load was only determined by the F3sap . The increase in size of infected footpads is a specific measure of the progress of infection since the normal increase of footpad size with corporal growth is subtracted . It might be argued that the lesion size might also be influenced by the amount and nature of the local inflammatory response [48] which might be mediated by the B2R receptor for the released bradykinin at the local of infection [49] . In Swiss and C57BL/6 mice infected with L . amazonensis , the histopatological primary footpad lesion analysis showed liquefactive necrosis and inflammatory infiltrate mainly consisting of macrophages filled with amastigotes and rare lymphocytes [48] . Interestingly , the study of the dermal ear infection with L . amazonensis in C57Bl/6 mice showed that the absence of the TLR2 receptor determined the reduction of both the parasite load and the recruitment of inflammatory cells [50] . On the other hand , the generation of an inflammatory response is expected to determine a bradykinin-mediated partial protection of mice vaccinated against leishmaniasis using a saponin adjuvant [Nico D , Souza LOP , de Almeida LN , Monteiro ACS , Scharfstein J , et al . , unpublished results] . In spite of those evidences , in the present investigation , the footpad sizes were significantly diminished only by vaccination treatment with NH36 , F1 and F3 and saponin but not with F2-saponin or saline indicating that the sustained small footpad sizes are more related to the protection generated towards the antigenic sequences used for vaccination than to the inflammatory response generated by the Leishmania infective challenge or by the saponin adjuvant . In this investigation , the RTPCR although sensitive enough for dog diagnosis [35] generated results that were not directly related to the increase of the whole footpad lesions ( Pearson correlation coefficient , p = 0 . 726 ) . While all control animals developed footpad lesions ( mean+ SE = 0 . 008+0 . 0036 ) only 5 out of 10 showed parasites . In our model , the footpad swelling detected the protective contribution of the F1 and F3 vaccines while the RTPCR disclosed only the most potent F3 peptide as the main domain of NH36 involved in generation of immunoprotection . Both results were significantly different from controls and are in agreement with the results obtained in the vaccination against L . chagasi infection confirming the C-domain of NH36 as the one containing the more important epitopes of potential cross-protection . The finding of few parasites in footpads might be related to the lower infective challenge used in this work . We used 105 infective promastigote of L . amazonensis , as Al Wabel et al . did for Balb/c vaccination with recombinant NH36 against L . major infection [17] . Coelho et al . [51] , on the other hand , used 106 L . amazonensis infective promastigotes and obtained more enhanced increases of Balb/c footpads . The use of a higher inoculum would probably also determine an increase of the parasite load in our model . However , it is worth noting that in our investigation , although using a lower challenge , significant differences concerning protection were found . Similar to what described by Kao et al . for the P . aeruginosa Type IV pilus vaccine [29] the superiority of the F3 vaccine over the NH36 cognate protein vaccine is evident by the 36 . 73% average increase in IDR , IFN-γ/IL-10 CD4 T cells and reduction of L . chagasi and L . amazonensis parasite load . This is probably related to the 2 . 7 enrichment in the important epitope sequences which represent 34% of the F3 peptide . Vaccine protection could be further improved by the generation of shorter recombinant peptides of the F3 fragment composed only of the combination of the most relevant epitopes ( research in progress ) . The F1sap vaccine induced lower levels of antibody response that was not inhibited by the synthetic predicted peptides . The F2 vaccine , on the other hand , showed the worst performance of the three fragments tested . It showed the lowest inhibition of binding assay and was only able to increase the anti-NH36 IgG2b and IgG1 antibodies to the same extent as the other vaccines . This increase seems to be related to specific properties of the QS21 saponin-containing adjuvant [52] since no other antibody enhancements were detected after vaccination with F2 . After challenge , the levels of IgG1 antibodies were reduced in vaccinated mice but increased in controls indicating that protection against the VL-TH2 expansion was achieved by all vaccines despite the typical TH1/TH2 mixed response expected for the use of saponin adjuvant [52] . The IgM response was also reduced after challenge confirming the establishment of a secondary IgG antibody immune response . Despite the many antigens tested for vaccination in laboratory models [53] only two other formulations are under analysis as tentative synthetic vaccines against Leishmania [54] , [55] . Thirty overlapping 9-mer peptides of the kmp-11 protein of L . donovani trigger IFN-γ secretion by human CD8+ T cells and contain many potential HLA class I-restricted T cell epitopes that can be presented by different HLA molecules [54] . The other formulation is the polyprotein Leish110f composed of the TSA , LmSTI1 and LeIF candidates fused in tandem induced mice protection mediated by CD4+ T cells with a higher secretion of TNF-α followed by IFN-γ and IL-2 [55] . To our knowledge the description of the C-terminal domain of the NH36 antigen as the main active component in protection against leishmaniasis constitutes the first case of a licensed vaccine to evolve to a DNA , to a recombinant defined protein formulation and then progress to a synthetic vaccine . Our findings contribute to the potential development of synthetic vaccine formulations against parasites of the Leishmania genus and against multiple microorganisms which have NHs in their replication pathways .
|
The continued spread , morbidity and mortality of human leishmaniasis together with the emergence of drug-resistant variants , the failure of epidemiological control based on dog culling and insecticide vector control and the chemotherapy toxicity have spurred attempts to develop an effective vaccine . Leishmaniasis affects 12 million people and another 350 million live under risk worldwide . We developed the first licensed second generation vaccine against leishmaniasis , a canine vaccine that has already reduced the incidence of the human and canine disease in endemic areas . Its main component is the Nucleoside hydrolase of Leishmania donovani ( NH36 ) which in its recombinant and DNA formulation is cross protective against agents of tegumentary leishmaniasis ( TL ) . For this work we generated three recombinant peptides covering the NH36 sequence and identified the C-domain of the Nucleoside hydrolase as being responsible for its immunogenicity and vaccine-induced protective efficacy against VL and also for the reduction of lesion size and parasite load against TL . Since all Leishmanias species share high identity in their Nucleoside hydrolases amino acid sequences , our study represents a major step forward in the development of a bivalent synthetic vaccine against leishmaniasis and a potential future multivalent vaccine against pathogens that are dependent on NHs for replication .
|
[
"Abstract",
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"Material",
"and",
"Methods",
"Results",
"Discussion"
] |
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"biotechnology",
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2010
|
Adaptive Immunity against Leishmania Nucleoside Hydrolase Maps Its C-Terminal Domain as the Target of the CD4+ T Cell–Driven Protective Response
|
Researchers have long been enthralled with the idea that gene duplication can generate novel functions , crediting this process with great evolutionary importance . Empirical data shows that whole-genome duplications ( WGDs ) are more likely to be retained than small-scale duplications ( SSDs ) , though their relative contribution to the functional fate of duplicates remains unexplored . Using the map of genetic interactions and the re-sequencing of 27 Saccharomyces cerevisiae genomes evolving for 2 , 200 generations we show that SSD-duplicates lead to neo-functionalization while WGD-duplicates partition ancestral functions . This conclusion is supported by: ( a ) SSD-duplicates establish more genetic interactions than singletons and WGD-duplicates; ( b ) SSD-duplicates copies share more interaction-partners than WGD-duplicates copies; ( c ) WGD-duplicates interaction partners are more functionally related than SSD-duplicates partners; ( d ) SSD-duplicates gene copies are more functionally divergent from one another , while keeping more overlapping functions , and diverge in their sub-cellular locations more than WGD-duplicates copies; and ( e ) SSD-duplicates complement their functions to a greater extent than WGD–duplicates . We propose a novel model that uncovers the complexity of evolution after gene duplication .
The mechanisms underlying the emergence of novel functions in nature remain a mystery . Gene duplication is believed to be the primary source of new genes and functions and has consequently been credited with great evolutionary importance [1] . Our knowledge on the importance of duplication in functional innovation is impressive , yet our ability to model the functional fate of duplicated genes is highly limited . A number of studies have attempted to establish a causal link between gene duplication and the emergence of major evolutionary innovations . For example , most Angiosperms have undergone at least one genome duplication ( polyploidy ) [2] , [3] in the Creataceous era , contemporary with the explosion of plant metabolic and physiological diversity [4] , [5] . This diversity resulted from the expansion of protein families by gene duplication , including pepsin- and subtilisin-like proteases [6] , metacaspases [7] , regulatory genes [8] and developmentally important MADS-Box genes [9] , [10] , [11] , [12] . In animals , although much rarer , gene duplications have preceeded the appearence of key developmental features and were concomitant with major events of species diversification [13] , [14] . It is tempting to establish a link between gene duplication and biological complexity , but the mechanisms underlying the persistence of genes in duplicate and determining their functional fate remain largely obscure . Population genetics theory predicts that most duplicated genes return to single copies “shortly” after duplication because an entirely redundant duplicate will fix deleterious mutations and undergo decay and erosion after duplication [1] , [15] , [16] . Following this prediction , genes will persist in duplicate in the genome if: ( i ) gene duplication , hence redundancy , endows organisms with mutational robustness [17]; ( ii ) there is selection for increased gene dosage [18]; or ( iii ) gene duplicates have diverged functionally through the partitioning of the ancestral gene functions [19] , [20] , [21] , thereby generating entirely new functions [22] , or have diverged in their expression profiles [23] . Because gene dosage is immediately unbalanced after duplication , other factors or mechanisms should counterbalance such a constraint to mediate the persistence of genes in duplicate [24] , [25] . These mechanisms remain hitherto a major question in molecular evolution [16] , [18] , [26] . The mode of gene duplication ( WGD or SSD ) has been proposed to have a key role in the fate of duplicated genes [27] ( although see [28] for the role of species ecology in the functional fate of duplicates ) , with WGDs being more likely to persist than SSDs , as the former does not upset the stoichiometric balance in the cell [24] , [25] , [29] , [30] . Long-term survival of WGDs in the genome can offer opportunities to generate novel functions , albeit this is constrained by gene dosage balance . Therefore , whether genes and their products resulting from both WGD and SSD are subject to the same evolutionary constraints and have similar potential to generate novel functions is unclear . Typically , events of functional divergence between duplicated genes can be inferred using evolutionary parameters , assuming that when the protein sequences of duplicates are more divergent so are their functions [31] , [32] , [33] . However , determining whether two copies of a duplicated gene have identical , similar or different functions requires the concerted and careful examination of the function of each gene product . While this approach is useful at a single gene level , genome-scale analyses of functional divergence between gene duplicates are unfeasible on a gene-by-gene basis . Alternatively , high-throughput methods , such as genetic interactions screening [34] , yeast two-hybrid screening [35] , [36] , [37] , [38] , [39] and analysis of protein complexes by mass spectrometry [40] , [41] , [42] , [43] provide substantial information that can aid in testing the roles of WGD and SSD in innovation . Using such high-throughput information , several authors have contributed to the understanding of the role of the modes of gene duplication in the functional divergence of duplicated genes . For example , Wagner analyzed the number of shared interactions between duplicated genes in a network as a crude measure of their functional overlap [44] . Analysis of various types of networks on a large scale led Conant and Wolfe [45] to the observation of asymmetry and partitioning of genetic interactions ( sub-functionalization ) between the daughters of genes after WGD in the yeast S . cerevisiae . The different contribution of WGD and SSD to functional divergence was also pointed out in another study using information on protein interactions [46] . Finally , Hakes and colleagues [25] used protein interactions and Gene Ontology ( GO ) annotations as proxies for protein function to show that functional divergence between SSDs is greater than between WGDs , WGDs produce less deleterious effects when deleted and WGDs are usually part of the same protein complexes . Recently , Costanzo and colleagues [34] , [47] have constructed a functional map that includes the genetic interaction profiles ( epistasis ) for approximately 75% of the genes in S . cerevisiae . Two genes are considered to interact when the phenotypic effect of a variant of one gene is aggravated ( synergistic or negative epistasis ) or alleviated ( antagonistic or positive epistasis ) by variation in the second gene [48] . In the extreme , these combinations can lead to synthetic lethality in which mutation of a single gene , although having little or no effect on the cell in isolation , results in cell death when combined with a mutation in a second gene [49] , [50] . These interaction profiles provide a means to identify functional relationships between duplicated genes . Accordingly , VanderSluis and colleagues [51] used genetic interaction profiles to demonstrate that duplicated genes can be functionally redundant , show subtle functional differences , their persistence depends on their dosage and gene copies can show asymmetry in their interaction profiles . Moreover , Jiang and colleagues [52] unearthed the role of gene duplication in the evolution of genetic interaction networks and in mediating functional diversification of the interaction partners of a duplicate . Despite their insightful findings , a model that describes the contribution of the mode of gene duplication to innovation is lacking . More precisely , the different propensities of WGDs and SSDs to generate novel functions that depart from the ancestral ones remain to be inferred . We used the genetic interaction dataset of Costanzo and colleagues and a large-scale evolution experiment across which we examined mutational dynamics in duplicated genes formed by SSD and WGD . Exhaustive analysis of interaction profiles and genome-wide mutational dynamics allowed us to distinguish the role of WGD and SSD in the functional specialization of S . cerevisiae genes and shed light on the complexity of the dynamics of evolution by gene duplication . In particular , we show that: ( a ) SSDs establish more functions and have stronger epistatic effects in the cell than WGDs; ( b ) SSD is often followed by neo-functionalization while sub-functionalization is likely to follow WGD and ( c ) we propose and test a model that explain the role of the mechanism of duplication in the functional fate of duplicates .
Early theory predicts that after gene duplication both copies are functionally redundant and that one of the copies , devoid of selective pressures , degenerates towards non-functionalization in a neutral manner ( without consequences for the organism's fitness ) . We hypothesize that gene duplication immediately re-shapes the fitness landscape of genes and that the shape of the new landscape is dependent upon the mode of duplication . WGD maintains the stoichiometric balance of gene products ( Figure 1A ) and consequently leads to relaxed selective constraints on both gene copies . These relaxed constraints lead to a stochastic loss of genes so that both copies persist in the genome if the combination of their functional loss does not alter the ancestral function and this combination is not deleterious to the organism ( Figure 1A ) . Conversely , the gene copies formed by SSD persist in the genome if their products do not upset the stoichiometric balance ( Figure 1A ) or the positive effects on fitness owing to the genetic robustness provided by a second gene copy compensates negative fitness effects of dosage imbalance . The persistence of SSDs facilitates genetic robustness by maintaining overlap in the interaction ( function ) profiles of the gene copies while generating opportunity for the divergence of one gene copy and the acquisition of novel functions ( Figure 1B ) . In support of the determinant role of dosage balance in the retention of duplicates and that WGD maintains such a balance is that WGD-duplicated genes have rarely experienced subsequent SSD , they are refractory to copy number variation and WGD-duplicated genes are dosage sensitive , often leading to diseases in humans [29] . The partial or total functional complementation between duplicates reported in several previous studies support the role of genetic robustness in the persistence of duplicates [53] , [54] , [55] , [56] , [57] . Our model allows a number of predictions to be made: a ) SSDs should complement their function to a greater extent than WGDs; b ) SSDs should establish more genetic interactions ( GI ) than WGDs; c ) WGD-duplicated gene copies should partition ancestral functions ( sub-functionalize ) more readily than SSD-gene copies; d ) SSD-gene copies should share more interaction partners and establish more novel interactions ( neo-functionalization ) than WGD-gene copies and e ) the WGDs-interaction partners should be more functionally linked ( they should genetically interact between themselves ) than those of SSD-interaction partners as the interactions partners for both copies of a WGD should correspond to those of the ancestral pre-duplication gene . Two key studies present evidence supporting some of the predictions made in this model . The first study is that of Hakes and colleagues [25] , who , using protein-protein interaction data and functional similarities , showed that: ( a ) WGDs exhibit less severe phenotypic effects when deleted than SSDs; ( b ) WGDs diverged functionally to a lesser extent than SSDs; and ( c ) WGDs generally encode proteins of the same protein complex . This study however used protein-protein interactions as a proxy for functions , while in this study we focused on genetic interactions . The second study was that of VanderSluis et al . [51] which showed that WGDs show stronger negative interactions than SSDs , suggesting greater partitioning of ancestral functions for the former than for the latter . Previous work , using information contained within protein-protein interactions of S . cerevisiae , found that WGDs gene copies show more redundancy , and hence are less essential , than SSDs gene copies [25] . Also , VandersLuis et al . [51] examined the difference in the average number of genetic interactions between duplicates , but did not quantify the interactions , which is an important measure of gene redundancy . Here , we examined whether SSDs present more genetic interactions than WGDs and we measured the difference in the strength of interactions between WGDs and SSDs . We extracted the genetic interaction profiles ( 762 , 768 significant interactions with P<0 . 05 , according to Supplementary files S4 and S5 from http://drygin . ccbr . utoronto . ca/~costanzo2009/ ) for 4 , 464 S . cerevisiae genes , which included both singletons and duplicated genes . Of these 4 , 464 , we obtained genetic interaction profiles for 678 duplicated S . cerevisiae gene pairs ( 248 SSDs and 430 WGDs , Table S1 and Table S2 respectively; see Material and Methods ) . Of the 762 , 768 significant genetic interactions , 25 , 003 genetic interactions were established by genes that were in duplicate in the genome ( corresponding to the number of genetic interactions once we removed those cases for which the effects of double mutants were not statistically significant when compared to the multiplicative effects of single mutants , P>0 . 05 ) . The number of genetic interactions detected is slightly different from that detected in [51] , although is consistent with VanderSluis et al ( 2010 ) [51]: albeit we identified marginally less WGDs and marginally more SSDs . The reason for this difference is probably due to the cutoff value used in the BLAST analyses or differences in the methodology used for identity searching ( see Material and Methods ) . Nevertheless , the slight difference between the numbers of genes in both datasets does not affect the conclusions of this study , as on the whole both datasets are very similar . Moreover , we performed the analyses focusing on subsets including 80% of WGDs and SSDs and we were able to reproduce all the conclusions that were obtained in the full datasets ( data not shown ) . The conclusions therefore are very robust to changes in the size of the duplicates datasets . The functional map of Costanzo and colleagues [47] is based on the synthetic genetic array methodology [58] , in which synthetic lethal genetic interactions are systematically mapped by producing single and double mutants [59] . In their study , Costanzo and colleagues [47] identified digenic interactions as those double mutants that show a significant deviation in fitness compared to the multiplicative fitness effects of the two single mutants , that is , epistasis ( hereafter referred to as ε , with ε− referring to negative epistasis and ε+ to positive epistasis ) [60] . Defects were measured in terms of colony size . Using epistasis data we found that epistatic effects of duplicated genes with other genes in the genome were predominantly synergistic for duplicates formed by both SSD ( the mean effect of double mutant: = −0 . 013 ) and WGD ( = −0 . 007 ) , which is in agreement with previous studies [34] , [47] . On average , we identified more epistatic interactions for singleton genes ( = 342 . 970 ) than for WGDs ( = 324 . 420 ) ( Figure 2A ) , suggesting that the copies of WGDs specialized in interacting with a subset of the partners for their ancestral gene ( pre-duplication gene ) . Importantly , we found more genetic interactions for SSDs than for singletons ( = 412 . 461 ) ( Figure 2A ) , suggesting that SSDs have established novel genetic interactions after duplication . Moreover , we identified more epistatic interactions on average for SSDs than for WGDs ( t = 6 . 155; d . f . = 857 , 33; P = 1 , 153×10−9; Wilcoxon rank test: P = 3 , 465×10−9 , Figure 2A ) . These results are consistent with the hypothesis that each gene copy of SSDs preserved on average more ancestral interactions than WGDs and they have established novel interactions once they have specialized in a subset of the ancestral functions ( sub-functionalization followed by neo-functionalization , a model previously proposed [22] ) . However , another possibility is that WGDs may present greater redundancy than SSDs ( functional complementation is greater among WGDs ) which may buffer the genetic interactions in WGDs , a model proposed in a recent study [51] . To test this possibility , we divided the set of WGDs into bins according to the divergence between the protein sequences of gene copies . According to the buffering model , the mean number of genetic interactions should be lower for bins of low divergence levels ( more redundant gene copies ) and significantly lower than the mean number of interactions for SSDs . This difference should become significantly diluted at large divergence levels between WGDs . In no bin was this the case and , in fact , the bin with the lowest divergence level for WGDs was the one with the largest number of genetic interactions ( Figure 2B ) . This supports the fact that most duplicated genes in the WGD dataset are no longer redundant after evolving for 100 My [61] . This supports the conclusion that SSDs present more genetic interactions than WGDs and that this is not due to larger redundancy among WGDs . Because genes with a larger number of interactions should play , on average , a more fundamental role in the cell than those with fewer interactions , we tested whether the number and strength of positive and negative epistasis differred between SSDs and WGDs . Hakes et al . showed , using protein interaction data , that WGDs were more redundant than SSDs as deleting WGDs had less severe effects than deleting SSDs [25] suggesting that WGDs should present less epistasis than SSDs . In agreement with their results , SSDs presented more positive interactions ( = 181 . 26 ) with other genes in the genome than WGDs ( = 152 . 779; Wilcoxon rank test: P = 3 . 035×10−5 ) . Likewise , SSDs presented more negative epistasis ( = 231 , 201 ) than WGDs ( = 171 , 741 ) ( Wilcoxon rank test: P = 0 . 00034 ) . We tested whether SSDs duplicates establish stronger epistatic interactions than WGDs , that is , whether deleting a SSD duplicated gene member would have greater effect in combination with other gene deletions than deleting a WGD duplicate . The mean magnitude of positive epistasis for singletons ( = 0 . 060 ) was significantly larger than that for SSDs ( = 0 . 055 ) and WGDs ( = 0 . 052 ) ( Figure 2C ) . The trend was reproduced for negative epistasis: singletons presented stronger average magnitude of epistasis ( = −0 . 079 ) than WGDs ( = −0 . 062 ) and SSDs ( = −0 . 070 ) . This indicates that the genetic redundancy provided by gene duplication buffers the epistatic effects and points to functional complementation between duplicates . Importantly , SSDs showed stronger epistatic effects than WGDs ( = −0 . 013 , = −0 . 007; Student t test: t = 3 . 644 , d . f . = 1058 . 919 , P = 2 . 82×10−4 ) , and this trend was also true when examining both positive epistasis ( t = 4 . 033 , d . f . = 1058 . 803 , P = 5 . 889×10−5 ) and negative epistasis ( t = 5 . 469 , d . f . = 892 . 493 , P = 5 . 864×10−8 ) . These results suggest that interactions of SSDs are of greater significance for the cell , are more abundant than those of WGDs and point to greater specialization , probably sub-functionalization , of WGDs than SSDs . The second prediction of our model is that greater genetic redundancy ( for example , overlapping functions ) in SSDs can allow the generation of novel functions in these duplicated genes . That is , neo-functionalization requires the maintenance of genetic redundancy as a selection pressure to allow the persistence of the gene in duplicate in the genome . Under the model we propose , greater partitioning of ancestral functions among WGDs than SSDs is expected and it is predicted that SSD-gene copies should share more genetic partners than WGD-gene copies ( Figure 3 ) . Larger partner sharing among SSDs compared to WGDs may not apply to protein-protein interactions , as shown in Hakes and colleagues [25] , especially when duplicated proteins form part of the same complex . To test this prediction , we examined the divergence in the interaction profiles of the duplicates by estimating the proportion of shared genetic interactions ( Θ ) between the members ( i and j ) of a pair as:Here nS ( i , j ) refers to the number of genetic interactions that are shared between the two copies of a duplicated gene . Using the proportion of shared interactions for duplicates coming from either SSD or WGD , we tested whether generation of novel functions ( for example , establishment of novel genetic interactions ) was more likely to take place in SSDs while specialization ( sub-functionalization: specialization in interacting with a subset of ancestral gene partners ) is more likely in WGDs . To do this analysis , we removed from the SSD dataset all those pairs which presented lower sequence divergence than 95% of the WGDs as these were likely to be much younger duplicates and could lead to apparently lower partner sharing in SSDs than in WGDs . The proportion of shared interactions was larger for the members of a SSD duplicate than for those of a WGD duplicate when considering all types of interactions together ( = 0 . 127 , = 0 . 115 , t = 2 . 693 , d . f . = 514 . 33 , P = 0 . 0073 ) , positive epistatic interactions ( = 0 . 0622 , = 0 . 055 , t = 3 . 506 , d . f . = 573 . 76 , P = 0 . 0124 ) and negative epistatic interactions ( = 0 . 0708 , = 0 . 0616 , t = 2 . 810 , d . f . = 522 . 11 , P = 0 . 0051 ) . Importantly , while SSDs shared significantly more partners than expected from a distribution of shared interactions between randomly paired singletons , this was not the case for WGDs ( Figure 4 ) . This pattern was also true for all amino acid sequence divergence levels ( Figure 4 ) . Noticeably , when the sequence divergence between both gene copies was high , sharing of partners between them was more apparent , probably due to the lower redundancy ( more functional divergence ) having less effects on masking true interactions , as proposed by the buffering hypothesis of VanderSluis and colleagues [51] . The same results were obtained for positive and negative epistasis ( data not shown ) . These results further indicate that WGDs have partitioned ancestral functions to the point that each gene copy performs a unique subset of the ancestral functions , while this is not the case for SSDs . To detail the role of WGD and SSD in sub- and neo-functionalization , respectively , we compared the epistatic interactions between pairs formed by WGD to those originated by SSD taking into account only epistatic interactions between the copies of a duplicated gene . VanderSluis et al . [51] showed stronger epistasis for WGDs than for SSDs . Sub-functionalization would imply strong genetic interactions between the gene copies because both are needed to perform the ancestral , likely essential , function . Neo-functionalization , on the other hand , would require less interactions as one gene copy is almost entirely performing the ancestral function . If this hypothesis were true then we should expect more duplicates to interact epistatically between themselves in the set of WGDs than in the SSD set . In agreement with a previous study [51] , WGDs interacted more than SSDs . Copies of a duplicated gene interacted epistatically with each other in 19 . 8% of WGDs against 12 . 9% of SSDs , and the difference between these percentages was significant ( Fisher exact test: F = 1 . 6638 , P = 0 . 0095 ) . Also , sub-functionalization and neo-functionalization after WGD and SSD , respectively , implies that the strength of the interaction should be greater between the gene copies of the set of WGDs than in SSDs . In concert with this prediction , and in addition to the results provided by [51] , the epistatic interactions between only the members of a duplication were significantly stronger for WGDs than for SSDs ( = −0 . 222 , = −0 . 343; t = 2 . 234 , d . f . = 89 . 197 , P = 0 . 0279; Wilcoxon rank test: P = 0 . 017 ) . We could not confirm this result for positive and negative epistasis separately due to the lack of statistical power after classifying the types of interactions . Our model supports neo-functionalization to be more likely in SSDs than WGDs . Comparison of WGDs and SSDs in terms of sequence divergence showed that WGDs diverged less than SSDs in plants [28] . We compared sequence divergence between copies of duplicated genes in the SSD set to that of the WGD set . Neo-functionalization would require dramatic changes in the sequence to perform novel functions while sub-functionalization would subject both gene copies to similar selection pressures as they are required to perform the ancestral function—that is , both gene copies have been co-evolving . It has been previously suggested that both copies of a sub-functionalized duplicate would not be subject to similar selective pressures due to asymmetric partitioning of ancestral functions [22] . However , the difference in the number of functional regions between duplicates that have sub-functionalized is expected to be low . To test our hypothesis we measured the rate of amino acid divergence between gene copies i and j ( Di , j ) , using JTT corrected amino acid distances , for each duplicated gene of the SSD and WGD sets ( see material and methods ) . As predicted by our hypothesis , the divergence levels between duplicated genes were on average greater for the set of SSDs than for the WGDs set ( = 0 . 3082 , = 0 . 267 , t = 2 . 023 , d . f . = 580 . 218 , P = 0 . 04 ) . Because sequence divergence is a good indication of functional divergence [31] , [32] , [33] , [62] , particularly when divergence is measured between copies of a duplicated gene , the greater divergence between SSDs further suggests that SSDs have a more important role in generating novel functions than WGD and that WGDs co-evolve more than SSDs . This result also predicts that the interaction partners of WGDs should be more functionally related than those of SSDs , as they belonged to the set of interaction partners of a single gene pre-dating the WGD duplication event . This prediction was tested in a previous study by Hakes and colleagues [25] which showed using semantic distances between duplicates that WGDs are more functionally related than SSDs . To shed more light on the role of SSD and WGD in the functional specialization of duplicated genes , we examined the sub-cellular localization of gene copies formed by both mechanisms of duplication . We extracted information on the cellular localizations of S . cerevisiae duplicated genes from the Munich Information Centre for Protein Sequences using the Comprehensive Yeast Genome Database ( MIPS Saccharomyces cerevisiae genome database: http://mips . helmholtz-muenchen . de/genre/proj/yeast/singleGeneReport . html ? entry=yer175c ) [63] . We considered two gene copies to present different sub-cellular location if they either had non-overlapping cellular locations or the overlap was not complete . Gene copies localizing to different sub-cellular regions are likely to have developed different functions and vice versa . Different cellular localization of gene copies also buffers the stoichiometric imbalance caused by gene duplication . This hypothesis and our model , predict that SSD-duplicate gene copies will show less overlap in localization than WGD-duplicate gene copies . As predicted by our model , the number of gene copies resulting from SSD whose duplicate localized to different subcellular locations ( 330 gene copies corresponding to 165 out of 498 pairs ) was significantly larger than that of gene copies resulting from WGD ( 414; 207 out of 861 duplicates , Table S3 ) ( Fisher exact test: F = 2 . 12 , P = 7 . 163×10−11 ) . Interestingly , most SSDs overlapped to some degree in their sub-cellular locations , an important finding for the genetic robustness proposed in our model to explain the retention of SSDs . Another prediction of the proposed model is that SSD-duplicates partners should expand the repertoire of functions more readily than WGD-duplicates partners—that is , SSD-duplicates partners should be less functionally related and hence should interact less than WGD-duplicates partners . To test this prediction , we measured how related were the genes interacting with each copy of a duplicate . Sub-functionalization after duplication would lead to gene copies that interact with highly related functions . Neo-functionalization , on the other hand , would yield gene copies whose partners would be partially unrelated to the ancestral functions ( Figure 3 ) . We identified the genetic interactions between the partners of each gene copy . We then measured the clustering between these interaction partners with the assumption in mind that greater clustering involves greater functional relatedeness . We measured the clustering coefficient between the partners of a gene copy as the number of interactions established between these partners ( κ ) :with l being the number of links between the partners of a duplicated gene and p the number of partners of a duplicated gene . Large clustering coefficients ( for example , 0≪κ≤1 , Figure 5A ) implies that the partners of a duplicated gene are interacting more than expected by chance . We measured this clustering coefficient in two ways . First we estimated κ for singletons and for each gene copy of SSDs and WGDs individually . This yielded larger κ values for WGDs and SSDs than singletons ( Figure 5B ) . WGDs showed significantly larger κ values than SSDs ( Figure 5B ) . We next joined the set of interaction partners of both copies of a duplicated gene in one group and calculated κ for that group . In agreement with our prediction , κ values were significantly larger for WGDs than for SSDs sets ( = 0 . 022 , = 0 . 017 , t = 12 . 882 , d . f . = 646 . 436 , P<2 . 2×10−16 ) . These results , in combination with larger functional divergence and partners sharing between SSD-duplicate gene copies than WGD-duplicate gene copies points to larger partitioning of ancestral functions in WGDs than SSDs and greater neo-functionalization in SSDs . Our model and results suggest that the functional divergence between members of a WGD is constrained by the need to keep a balanced stoichiometry between duplicates from the same pathway or network , and by their co-evolution . Because of their greater genetic robustness , SSDs should be less constrained to evolve in the short term than WGDs . To test this hypothesis in real time , we evolved for approximately 2 , 200 generations 5 lines of S . cerevisiae , all of which derived from the same ancestral strain , ( 100 plate-to-plate passages of single colonies ) . To accelerate the mutation accumulation experiment , we used an msh2 deletion strain , which is deficient in mismatch repair ( MMR ) and therefore has an increased spontaneous mutation rate ( see Material and Methods for details ) . This experiment was designed to accumulate slightly-deleterious mutations , thereby testing functional complementation between WGDs compared to that of SSDs . If non-synonymous mutations were as deleterious when they originated in WGDs as in SSDs then we should observe no significant differences in the enrichment of SSDs and WGDs for non-synonymous SNPs . We sequenced the ancestral genome and the evolved genomes at 20 , 30 , 50 , 70 , 90 and 100 passages . These lines evolved under strong bottlenecks ( transferring a single colony to a fresh plate ) , leading to the fixation of mutations in all the yeast chromosomes ( figure 6A ) . Synonymous and non-synonymous SNPs accumulated linearly across the evolution experiment ( figure 6B ) , this being indicative of the effect of genetic drift on the fixation of mutations . Because of the clonal transfer nature of each line , genome-wide mutations at each isolation time ( t ) included those fixed in the previous isolation time ( t−1 ) . At the end of the experiment we detected a total of 883 SNPs across the 5 lines distributed throughout the genomes ( table S4 ) ( after filtration of ancestral SNPs ) . Of the 883 mutations , 249 were fixed in intergenic or intronic regions , while the remaining 634 mutations affected exons . There were 158 annotated synonymous mutations in addition to 399 annotated non-synonymous mutations affecting 386 different protein-coding genes . The number of non-synonymous mutations varied between the five evolving lines , ranging between 55 ( fixed in 52 protein-coding genes; approximately 0 . 9% of the total number of genes in the genome ) and 104 ( fixed in 103 protein-coding genes; approximately 1 . 8% of the total number of genes ) . If WGDs were under stronger constraints than SSDs then deleterious non-synonymous nucleotide polymorphisms ( Nsyn-SNPs ) should be less likely fixed at WGD than SSDs . In addition , SSDs should fix more Nsyn-SNPs than expected because of their greater genetic robustness , as predicted by our model . SSDs fixed more Nsyn-SNPs than WGDs in all five mutation accumulation ( MA ) experimental lines ( Figure 6C; 21 . 4% of SSDs fixed Nsyn-SNPs versus 16 . 5% of WGDs; Fisher exact test P = 0 . 024 ) . In four of the five MA lines , the fraction of SSDs fixing Nsyn-SNPs was significantly larger than that of WGDs ( Figure 6C ) . On average ( considering the five lines of experimental evolution ) , 21 . 4% of Non-synonymous SNPs were fixed in SSDs , against the expected value of 17 . 1% ( = 12 . 37 , P<0 . 025 ) . In contrast , only 16 . 5% of non-synonymous SNPs were fixed in WGDs against the expected value of 16 . 8% under the hypothesis of no functional complementation ( = 4 . 4 , P>0 . 1 ) . Although the protein sequence length for SSDs was slightly greater than WGDs , this was not a determining factor of whether a gene contained a Nsyn-SNP as WGDs encoded significantly larger proteins than singletons yet they accumulated similar numbers of Nsyn-SNPs . In conclusion , SSDs present greater mutational robustness than WGDs at short evolutionary time intervals , which may allow the fixation of innovative mutations despite their destabilizing effects and the rapid increase in the strength of selection constraints on these novel functions .
Our analyses on the distribution of functions and epistatic interactions among duplicates generated by WGD and SSD lead to the following conclusions: ( 1 ) SSDs show more complementary functions than WGDs , while being more essential than WGDs; ( 2 ) SSDs have established more epistatic interactions than singletons and WGDs , suggesting neo-functionalization after SSD; ( 3 ) WGDs have partitioned ancestral gene functions so that each gene copy performs a subset of the functions of the ancestral , pre-duplication , gene ( sub-functionalization ) ; ( 4 ) SSDs have diverged functionally more than WGDs , a fact consistent with larger functional innovations among SSDs than WGDs; ( 5 ) SSD provides more mutational robustness than WGD . We provide a mechanistic model to explain the functional fates of duplicates according to the mechanism of duplication .
We used the latest update of the genetic functional chart of S . cerevisiae [47] ( Supplementary files S4 and S5 from http://drygin . ccbr . utoronto . ca/~costanzo2009/ ) . This functional map is based on the synthetic genetic array methodology [58] , in which synthetic lethal genetic interactions are systematically mapped by producing single and double mutants [59] . In their study , Costanzo and colleagues [47] identified digenic interactions as those double mutants that show a significant deviation in fitness compared to the multiplicative fitness effects of the two single mutants , that is , epistasis ( ε ) [60] . Negative interactions ( ε− ) refer to those double mutants causing more severe defects than the multiplicative effects of the single mutants , with synthetic lethality being the extreme case . Positive interactions ( ε+ ) are those causing less consequence than the multiplicative effects of single mutants . Defects were measured in terms of colony sizes . The updated version of the double mutants data includes more than 6×106 binary genetic interactions ( GI ) . Paralogous pairs of duplicated genes were defined as the resulting best reciprocal hits from all-against-all BLAST-searches using BLASTP with an E-value cutoff of 1E-5 and a bit score cutoff of 50 [78] . Paralogs were further classified as ohnologs resulting from the whole genome duplication occurring in the yeast lineage 100–150 mya according to the reconciled list provided by the YGOB ( Yeast Gene Order Browser , http://wolfe . gen . tcd . ie/ygob/ ) [79] . All other paralogs were considered to belong to SSD events . Because SSD includes contemporaneous , older and younger duplicates than the WGD event , we corrected divergence levels of WGD and SSD normalizing them by the total divergence of the protein as follows:Here , divergence between the gene copies a and b is measured as the difference between the divergence of gene copy a and the sequence of the ancestral node ( anc ) of a and b , and that of the gene copy b and the ancestor , normalized by the sum of divergences . Effectively , the divergence of each gene copy to the ancestor corresponds to the length of the branch leading to that gene copy . To determine the position of the ancestor , we used as an outgroup sequence the ortholog for the duplicated gene in Kluyveromyces polysporus ( sequence c ) . Branch length for a gene copy a was estimated as:
|
Gene duplication involves the doubling of a gene , originating an identical gene copy . Early evolutionary theory predicted that , as one gene copy is performing the ancestral function , the other gene copy , devoid from strong selection constraints , could evolve exploring alternative functions . Because of its potential to generate novel functions , hence biological complexity , gene duplication has been credited with enormous evolutionary importance . The way in which duplicated genes acquire novel functions remains the focus of intense research . Does the mechanism of duplication—duplication of small genome regions versus genome duplication—influence the fate of duplicates ? Although it has been shown that the mechanism of duplication determines the persistence of genes in duplicate , a model describing the functional fates of duplicates generated by whole-genome or small-scale duplications remains largely obscure . Here we show that despite the large amount of genetic material originated by whole-genome duplication in the yeast Saccharomyces cerevisiae , these duplicates specialized in subsets of ancestral functions . Conversely , small-scale duplicates originated novel functions . We describe and test a model to explain the evolutionary dynamics of duplicates originated by different mechanisms . Our results shed light on the functional fates of duplicates and role of the duplication mechanism in generating functional diversity .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"biology",
"evolutionary",
"biology",
"evolutionary",
"theory"
] |
2013
|
The Roles of Whole-Genome and Small-Scale Duplications in the Functional Specialization of Saccharomyces cerevisiae Genes
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This work examined the mechanisms underlying auditory motion processing in the auditory cortex of awake monkeys using functional magnetic resonance imaging ( fMRI ) . We tested to what extent auditory motion analysis can be explained by the linear combination of static spatial mechanisms , spectrotemporal processes , and their interaction . We found that the posterior auditory cortex , including A1 and the surrounding caudal belt and parabelt , is involved in auditory motion analysis . Static spatial and spectrotemporal processes were able to fully explain motion-induced activation in most parts of the auditory cortex , including A1 , but not in circumscribed regions of the posterior belt and parabelt cortex . We show that in these regions motion-specific processes contribute to the activation , providing the first demonstration that auditory motion is not simply deduced from changes in static spatial location . These results demonstrate that parallel mechanisms for motion and static spatial analysis coexist within the auditory dorsal stream .
Motion is a fundamental dimension of acoustic and visual stimuli that is critical for animals to interact with their environment . Human psychoacoustic studies have addressed whether auditory motion analysis depends on sequential perception of stationary sources or whether specific motion detection mechanisms exist , but the results so far have remained inconclusive [1–9] . Studies of neuronal activity in various mammalian species , including macaques , have shown that cues supporting auditory motion perception can induce pronounced asymmetry of neuronal responses to opposite motion directions in the inferior colliculus and primary auditory cortex A1 [10 , 11] . However , it has been argued that this apparent direction sensitivity does not represent genuine motion selectivity but results from “adaptation of excitation , ” defined as the reduced capacity of a neuron to respond to excitatory stimuli following the presentation of a prior excitatory stimulus , a mechanism also called “spatial masking” [12–14] . Motion processing per se has not been investigated beyond A1 in animal models . However , sensitivity to static spatial information has been shown to increase from A1 to the caudomedial ( CM ) and caudolateral ( CL ) belt areas in macaques [15–19] , opening the possibility that these regions might be more sensitive to dynamic spatial information than A1 . Human functional magnetic resonance imaging ( fMRI ) studies indicate that the planum temporale , the region of the auditory cortex that contains areas homologous to monkey areas CM and CL , is involved in auditory motion processing [20 , 21] . However , these studies did not directly address the question of the underlying mechanisms and did not allow for any conclusion about the existence of specific motion-detection processes for sound movement analysis as opposed to sequential processing of stationary sources . Similarly , lesion studies did not allow for distinguishing between the two hypotheses [22–25] . In this study , we measured the fMRI blood-oxygen-level-dependent ( BOLD ) response to auditory motion in the whole auditory cortex of awake macaques . We performed a series of experiments designed to elucidate the mechanisms supporting auditory motion processing . Data revealed that auditory motion perception relies on specific computational mechanisms beyond the simple representation of successive snapshots of location .
The two first experiments involved motion and stationary stimuli . Four moving and five stationary stimuli were presented in a random order to subjects involved in a visual fixation task , and a sparse-sampling paradigm was used to measure the BOLD response induced by each stimulus ( Fig 1B ) . Auditory stimuli were based on individual intra-auricular recordings of an amplitude-modulated broadband noise . Virtual moving stimuli were perceived as moving back and forth between the positions 0° and 80° within one hemispace , with half of the stimuli starting from the midline position ( 0° ) , while the other half started from the most lateral position ( 80° ) , resulting in four motion stimulus exemplars per subject . The five stationary stimuli corresponded to sounds perceived as coming from the locations −80° , −40° , 0 , +40° , and +80° , respectively ( the minus sign referring to the left hemispace and the plus sign to the right one ) . Because moving stimuli starting from the central position induced similar BOLD responses as those starting to move from the periphery , data were pooled , resulting in two motion conditions corresponding to sounds moving within the left hemispace ( Motion Left ) and those moving within the right hemispace ( Motion Right ) . The goal of this experiment was to identify the neural substrates of motion perception that were not explained by the processing of stationary sounds . We thus compared the BOLD response induced by moving sounds within each hemispace with the average BOLD response induced by the stationary stimuli corresponding to the spatial positions through which the moving sounds passed: the BOLD responses induced by stationary stimuli −80° , −40° , and 0° were thus averaged and compared to those induced by sounds moving in the left hemispace ( contrast Motion Left minus Stationary Left ) , while the BOLD responses induced by stationary stimuli +80° , +40° , and 0° were averaged and compared to those induced by sounds moving in the right hemispace ( contrast Motion Right minus Stationary Right ) . These comparisons allowed us to control for the laterality of the motion stimuli ( nondynamic spatial information , corresponding to the encoding of space within which the motion stimulus was moving ) , as well as for their intrinsic spectrotemporal content ( amplitude-modulated broadband noise filtered through the pinna ) . In each subject ( monkey 1 , M1; monkey 2 , M2 ) , the contrasts Motion Left minus Stationary Left and Motion Right minus Stationary Right revealed widespread activation of the posterior part of the auditory cortex contralateral to the stimuli , on the superior temporal gyrus ( STG ) ( Fig 2A and 2B ) . The activation included the three stages of the hierarchically organized auditory cortex , namely the core ( in A1 ) , the belt ( in the middle lateral [ML] and CL areas , surrounding A1 ) , and the parabelt ( the caudal part of the parabelt , lateral to CL and ML , on the STG convexity ) , and extended into the inferior bank of the STG ( also known as the superior bank of the superior temporal sulcus ) . Activation in the ipsilateral hemisphere was much more limited ( M1 ) or absent altogether ( M2 ) . These results indicate that motion-induced activity in the contralateral posterior auditory cortex cannot simply be explained by a spatial laterality process or by encoding of the intrinsic spectrotemporal content of the moving stimuli since these processes were controlled for by the stationary stimuli . While in Experiment 1 the BOLD response induced by each stimulus was measured 5 s after the stimulus onset ( targeting the peak of the hemodynamic response function [28] ) , in a second experiment we measured the time course of the hemodynamic response induced by each stimulus , recording the BOLD response 2 , 3 , 4 , and 5 s after the stimulus onset ( Fig 2C ) . This was to eliminate the possibility that the greater activation triggered by motion stimuli in Experiment 1 was due to adaptation of the BOLD response to the stationary stimulus while the motion-induced response was still sustained at its maximal level . This experiment revealed no interaction between the two stimulus conditions and the four time points tested , except in a small cluster in the right inferior bank of the STG , where stationary sounds did not induce any significant activation . This confirms that the contrast between moving and stationary stimuli revealed in Experiment 1 was not due to a different time course of the BOLD response to the two types of stimuli . The change of spatial location inherent to moving stimuli induces some temporal variations of the sound spectral envelope due to filtering of the sounds through the pinna . This spectrotemporal effect of motion could theoretically be the source of auditory motion selectivity as described so far . To control for this , we generated a new stimulus by averaging at each time point the signal coming from each channel and presenting the stimulus diotically ( i . e . , the same signal was sent to each ear ) . This stimulus had a spectrotemporal structure similar to the motion stimulus , allowing us to control for the combined effect of the intrinsic spectrotemporal content of the stimulus and the spectrotemporal effect of motion , but did not contain any static spatial cue ( Fig 1A ) . In our third experiment , we compared the BOLD response induced by motion with the one induced by the spectrotemporal control stimulus . The contrasts Motion Left minus Spectrotemporal control and Motion Right minus Spectrotemporal control revealed activation in ML , CL , the caudal parabelt , and the inferior bank of the STG in the hemisphere contralateral to the stimuli ( Fig 3 ) and no activation in the ipsilateral hemisphere . The results thus indicate that motion-induced activation in these contralateral regions cannot be explained by spectrotemporal processes . We then tested the hypothesis that a linear combination of spectrotemporal and stationary spatial processes could fully explain motion-related activity . To do so , we gathered in a single experiment the three different types of stimuli: motion , stationary , and spectrotemporal control stimuli . As a control , we first computed the same contrasts as in Experiments 1 and 3: the contrasts Motion minus Stationary and Motion minus Spectrotemporal controls revealed patterns of activation similar to those observed in Experiments 1 and 3 ( Fig 4 ) . Brain regions commonly activated by both contrasts were ML , CL , the caudal parabelt , and parts of the inferior bank of the STG ( green region in Fig 4 ) . This result indicates that in these regions , motion-related activation cannot be explained by static spatial processing ( controlled in the contrast Motion minus Stationary ) , spectrotemporal effect of motion ( controlled in the contrast Motion minus Spectrotemporal control ) , or the intrinsic spectrotemporal content of the stimulus ( controlled in both contrasts ) alone . We then tested the hypothesis that the addition of these processes could explain motion-induced activation . More specifically , we tested the following model: Motion = Static central sound + Spatial laterality + Spectrotemporal effect of motion , where spatial laterality was defined with the contrast Stationary sounds minus Stationary central sound and the spectrotemporal effect of motion with the contrast Spectrotemporal controls minus Stationary central sound ( S2 Fig ) . Motion-induced activation was not found to be significantly different from the sum of the three components in most parts of brain regions activated by motion stimuli , including A1 ( Fig 5 , transparent regions within the black boundary ) , indicating that the simple additive model provides a good estimation of the activation induced by motion stimuli in these regions . However , in parts of ML , CL , the caudal parabelt , and the inferior bank of the STG , the BOLD response induced by motion stimuli was significantly greater than the sum of the BOLD responses induced by stationary central sound , spatial laterality , and spectrotemporal effect of motion ( Fig 5 , green cluster ) . The excess signal ( i . e . , the part not explained by the above components ) that was present in these areas could arise if the three processes made different contributions ( i . e . , different weighting coefficients attached to each process ) , if the processes interacted , or if an additional , independent ( and thus genuine motion-specific ) process would trigger the response . To distinguish between these explanations , we performed a multiple linear regression analysis across those voxels where the BOLD response to auditory motion was not fully explained by the simple additive model ( green cluster in Fig 5 ) . This analysis revealed that the motion-induced BOLD signal was best estimated by a model including differential weighting factors ( with a slightly smaller contribution of spectrotemporal effect of motion , compared to the two other components in both subjects; see Table 1 ) , weak or no interactions between the components ( R2 change between models with and without interactions: M1: 0 . 004 , F = 0 . 13 , p = 0 . 969; M2: 0 . 019 , F = 4 . 09 , p = 0 . 004; R2 for best model: M1: 0 . 82; M2: 0 . 86; p-values below 1 x 10−6 for each subject ) , and , importantly , a term that assumes the presence of genuine motion-selective responses to occur in these areas ( the added constant term in the linear regression , Table 1 , p-values below 1 x 10−5 for each subject ) . This additional component accounted for about 42% of the mean signal intensity induced by motion stimuli ( M1: 42 . 5%; M2: 42 . 2% ) . A control analysis across voxels taken within the region where the full signal could be explained by the simple additive model ( transparent patch in Fig 5 ) revealed similar regression coefficients but no significant constant term ( Table 1 ) . S3 Fig illustrates the goodness of fit of the best-adjusted model with experimental data in each subject . To further characterize these auditory motion-selective areas , we tested whether they were also selective for visual motion . Visual-motion areas were identified by contrasting the BOLD signal induced by slowly moving horizontally oriented gratings with that induced by stationary gratings . The auditory and visual motion regions were found to partially overlap on the inferior bank of the STG ( Fig 6 ) .
Movement selectivity has been classically investigated by comparing moving and stationary stimuli . In humans , the contrast Motion minus Stationary has consistently revealed activation of the planum temporale but not Heschl’s gyrus [20 , 21 , 29–32] . While human A1 has traditionally been considered to be located on the Heschl’s gyrus , recent tonotopy data suggest that A1 is rather found on the posterior half of the Heschl’s gyrus and slightly extends posteriorly into a small part of the planum temporale [33 , 34] . The planum temporale could thus encompass human homologues of macaque auditory areas CM , CL , and ML but also of the posterolateral part of A1 . According to this model , our results fit well with human data since the contrast Motion minus Stationary induced the recruitment of the caudolateral parts of A1 and extended into CL and ML ( Experiments 1 and 4 ) . The contrast Motion minus Stationary controls for the intrinsic spectrotemporal content of the motion stimuli and , when the stationary control sounds cover the whole spatial range spanned by the motion stimulus , its nondynamic spatial component as well . However , it does not control for the spectrotemporal effects of motion: filtering of sound through the pinna differs for each spatial position , inducing slow modulations of the sound spectral envelope . This dynamic nonspatial component aspect has only been controlled for in one previous study [21] . In this human fMRI study , spectrotemporal effects of motion were found to be processed in parts of the planum temporale overlapping with those involved in motion processing ( revealed by the contrast Motion minus Stationary ) . Our study provides similar results in macaques ( Fig 4 ) . Compared to the previous human study [21] , our study in macaques went several steps further . First , we tested for the first time the possibility that the addition of the different components of auditory stimuli could explain the activation that they induced . Our results demonstrate that the additive combination of ( 1 ) the intrinsic spectrotemporal component ( “Stationary central sound” processing ) , ( 2 ) the nondynamic spatial component ( spatial laterality processing ) , and ( 3 ) the dynamic nonspatial component ( spectrotemporal effect of motion ) allows a full characterization of motion processing in large parts of the STG , including A1 . However , in a circumscribed region overlapping parts of ML , CL , the caudal parabelt , and the inferior bank of the STG , the additive model did not explain a significant fraction of the signal induced by motion stimuli . Second , we controlled for potential interactions between components . This was done by introducing in the linear models all possible interactions and testing whether the percentage of the variance explained by the model including the interactions was significantly higher than in the model without the interaction terms . This analysis revealed weak or no interactions between the components . Third , we controlled for mechanisms that can influence the gain of the three different components ( i . e . , different forms of adaptation or amplification ) . It has been argued that greater activation induced by moving sounds compared to stationary sounds could represent adaptation of responses induced by stationary sounds [35–38] . By measuring the time course of the hemodynamic response induced by motion and stationary sounds , here we demonstrate that the differential activation cannot be explained by ( slow ) adaptation of the BOLD response triggered by stationary sounds ( Experiment 2 ) . Rapid adaptation of neuronal responses could also , in principle , explain greater activation induced by moving sounds . In the present study , the use of an amplitude-modulated noise as a stimulus should have limited such an effect . Moreover , adaptation or amplification mechanisms were controlled in the final linear regression analysis by the coefficients weighting the different components and their interactions . The regression analysis revealed that the magnitude of these mechanisms was moderate ( coefficients close to 1 ) and similar between the region where part of the motion processing signal was left unexplained and the region where the signal could be fully explained by the simple additive model . Thus , adaptation or amplification fails to explain the unaccounted signal . The linear regression analysis revealed that after controlling for the different processes not specific to motion , their potential interactions , and their potential adaptation or amplification , on average 42% of the signal variance remained unexplained . Since processes directly or indirectly linked to processing of several stationary sounds were controlled for in this analysis , we conclude that this remaining part of the signal comes from a motion-specific process . The nature of the mechanisms underlying auditory motion perception has been debated for more than 30 y . The “snapshot hypothesis” postulates that motion is inferred from snapshots of object successive positions , without direct appreciation of motion . According to this hypothesis , auditory motion perception is based on the same mechanisms as those involved in the localization of static sound sources . The alternative hypothesis , usually referred as the “motion detector hypothesis” or “velocity detector hypothesis” , considers that motion perception is based on specific mechanisms . On the one hand , the fact that in humans , the minimum audible movement angle ( MAMA; defined as the smallest movement angle allowing a subject to determine whether a sound is moving or not ) differs from the minimum audible angle ( MAA; defined as the smallest location difference between two static sources that subjects could discriminate ) and was found to increase with speed has been interpreted as suggesting that motion detectors exist [3 , 4] . It has also been argued that if moving sounds are processed via a snapshot process , comparing the location of the starting and ending points should be sufficient to perceive movement , and information about intermediary locations should be redundant . However , the MAMA for moving sounds was found to be smaller than the MAA for tone bursts marking the starting and ending positions of the moving sound [5 , 39] , and subjects could discriminate between accelerating and decelerating 90 ms-long stimuli starting and ending at identical spatial locations [6] , indicating that the human brain extracts other information than the location of the starting and end points of a moving sound . On the other hand , movement detection and discrimination performances of human subjects have been explained by estimation of the distance traversed by the source rather than appreciation of the motion per se [1] . The MAMA and the MAA were also found to show similar dependency on sound frequency , spectral bandwidth , and source azimuth , suggesting that static spatial cue perception and dynamic spatial cue perception are dependent on the same underlying mechanisms [2 , 40] . Altogether , these data have failed to provide clear evidence about the mechanisms underlying motion perception . Our results indicate that the parts of the auditory cortex , including A1 , analyze auditory sources in movement by processing their spatial location and the consequence of location change ( spectrotemporal effect of motion ) , consistent with a “snapshot” strategy . However , we demonstrate that caudal belt and parabelt regions of auditory cortex extract the motion component of moving stimuli ( motion-specific process ) in addition to the non-motion specific components . The coexistence of the two mechanisms might explain why it has been so difficult to distinguish between the snapshot and the motion detectors hypotheses in the past . It is also relevant to psychophysical data illustrating facilitation of motion perception by static spatial information [7 , 8] . The BOLD response measured by fMRI only provides an indirect measure of neuronal activity . The choice of macaques as subjects of this study paves the way for a detailed investigation of the motion-specific mechanism at the cellular level . Our study indicates that motion-specific and snapshot processes coexist in the caudal belt and parabelt regions . Electrophysiological studies will be useful to determine whether the two types of processes are encoded by different populations of neurons or not . This study investigated the mechanisms underlying auditory motion along the azimuth axis restricted to each hemispace . It is possible that the relative contribution of motion-specific and snapshot mechanisms depends on the nature of the movement ( in elevation , in depth , or across hemispaces ) . Primates are particularly accurate at discriminating the spatial location of sounds coming from the regions near the midline [41] , and based on the main opponent-channel hypothesis [42] , the firing rate of auditory neurons contains more information about the precise location of a sound source when it is near the midline , by opposition to the peripheral space . It is thus possible that the contribution of motion-specific mechanism for sounds moving across the midline is less important than when sounds move within one hemispace . Looming sounds are particularly relevant from a behavioral point of view , often indicating a threat . In such sounds , information about the successive static position of the sound is limited to monaural cues and the distance or time to arrival is systematically underestimated [43] . Thus , one might expect the relative contribution of snapshot processes to be less important . These will be interesting hypotheses to test in the future . Auditory information has been proposed to be processed along two main streams: a ventral stream connecting the rostral belt and parabelt areas to the ventral prefrontal cortex , involved in the identification of sounds , and a dorsal stream connecting the caudal belt and parabelt to the posterior parietal cortex and the dorsolateral prefrontal cortex , involved in spatial processing [18 , 44] . The exact number and the respective role of each stream are still a matter of debate . For instance , several authors have suggested that the auditory dorsal stream could be divided into distinct substreams [15 , 45–47] . Anatomical tract-tracing studies suggest at least two substreams originating from the caudal belt areas: a “dorsodorsal substream” involving CM , projecting to Tpt posterior to CM and thence to the parietal and prefrontal cortex; and a “dorsocaudal substream” connecting ML and CL to the caudal parabelt and the inferior bank of the STG , which itself projects to the parietal cortex [48] . Evidence for a role of the dorsal auditory pathway in spatial processing in nonhuman primates comes from electrophysiological data indicating that sensitivity to static spatial information is higher in CL compared to A1 and the rostral belt areas [15 , 18 , 19] . Our study revealed a similar refinement of static spatial processing between A1 and CL ( see S4 Fig ) . Some single-unit electrophysiological studies also highlighted the role of CM in spatial processing [17 , 19] . However , spatial selectivity seems to be weaker compared to CL [19] , and modelling of neural data suggests that the firing rates of CL neurons , but not of CM neurons , carry enough information to account for sound localization performance in azimuth [16] . Using fMRI , we did find strong and consistent BOLD activation induced by static and moving sounds in CL but not in CM . Since the BOLD response indirectly reflects the activity of very large populations of neurons , it is possible that at this scale , the spatial sensitivity of CM neurons cannot be detected . Together , these results suggest that spatial sensitivity differs to some extent between CL and CM and that the specialization for static auditory spatial processing mainly occurs along the dorsocaudal substream . In addition to this static spatial processing , our data demonstrate a particular specialization for motion analysis within the dorsal-caudal substream , indicating that this stream carries out higher-level spatial computation rather than just representing fixed space . This result indicates the existence of parallel pathways for fixed and dynamic auditory spatial analysis within the dorsocaudal stream that likely feed into distinct downstream mechanisms as in the visual system . The exact number of substreams within the visual dorsal pathway and their respective roles are still debated [49–51] . Subdivision of the human visual dorsal pathway into at least two substreams has been proposed , with the dorsodorsal pathway involving the superior parietal lobule , while the ventral-dorsal pathway involves the visual motion areas in the temporal sulcus ( including MT ) and the inferior parietal region [52 , 53] . Auditory motion-specific areas described in the present study have been found to extend on the inferior bank of the STG ( equivalent of the superior bank of the temporal sulcus ) , in the vicinity of visual motion areas , and our visual experiment revealed a small overlap between auditory and visual motion-selective areas in this region . These data suggest that the auditory and visual motion substreams share some neural substrates in the inferior bank of the STG , which might potentially support the numerous behavioral interactions that have been reported between auditory and visual motion perception [54 , 55] . It will be interesting to determine whether this region represents the point where the auditory and visual motion substreams merge by testing whether the same population of neurons respond to auditory and visual motion stimuli and where these neurons project . Because the posterior auditory cortex in humans is involved not only in spatial analysis but also in speech and music perception , recent models of the dorsal auditory stream incorporate the idea that there may be a transformation of auditory information into a motor signal coding for the action necessary to produce the sound [47 , 56 , 57] . While this auditory-motor function could coexist with perceptual spatial processing in distinct substreams [47] , it has also been argued that spatial processing could be interpreted as a preparation for eye movement or grasping [58 , 59] . In this case , the whole dorsal pathway could be characterized as a mechanism for auditory-motor integration , with different substreams supporting different auditory-motor processes . We suggest that the ability to compute motion allows a substream of the auditory dorsal pathway to predict the trajectory of sources in a way that helps visual tracking and grasping .
All procedures were approved by the Animal Welfare and Ethical Review Body at Newcastle University and by the United Kingdom Home Office ( PPL 60/4095 , 60/4037 and 70/7976 ) . Experiments complied with the Animal Scientific Procedures Act ( 1986 ) , the European Directive on the protection of animals used for scientific purposes ( 2010/63/EU ) , and the United States National Institutes of Health Guidelines for the Care and Use of Animals for Experimental Procedures and were performed with great care to ensure the well-being of the animals . Two awake male rhesus monkeys ( Macaca mulatta ) M1 and M2 , respectively 7 and 11 y old ( weighing 7 and 17 kg ) , participated in the experiments . The monkeys were initially implanted with a head holder . All surgical procedures were performed under general anesthesia and sterile conditions . Details regarding surgical procedures , postoperative care , and the cleaning of the implant are published elsewhere [60] . The animals were first habituated to the scanner environment over the course of several days and then enrolled in the experiments . Sound stimuli were created in MATLAB 7 . 1 ( MathWorks , Natick , Massachusetts , US ) with a sample rate of 44 . 1 kHz and 16-bit resolution . All stimuli for the auditory motion experiments ( Experiments 1 to 4 ) were based on a random-phase noise carrier ( 1–20 kHz ) . The noise was amplitude modulated by a sinusoidal envelope of 80% depth at 80 Hz in order to produce an additional localization cue [61] and to prevent adaptation . Prior to the scanning experiments , the amplitude-modulated noise was delivered in free field in an echo-suppressed room from 17 different positions separated by 10° , along the azimuthal axis ( from −80° to +80° ) and recorded with a omnidirectional miniature electret microphone ( Knowles Corporation , Itasca , Illinois , US ) placed within each ear canal of the subject , resulting in the recording of the sound convolved by the head-related transfer function of each monkey . The microphone output was amplified and recorded digitally at a sampling rate of 44 . 1 kHz . In addition to interaural level and time differences , this whole procedure preserves spectral cues specific to each individual and has been shown in humans to induce stimuli to be perceived as localized in the external space when delivered through headphones [62] . While providing stimuli tailored to each subject , this approach is time consuming , and when applied to macaques , it is limited by the fact that the subject’s pinnae are mobile such that movements can distort spectral cues . By gently holding the subject’s pinnae from the back and keeping the stimulus recording sessions short ( ~1 h ) , we could prevent any movement . To accommodate this time limitation , we did not attempt to record sounds separated by less than the MAA ( around 3° in macaques; see [17 , 26 , 63] ) . Instead , we took advantage of the fact that a motion percept can be induced by sequentially presenting sounds coming from spatial positions separated by more than the MAA as long as these spatial positions are not too far apart and as long as the duration of each sound is short enough ( in other words , as long as the apparent speed is high enough ) . Motion stimuli moving three times back and forth between the central space ( 0° position ) and the most lateral position ( + or −80° position ) within each hemispace were created by concatenating 100 ms-long segments of recordings from adjacent locations ( Fig 1 ) ; half of the stimuli started from the central position and the other half started from the most lateral position . Any abrupt change of power between segments was avoided by concatenating on-phase segments , starting and finishing when the power of the amplitude-modulated signal was minimum . Since these spatial locations were separated by 10° , it resulted in stimuli virtually moving at a speed of 100°/s . A similar approach was used to create stationary stimuli: 100 ms-long recorded segments coming from the same location were concatenated to form long examplars of stationary sounds . Five different stationary stimuli were created , corresponding to spatial positions −80° , −40° , 0° , +40° , and +80° ( Fig 1 ) . Finally , spectrotemporal controls of each motion stimulus were created by averaging at each time point the signal coming from each channel and presenting the stimulus diotically ( Fig 1 ) . The resulting stimuli were sounds with intensity and spectral content varying with time like the motion stimuli but with no spatial information ( stimuli sounding as coming from inside the head , without spatial laterality ) . All auditory motion and control stimuli were 4 . 9 s long . To validate the percept induced by the virtual motion stimuli in our monkey subjects , we characterized our stimuli psychophysically in humans . This approach takes advantage of the similarity of spatial perception between humans and monkeys and of the fact that the MAA is actually smaller in humans [17 , 26 , 27 , 63] , allowing us to establish a more exacting test in which differences between concatenated and moving stimuli are more likely to be detected . Briefly , we built an apparatus capable of delivering static or moving sound stimuli in free field in our soundproof chamber . This used an electric motor with adjustable speed ( controlled by a potentiometer ) with an attached rotor arm to which a small speaker was attached , to achieve sound-source rotatory movement in the azimuthal plane through the subject’s ear canal . We have replicated in three human participants ( two males and one female with no hearing disorder , age range: 20–35 y , having given their informed consent ) the intra-auricular recording approach used in macaques , using exactly the same sounds and the same recording equipment . For each human participant , we recorded from the ear canal when static sounds were delivered from azimuthal positions recorded in 10° intervals from zero ( midline , front ) . Additionally , we recorded motion stimuli from the ear canal when a speaker moved around the head with an angular motion of 100°/s or 50°/s , clockwise and anticlockwise . The two types of recordings were based on the same amplitude-modulated noise stimulus used in the macaque work . The recording session lasted between 2 and 3 h , requiring the human participant to remain still during this period . Static recordings from adjacent positions were then concatenated to create stimuli virtually moving at speeds of 100°/s or 50°/s , the duration of each recorded segment being 100 and 200 ms , respectively ( concatenated stimuli ) . This procedure was used to create four concatenated stimuli per participant , while recordings of real moving sounds were used to create moving stimuli matching the travelled path and the direction of the concatenated stimuli: two stimuli of each type moved clockwise ( one moving from +90° to +180° and the other one moving from −90° to 0° ) , and two stimuli moved anticlockwise ( one moving from −90° to +180° and the other one moving from 90° to 0° ) . We tested each participant’s perception of these stimuli using criterion-free psychophysics . We used an AXB psychophysical paradigm , where X was always a moving stimulus and A and B were either a moving stimulus or a concatenated stimulus ( whether A or B was the moving stimulus was randomized across trials ) and each stimulus moved at 100°/s along the same path . Participants were asked to identify which of stimuli A or B was different from X . The results confirmed that no participant was able to distinguish concatenated stimuli from motion stimuli at 100°/s ( performance was at chance level in each participant: Chi-square tests , n = 240 , degrees of freedom [df] = 1 , X2/p = 0 . 6/0 . 44 [participant 1] , 0 . 42/0 . 52 [participant 2] , 0 . 6/0 . 44 [participant 3]; S5 Fig ) . Because spatial acuity in azimuth is better in humans than macaques [17 , 26 , 27 , 63] , this result supports our claim that concatenated stimuli used in the scanner were perceived by macaques as smoothly moving . In a control experiment , we replicated the AXB psychophysical paradigm using the concatenated and motion stimuli moving at a speed of 50°/s . This second experiment confirmed that the percept is speed dependent , as two participants were then able to discriminate concatenated stimuli from motion stimuli ( Chi-square tests , n = 240 , df = 1 , X2/p = 138/<1 x 10−19 [participant 1] , 86 . 4/<1 x 10−19 [participant 3] ) , while the third participant was still at chance level ( Chi-square test , n = 240 , df = 1 , X2/p = 0 . 42/0 . 52 , S5 Fig ) . Stimuli for the tonotopy experiment were based on a random-phase noise carrier with three different passbands , 0 . 5–1 kHz , 2–4 kHz , and 8–16 kHz , resulting in three different stimuli that encompassed different spectral ranges . The carriers were amplitude modulated with a sinusoidal envelope of 90% depth at 10 Hz to achieve robust responses . Stimuli for the visual motion localizer experiment ( Experiment 5 ) were horizontally oriented gratings ( spatial frequency: 0 . 5 cycles/° ) of 6° diameter , displayed at 7° to the right or to the left of the vertical meridian . Half of the stimuli were moving at a frequency of 8 Hz , while the remaining stimuli were stationary . Auditory stimuli were delivered in the scanner at an RMS sound pressure level of 74 dB using custom adapted electrostatic headphones based on a Nordic NeuroLab system ( Nordic NeuroLab , Bergen , Norway ) . These headphones feature a flat frequency transfer function up to 16 kHz and are free from harmonic distortion at the applied sound pressure level . We recorded the spontaneous eye movements of one monkey when exposed to the stationary lateralized stimuli ( −80° , −40° , +40° , and +80° ) through the headphones . Perception of the stimuli induced systematic eye movements in the direction of the sound ( S6 Fig ) , indicating that the spatial information of the stimuli was preserved through the headphones and that the monkey could perceive it . Subjects were scanned in a sitting position , head-fixed , while engaged in a visual fixation task ( fixation window: 2° ) . Eye position was monitored at 60 Hz with a camera-based system ( SensoriMotoric Instruments , Teltow , Germany ) , and correct fixation was rewarded by drops of fruit juice . To avoid any contamination of the stimulus-induced BOLD responses by the response evoked by the acoustic noise of the scanner , a sparse-sampling paradigm was used for all auditory experiments . Images were acquired every 10 s ( acquisition time: 1 . 6 s ) , stimuli being presented during the 8 . 4 s silent gap . Based on a previous time course characterization of the BOLD response in the auditory system of macaques [28] , the plateau phase of the BOLD response was targeted in experiments 1 , 3 , and 4 by starting acquisition of the images 5 s after the stimulus onset . In Experiment 2 , image acquisition started 2 , 3 , 4 , and 5 s after the stimulus onset . To obtain baseline data , stimuli were omitted in 25% of the trials prior to image acquisition . The visual localizer experiment was acquired with a continuous paradigm . Stimuli were delivered in a pseudorandomized way , ensuring that each stimulus was presented the same number of times within each daily session . Because we aimed to only analyze trials in which the monkey was fixating , we interrupted the session when the monkey stopped fixation for more than 5 min . The number of trials per stimulus therefore varied from one session to the next , according to the monkey’s willingness to participate in the visual fixation task . Between 28 and 50 images per stimulus were acquired in each daily session . For the tonotopy experiment , 3 sessions were acquired in each subject . For the first , third , and fourth auditory motion experiments , 5 , 6 , and 17 sessions were acquired in M1 , and 7 , 6 , and 14 sessions were acquired in M2 . For the hemodynamic response function experiment ( Experiment 2 ) , 11 sessions were acquired in M1 . For the visual localizer experiment ( Experiment 5 ) , 7 sessions were acquired in M2 . Data were recorded in a 4 . 7 T actively shielded vertical MRI scanner ( Bruker Biospec 47/60 VAS ) equipped with an actively shielded gradient system ( Bruker GA-38S ) of 38 cm innerbore diameter ( Bruker BioSpin , Ettlingen , Germany ) . A transmit/receive volume RF coil with an active decoupler ( Bruker ) was used to acquire functional and nonisotropic structural data . The volume coil in the transmit-only mode and an 8-channel receiving surface phased-array coil ( H . Kolster , Windmiller Kolster Scientific , Fresno , California , US ) were used to acquire isotropic structural data in order to generate three-dimensional surfaces . Nonisotropic structural T1-weighted images ( resolution: 0 . 5 mm x 0 . 5 mm x 2 mm ) were acquired at the end of each session using a modified driven equilibrium Fourier transform ( MDEFT ) sequence with the same slice geometry as the functional scans to simplify coregistration . The imaging parameters were as follows: FOV: 12 . 8 cm x 9 . 6 cm; FA: 30° , TI: 800 ms; TE: 6 ms , TR: 2 s . Isotropic structural T1- and T2-weighted images ( FOV: 10 cm x 10 cm; resolution: 0 . 6 mm x 0 . 6 mm x 0 . 6 mm ) were acquired during a separate session using a magnetization-prepared rapid gradient-echo ( MP-RAGE ) sequence ( FA: 27° , TI: 800 ms , TE: 7 ms , TR: 2 . 1 s ) , and a rapid acquisition with relaxation enhancement ( RARE ) sequence ( TE: 14 ms , RARE factor: 8 , TR: 5 . 5 s ) , respectively . No parallel acceleration was used . Functional data covering the whole STG were acquired with a single-shot gradient-echo echo-planar imaging ( EPI ) sequence optimized for each monkey . Typical parameters were as follows: FOV: 12 . 8 cm x 9 . 6 cm; FA: 90° , TE: 21 ms , TA: 1 . 6 s , axial orientation , slice thickness: 2 mm , interleaved slice acquisition . The inplane resolution was 1 mm x 1 mm for M1 and 1 mm x 1 . 5 mm for M2 . Functional MRI data were analyzed with SPM8 ( http://www . fil . ion . ucl . ac . uk/spm/ ) . Data acquired from each animal were processed separately in their native space . Images from each session were first realigned to the mean EPI image . No attempt was made to coregister EPI and structural scans . Instead , a pair consisting of a mean EPI image and a nonisotropic structural scan acquired during the same session was chosen as a reference , based on the quality of their alignment to each other . All functional images were coregistered to this reference EPI image , and all the nonisotropic structural scans were coregistered to the corresponding structural scan . The isotropic structural scans were coregistered to the mean of all nonisotropic structural scans . Functional data were smoothed with a kernel of 2 mm fullwidth at half maximum , high-pass filtered with a cut-off of 300 s to account for slow signal drifts , and adjusted for global signal fluctuations ( global scaling ) . In a general linear model analysis for the combined sessions of each experiment , the voxel-wise response estimate coefficients ( beta-values ) and t-values ( one sided t-test ) for the different contrasts of interest were calculated ( head movement parameters were regressed out ) . Associated p-values were corrected for multiple comparisons using the FWE correction on the bilateral STG ( Experiments 1 , 2 , and 3 ) and for the STG contralateral to the stimuli ( Experiments 4 and 5 ) . For auditory and visual motion experiments , data acquired while subjects did not fixate were discarded . For tonotopy experiments , all data were used . In Experiment 4 , a multiple linear regression analysis was performed across voxels in each subject using SPSS ( IBM SPSS Statistics 21 . 0 ) . The analysis was first performed across the set of voxels where the contrasts Motion Left minus ( Left Stationary central sound + Left Spatial laterality + Left Spectrotemporal effect of motion ) and Motion Right minus ( Right Stationary central sound + Right Spatial laterality + Right Spectrotemporal effect of motion ) performed at the voxel level were significant ( t-values > 4 . 1 , corrected p < 0 . 05 ) . In order to determine the source of the signal that was not explained by the linear addition of components , we tested the following model across those voxels: First- and second-order interactions between the three explanatory factors were incorporated only if this more complex model significantly increased the percentage of variance explained by the model . As a control , we performed the same analysis across a subset of voxels taken from the region where the voxel-based contrasts did not induce any significant difference ( t-values < 4 . 1 , corrected p > 0 . 05 ) . To match the statistical power of both analyses , the size of this second voxel set was matched to the first one by selecting voxels with the smallest t-values . Since the probability of false-negative results decreases with the t value , this procedure reduced the risk of selecting false-negative voxels . Performing these analyses on smoothed and unsmoothed data provided similar results . Only results based on unsmoothed data are described in the Results section of the manuscript . Isotropic structural images were used to generate the rendered surfaces . The ratio between T1-weighted and T2-weighted images was computed , and the resulting image was used to manually segment the gray matter of the STG . The binary image was used to generate a tri-dimensional triangulated mesh using BrainVisa suite ( http://brainvisa . info ) . The functional results ( contrast maps and t maps ) were then projected with BrainVisa onto the rendered surface . Tonotopy maps ( S1 Fig ) were calculated by subtracting the response estimate coefficient ( beta-values ) of the low-frequency condition ( 0 . 5–1 kHz ) from the high-frequency condition ( 8–16 kHz ) . The contrast High frequency minus Low frequency was inclusively masked by the contrast High frequency minus Silence , while the contrast Low frequency minus High frequency was masked by the contrast Low frequency minus Silence ( p < 0 . 05 , uncorrected for multiple comparisons for both masks ) . The low- and high-frequency reversals of tonotopic gradients were identified on the surfaces and used to define the position of the core and belt areas on the superior bank of the STG: the low-frequency gradient reversal defined the rostral border of A1 and ML , and the high-frequency reversal defined the caudal border of A1 and ML and the rostral border of CL ( see Fig 2A ) . The caudal parabelt was defined as the region lateral to ML and CL on the STG convexity .
|
Motion is a fundamental dimension of acoustic and visual stimuli that is critical for animals to interact with their environment . Yet , surprisingly , we still do not understand the basic mechanisms in the brain that underlie perception of auditory motion . For the last 30 y , this research field has been hampered by unsuccessful attempts to answer a simple but fundamental question: is auditory motion perception deduced from processing individual static sounds , or are there mechanisms in the auditory domain dedicated to detecting motion ? Here we report the discovery of specific motion detectors located in the auditory cortex of primates . We demonstrate that these auditory motion detectors are close to the well-known visual motion detectors . Both types of detectors are likely to be crucial for the planning of limb and eye movement . This study addresses a fundamental issue in neuroscience and sheds new light on the brain mechanisms underlying the essential aspects of our ability to navigate the world .
|
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"Abstract",
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"Results",
"Discussion",
"Materials",
"and",
"methods"
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] |
2017
|
Auditory motion-specific mechanisms in the primate brain
|
While short-read sequencing technology has resulted in a sharp increase in the number of species with genome assemblies , these assemblies are typically highly fragmented . Repeats pose the largest challenge for reference genome assembly , and pericentromeric regions and the repeat-rich Y chromosome are typically ignored from sequencing projects . Here , we assemble the genome of Drosophila miranda using long reads for contig formation , chromatin interaction maps for scaffolding and short reads , and optical mapping and bacterial artificial chromosome ( BAC ) clone sequencing for consensus validation . Our assembly recovers entire chromosomes and contains large fractions of repetitive DNA , including about 41 . 5 Mb of pericentromeric and telomeric regions , and >100 Mb of the recently formed highly repetitive neo-Y chromosome . While Y chromosome evolution is typically characterized by global sequence loss and shrinkage , the neo-Y increased in size by almost 3-fold because of the accumulation of repetitive sequences . Our high-quality assembly allows us to reconstruct the chromosomal events that have led to the unusual sex chromosome karyotype in D . miranda , including the independent de novo formation of a pair of sex chromosomes at two distinct time points , or the reversion of a former Y chromosome to an autosome .
Sex chromosomes are derived from ordinary autosomes , yet old X and Y chromosomes contain a vastly different gene repertoire [1] . In particular , X chromosomes resemble the autosome from which they were derived , with only few changes to their gene content [2] . In contrast , Y chromosomes dramatically remodel their genomic architecture . Y evolution is characterized by massive gene decay , with the vast majority of the genes originally present on the Y disappearing , and Y degeneration is often accompanied by the acquisition of repetitive DNA [3]; old Y chromosomes typically have shrunk dramatically in size and contain only few unique genes but vast amounts of repeats . The decrease in sequencing cost and increased sophistication of assembly algorithms for short-read platforms have resulted in a sharp increase in the number of species with genome assemblies . Indeed , X chromosomes have been characterized and sequenced in many species . However , assemblies based on short-read technology are highly fragmented , with many gaps , ambiguities , and errors remaining; this is especially true for repeat-rich regions , such as centromeres , telomeres , or the Y chromosome [4–6] . Thus , most sequencing projects have ignored the Y chromosome . Labor-intensive sequencing of Y chromosomes in a few mammal species has revealed a surprisingly dynamic history of Y chromosome evolution , with meiotic conflicts driving gene acquisition on the mouse Y chromosome [7] , or gene conversion within palindromes retarding Y degeneration in primates [8] . However , all current Y assemblies are based on tedious resequencing of bacterial artificial chromosome ( BAC ) clones and available only for a handful of species [9–11] , and the repeat-rich nature of Y chromosomes has hampered their evolutionary studies in most organisms . Here , we present a near-finished reference genome for Drosophila miranda , including its Y chromosome , using a combination of long-read single-molecule sequencing , high-fidelity short-read sequencing , optical mapping , BAC clones sequencing , and Hi-C-based chromatin interaction maps . D . miranda has become a model system for studying the molecular and evolutionary processes driving sex chromosome differentiation , because of its recently evolved neo-sex chromosome system ( see Fig 1 ) . In particular , chromosomal fusions within D . miranda have resulted in the recent sex-linkage of former autosomes at two independent time points ( Fig 1D ) , and these new sex chromosomes are at different stages in their transition to differentiated sex chromosomes . Specifically , chromosomes XR and YD became sex-linked about 15 million years ( MY ) ago [12] , and the neo-X and neo-Y became sex chromosomes only about 1 . 5 MY ago [13] . These former autosomes are in the process of evolving the stereotypical properties of ancestral sex chromosomes [14 , 15] . Intriguingly , the ancestral Y chromosome ( Yanc ) in this species group became fused to an autosome , probably around the same time XR and YD formed , and lost some of the characteristics of an ancient Y chromosome [16–18] . Thus , D . miranda allows the investigation of the functional and evolutionary changes occurring on differentiating sex chromosomes , and their reversal . The most recent assembly of D . miranda was generated via short-read Illumina sequencing and is highly fragmented . In particular , the genome was in 47 , 035 scaffolds , with a scaffold N50 ( a weighted median statistic such that 50% of the entire assembly is contained in scaffolds equal to or larger than this value ) of 5 , 007 bp and a total assembled genome size of 112 Mb ( a female-only assembly resulted in 22 , 259 scaffolds , with an N50 of 13 , 773 bp and an assembled size of 125 Mb ) . The high amount of sequence similarity between the neo-sex chromosomes ( 98 . 5% identical at the nucleotide level ) , yet high repeat content of the neo-Y ( over 50% of its DNA is derived from repeats [19] ) posed a particular challenge to its assembly using short reads . Specifically , initial attempts to assemble the neo-Y resulted in a chimeric , highly fragmented and incomplete assembly , consisting of 36 , 282 ( often chimeric ) scaffolds , and a scaffold N50 of only 715 bp [20] . Thus , our previous analysis of neo-Y chromosome gene content evolution was instead based on mapping male reads to the neo-X assembly and identifying male-specific SNPs [20] , or trying to reconstruct neo-Y transcripts using both male and female genome and transcriptome data [21] . This indirect approach , however , only allows the investigation of conserved regions on the neo-sex chromosome that differ by simple SNPs or short indels within genes . Here , we assemble the genome of D . miranda using long reads for contig formation , short reads for consensus validation , and scaffolding by chromatin interaction mapping , and we verify our assembly using optical maps and BAC clone sequencing . Our assembly covers large fractions of repetitive DNA , with entire chromosomes being in a single scaffold , including their centromeres , and we recover over >100 Mb of the recently formed neo-Y chromosome . Our new assembly strategy achieves superior continuity and accuracy and provides a new standard reference for the investigation of repetitive sequences and Y chromosome evolution in this species .
We sequenced adult male D . miranda ( from the inbred strain MSH22 ) using a combination of different technologies: single-molecule real-time sequencing ( PacBio ) , paired-end short-read sequencing ( Illumina HiSeq ) , optical mapping ( using BioNano ) , shotgun BAC clones sequencing ( Illumina HiSeq ) and chromatin conformation capture ( Hi-C; see S1 Table ) . Assembly of these complementary data types proceeded in a stepwise fashion ( Fig 2A ) , similar to a recent approach [22] , to produce progressively improved assemblies ( Table 1 ) . Briefly , we produced two initial assemblies of the PacBio data alone using the Falcon [23] and Canu [24] assemblers , and double merged the resulting assemblies with Quickmerge [25] . The resulting hybrid assembly had a contig NG50 ( the minimum length of contigs accounting for half of the haploid genome size ) of 5 . 2 Mb in 271 scaffolds . PacBio contigs were separated into X-linked and autosomal contigs versus Y-linked contigs , based on genomic coverage patterns of mapped male and female Illumina reads ( S1 Fig ) , to avoid cross-mapping of short-read Hi-C data , and clustered into chromosome-scale scaffolds using Hi-C data ( Fig 2B , S2 Fig , S3 Fig ) . Mapping of Illumina reads also allowed us to identify and remove contigs that resulted from uncollapsed haplotypes ( S4 Fig ) . X-linked and autosomal contigs were scaffolded with female Hi-C libraries , while Y-linked contigs were clustered using Y-mapping reads from male Hi-C libraries ( S2 Fig ) . Visual inspection of contact probability maps allowed us to identify a few misassemblies , which were manually corrected followed by rescaffolding ( S2 Table ) . To assess quality , the resulting assembly was validated via statistical methods and short-read Illumina mapping ( S3 Table ) , and comparison to optical mapping data ( S4 Table and S5 Fig ) and sequenced BAC clones from the MSH22 strain ( S5 Table , S6 Table , Fig 2D and S6 Fig ) and previous assemblies ( D . miranda D . mir1 . 0 [20] Fig 2C and S7 Fig; D . pseudoobscura; S8 Fig ) . To maximize accuracy of the final reference assembly , errors were manually curated before final gap filling and polishing ( S2 Table ) . Our final assembly , D . mir2 . 0 , totaled 287 Mb of sequence , with a scaffold NG50 of 35 . 3 Mb ( Table 1 ) . D . mir2 . 0 comprises just 102 scaffolds and 120 gaps ( S7 Table ) , and the three autosomes , the three X chromosome arms , and the Y of D . miranda are all mostly covered by a single scaffold ( Fig 3 ) . The unplaced scaffolds are relatively small ( median size 37 . 3 kb ) and highly repeat-rich ( median repeat content 94 . 7% ) , and sex-specific coverage patterns suggest that most are derived from the Y chromosome . In contrast , the previous assembly D . mir1 . 0 consisted of 47 , 035 scaffolds [20] . We used two approaches , REPdenovo [26] and RepeatModeler [27] , to annotate repeats in the D . miranda genome and Maker [28] to annotate genes ( Fig 3 ) . We identified a total of 17 , 745 genes , and 43 . 7% of the genome was annotated as repeats . BUSCO assessments [29] support that our genome assembly and annotation are highly complete ( S8 Table ) . The previous D . miranda reference assembly ( D . mir1 . 0 ) was generated from paired-end short reads using the SOAPdenovo assembler and cross-species scaffold alignments to D . pseudoobscura [20] . Paired-end read sequences used to create the D . mir1 . 0 reference assembly were aligned to our D . mir2 . 0 assembly for a reference-free measure of structural correctness . These alignments confirmed that our current assembly is a dramatic improvement over D . mir1 . 0 ( S3 Table ) , with fewer putative translocations ( 36 versus 17 , 764 ) , deletions ( 229 versus 6 , 075 ) , and duplications ( 8 versus 1 , 703 ) . D . miranda and D . pseudoobscura are known to harbor dozens of inversions [30] , and the initial D . miranda genome was scaffolded using D . pseudoobscura . Genome-wide alignments between our current D . miranda assembly and D . mir1 . 0 reveal dozens of rearrangements that were likely introduced by the scaffolding ( Fig 2C; S7 Fig ) and reflect inversions between D . miranda and D . pseudoobscura ( see S7 Fig and S8 Fig ) . We independently assessed the quality and large-scale structural continuity of our assembly by comparing it to sequenced BAC clones and optical mapping data . In total , we shotgun sequenced 383 randomly selected BAC clones from a D . miranda male BAC clone library [19] , which should cover roughly 1/4 of the D . miranda genome . Three hundred seventy-two BAC clones passed our sequence coverage filter and could be aligned to our D . miranda genome; of those , 361 ( i . e . , 97% ) contiguously map to a unique position in the genome ( Fig 2D; S5 Table , S6 Table; S6 Fig ) . Only 11 BAC clones map to two or more ( typically highly repetitive ) genomic locations ( Fig 2D ) , and could represent assembly mistakes or recombinant BAC clones . Similarly , most of our genome is covered by optical mapping data ( S5 Fig and S4 Table ) . Thus , continuous and unique mapping of most BAC clones and coverage by optical reads confirm the high quality of our genome assembly . Our high-quality assembly contains large amounts of highly repetitive regions , including telomeres , pericentromeric regions , and putative centromeric repeats as well as the repeat-rich Y chromosome . Overall , about 126 Mb of the assembled 287 Mb D . miranda genome are repetitive , and we assembled about 41 Mb of pericentromeric and centromeric repeats and telomeres ( S7 Table ) . In some cases , we assembled through the entire centromere and recovered telomeric repeats at the end of a chromosome arm ( see below ) . In contrast , the previous D . miranda assembly based on only Illumina reads recovered less than 0 . 5 Mb of pericentromeric DNA ( S7 Table , S7 Fig ) , and even the highly curated D . melanogaster genome assembly [31] entirely lacks centromeric sequence ( S9 Fig ) . In addition , we assembled 110 . 5 Mb of Y-linked sequence , with 101 . 5 Mb contained within a single scaffold ( Fig 3 ) . Our assembly allows us to recover repetitive regions , including gene duplications and tandem repeats , most of which were collapsed and missed in our previous assembly ( S10 Fig ) . In Drosophila , telomeres are maintained by the occasional transposition of specific non-LTR retrotransposons ( i . e . , the HeT-A , TAHRE , and TART elements ) to chromosome ends [32 , 33] , and hybridization studies have suggested about two telomere repeats per chromosome end in D . miranda [34] . Indeed , for almost all chromosome arms ( Muller A , B , C , both ends of E , F , neo-Y , and YD ) , we properly identified the ends of chromosomes based on the presence of telomeric transposable elements ( see Fig 4A , Fig 4B ) . Centromere sequences show little conservation between closely related species but have a common organization in most animals and plants [35–37] . In particular , centromeres typically comprise megabase-scale arrays of tandem repeats embedded in heterochromatin but are notoriously difficult to recover in genome assemblies . In several instances , we sequenced several megabases into the highly repetitive pericentromeric region ( Fig 3 , Fig 4; S11 Fig ) , and for one chromosome ( Muller element E ) , we assembled the entire chromosome ( based on the recovery of telomeric sequences on both chromosome ends ) , including its centromere . We used Tandem Repeat Finder ( TRF ) [38] to identify satellite repeats , and plotted their occurrence along the genome ( Fig 3 , Fig 4C , S12 Fig ) . Interestingly , we find that the two most highly abundant repeats in the genome are adjacent to each other and heavily enriched along pericentromeric regions ( Fig 4F , S13 Fig ) : a 21-bp motif that is found at the center of the centromeric region at most chromosomes , and an unrelated 99-bp repeat motif that is heavily AT-rich and has characteristics described for other centromeric repeats ( Fig 4D , Fig 4E ) . Specifically , the 99-bp motif shows a 10-bp periodicity of A and/or T di- and trinucleotides , similar to centromere repeats found in diverse species , including D . melanogaster and the legume Astragalus sinicus [39 , 40] . Pericentromeric regions are heterochromatic , and we see strong enrichment of H3K9me3 along the pericentromere ( Fig 3 , Fig 4F ) . However , centromere repeats are partially occupied by a special centromeric variant of histone H3 ( cenH3 ) , which forms specialized nucleosomes that wrap centromeric DNA [41] , and we would thus expect less H3K9me3 enrichment at sequences that partly replace the canonical H3 histone with cenH3 . Indeed , H3K9me3 enrichment is reduced at both the 21-bp and 99-bp motif relative to other pericentromeric regions ( Fig 4F , S13 Fig ) . Thus , the genomic distribution of the 21-bp and 99-bp motifs and their structural features and epigenetic modifications strongly suggest that they represent the functional centromere in D . miranda . In addition to the repetitive pericentromeres , our assembly also contains two large heterochromatic islands along the two autosomal arms ( about 800 kb on chromosome [ch]4 and 1 . 5 Mb on ch2; Fig 3 ) . These heterochromatic islands and their positions are supported by in situ hybridization data ( Fig 1C ) . Intriguingly , while the repeat density is increased in these islands ( especially on ch2 ) , gene density is similar to other euchromatic regions . In D . melanogaster , repeat-rich heterochromatic regions appear to be absent along the major chromosome arms , and it will be of great interest to understand the functional significance and phylogenetic distribution of these heterochromatic islands . The presence of its recently formed neo-sex chromosomes has established D . miranda as an important model system [13 , 15 , 20] . Yet , the assembly of both the neo-X and neo-Y proved particularly challenging to short-read technology , and our previous attempt to create a contiguous Y/neo-Y chromosome assembly failed [20] . In contrast , our current assembly contains most of the Y chromosome in one large scaffold ( 101 . 5 Mb , see Fig 3 , Fig 5 ) . Intriguingly , the neo-Y assembly is about three times the size of the neo-X assembly ( S7 Table , Fig 5 ) ; thus , analysis of neo-Y sequences based on neo-X alignments clearly misses the majority of the changes that occurred between the neo-sex chromosomes . Sequence analysis of BAC clones confirms that our neo-X and neo-Y assembly is of high quality . In particular , 28 BAC clones fully map to the neo-X chromosome and 92 map to the neo-Y/Y chromosome; only three BACs in highly repetitive sequences on the neo-Y map to two different regions ( and may either indicate a misassembly or a recombinant BAC clone; S5 Table , S6 Table; Fig 2D ) . Thus , our assembly approach allowed us to recover a highly contiguous Y/neo-Y sequence . Inspection of BAC sequences from homologous neo-X and neo-Y regions confirms the specificity of our neo-X and neo-Y-linked assembly . That is , we find little cross-mapping between BAC clone sequences derived from the neo-X chromosome and its former homolog , the neo-Y , and vice versa , confirming the lack of chimeric assemblies ( S14 Fig ) . Also , comparisons of homologous regions covered by BAC clones validate that neo-Y sequences contain roughly three times more DNA than their homologous segments on the neo-X , supporting the global size differences in chromosome assemblies that we observe . Thus , rather than shrinking—the fate that is typically ascribed to Y chromosomes—we find that early Y chromosome evolution instead is characterized by a massive global DNA gain . Genome-wide alignments between the neo-X and neo-Y chromosome support a global increase in size of the neo-Y chromosome at intronic and intergenic regions , mainly driven by the accumulation of repetitive elements ( Fig 3 , Fig 5 , S15 Fig ) . We assembled 110 . 5 Mb of Y/neo-Y-linked sequence , and 81 . 5 Mb are derived from repetitive elements ( compared to 5 . 3 Mb on the neo-X ) . TEs are uniformly enriched along the neo-Y chromosome ( Fig 3 , Fig 5 ) and a main contributor to its dramatically increased genome size . Transposons show a highly nested structure on the neo-Y , with TE copies being disrupted by the insertion of ( fragments of ) other transposable elements ( Fig 5B , Fig 5C ) , making the exact delineation of TE copies challenging . The most abundant repeat on the neo-Y is the ISY element [42] , a helitron transposon that is inserted about 22 , 000 times on the neo-Y/Y chromosome and occupies more than 16 Mb on the neo-Y ( i . e . , 16% of neo-Y sequence; Fig 3 , S16 Fig ) . In contrast , we only find about 1 , 500 copies on its former homolog , the neo-X chromosome ( 3% of the neo-X; less than 1 Mb ) . The second most common repeat class that has amplified on the neo-Y are gypsy transposable elements; we find roughly 14 , 300 insertions on the neo-Y ( 15% of neo-Y sequence , 15 Mb ) and less than 1 Mb on the neo-X ( about 800 insertions , i . e . , 3% of its sequence ) . In D . miranda , novel sex chromosomes were created recently at two different time points by chromosomal fusions ( Fig 1D ) . In an ancestor of D . miranda , about 15 MY ago , a new X-linked arm ( referred to as chromosome XR ) arose by the fusion of an autosome ( Muller element D ) to the ancestral X chromosome ( element A , referred to as chromosome XL in D . miranda ) . The fusion of Muller elements A and D left behind an unfused element D in males ( which we refer to as YD ) , and this chromosome co-segregates with the ancestral Y and is transmitted through males only . The lack of recombination in male Drosophila implies that YD is entirely sheltered from recombination and thus undergoes genome-wide degeneration [12 , 43] . Indeed , while the fused Muller D that became part of the X chromosome has maintained most of its ancestral genes ( we annotate over 2 , 800 genes on XR ) , previous attempts to recover Y-linked genes in D . pseudoobscura have proven difficult . On one hand , single-copy genes located on the ancestral Y chromosome ( Yanc ) of Drosophila were found to be autosomal in D . pseudoobscura and its relatives [16] , and located on the small dot chromosome ( i . e . , element F [17] ) . It was suggested that the current Y chromosome in D . pseudoobscura instead is the remnant of a highly degenerate YD [16] , and we previously identified about 30 transcripts from the Y in D . pseudoobscura , most of which were found to have their closest paralogs on Muller D [44] . This supports the idea that the current Y of D . pseudoobscura is derived from the unfused Muller D , i . e . , YD . A more recent chromosomal fusion ( about 1 . 5 MY ago ) between YD and element C created another neo-sex chromosome specific to D . miranda . This time , the fused element ( termed the neo-Y ) is male limited and undergoing degeneration , while the unfused element ( the neo-X ) is evolving characteristics typical of X chromosomes [19 , 20] . Our high-quality genome assembly allows us to reconstruct the evolutionary events leading to the independent creation of novel sex chromosomes in the D . miranda genome and the reversal of a former Y chromosome ( Yanc ) to an autosome ( Fig 6 ) . Gene content is conserved across chromosomes in Drosophila ( referred to as Muller elements A–F [45] ) , with Muller element A being the ancestral X chromosome in the genus Drosophila ( Fig 1 ) . We used orthology information from either D . melanogaster or D . pseudoobscura to infer chromosomal rearrangements in D . miranda and their evolutionary trajectory ( Fig 6 ) . The fusion between elements A and D created a metacentric X chromosome in D . miranda , and our assembly contains both of these chromosome arms as a single scaffold , including a large pericentromeric block on XR that is highly repeat rich . Comparison to D . melanogaster identifies a pericentric inversion that moved approximately 340 genes from element A onto XR ( see Fig 6A ) . An X chromosome–autosome fusion results in two Y chromosomes in males ( i . e . , Yanc and the unfused element D ) , but D . miranda and its relatives only harbor a single Y . The ancestral Y chromosome in Drosophila contains a handful of single-copy genes that have no homologs on the X chromosome [46 , 47] , as well as the multi-copy ribosomal DNA ( rDNA ) repeat cluster that is present on both the X and the Y and used for pairing of the sex chromosomes during male meiosis [48–50] . Our assembly reveals that the gene content of the ancestral Y is split up between two chromosomes: all five ancestral single-copy Y genes in Drosophila ( i . e . , kl-2 , kl-3 , ORY , PRY , and PPr-Y ) are located in a single genomic region on the dot chromosome , adjacent to the centromere ( Fig 6B ) , while the rDNA repeat cluster is found on the Y chromosome of D . miranda ( Fig 6C ) . The presence of two Y chromosomes in an ancestor of D . miranda may have resulted in an increased frequency of aneuploidy gametes [51] . Potential problems in meiosis could have been ameliorated by the fusion and/or translocation of genetic material from Yanc to both element F and YD , and relocation of the rDNA repeat cluster onto YD could have helped to ensure proper segregation between the X and Y chromosome . Indeed , an in situ hybridization study suggests that copies of the rDNA loci exist on both the X and Y chromosomes in relatives of D . miranda that share the element A–D fusion and translocation of single-copy Yanc genes onto element F [17] , suggesting that these structural rearrangements co-occurred rapidly before the divergence of this species group . Note , however , that the chromosomal location of the rDNA cluster can differ among closely related Drosophila species [52] , so other scenarios of movement of rDNA genes are possible . The Y-derived material on the dot of D . miranda amounts to approximately 300 kb , which is substantially smaller than Y chromosomes found in Drosophila [53] , suggesting that Yanc presumably lost genetic material after fusing to the dot chromosome . Similar shrinkage of the Yanc was found in its sister species , D . pseudoobscura [18] , which shows an inversion of the Y-derived segment with respect to D . miranda ( S17 Fig ) . The Yanc/element F fusion break point is corroborated independently by a BAC clone spanning the fusion ( S17 Fig ) , validating our genome assembly in this region . Despite Yanc presumably having lost large amounts of repetitive DNA , we find its repeat content to be elevated relative to euchromatic regions , and Yanc genes contain higher levels of heterochromatin compared to genes from other chromosomes ( S17 Fig ) . They also have maintained their testis-specific expression pattern in D . miranda ( S17 Fig ) . Thus , despite having become linked to an autosome , single-copy Y genes have retained their ancestral chromatin environment and testis function . Nonrecombining Y chromosomes degenerate within a few MY in Drosophila [19 , 20] , and most ancestral genes on YD were presumably lost before it fused to element C about 1 . 5 MY ago . We tried to reconstruct the evolutionary history of the Y chromosome in D . miranda by identifying which parts of the Y/neo-Y chromosome were derived from Muller D versus Muller C versus the original Yanc . Our Y/neo-Y chromosome assembly consists of two chromosome arms , spanning the putative centromeric repeats , and the heterochromatic pericentromere ( Fig 6C ) . A dot plot between the neo-X ( Muller C ) and neo-Y reveals several large blocks of homology on the large Y/neo-Y arm but none on the shorter arm ( Fig 5A ) . Fig 6C plots the location of single-copy genes along the neo-Y/Y chromosome of D . miranda , color coded by Muller element . We identify many genes from the long arm of the Y/neo-Y , most of which are derived from Muller C; in contrast , only few unique genes exist on the short arm , and their closest homologs are not preferentially located on Muller C ( Fig 6C ) . This suggests that the long arm is derived from the neo-Y , but not the shorter one , which instead may be derived from YD and should thus also be Y-linked in D . pseudoobscura . The current genome of D . pseudoobscura lacks an assembly of its Y chromosome , and repetitive nonfunctional regions evolve rapidly , which makes identification of YD sequences challenging . We attempted to detect putative YD sequences by identifying reads and scaffolds from the fragmented D . pseudoobscura genome that are male specific ( see Methods ) and mapping them onto our D . miranda Y/neo-Y assembly . Preferential mapping of putative male-specific ( i . e . , Y-linked ) sequences from D . pseudoobscura to the short arm of the D . miranda Y/neo-Y chromosome assembly supports the notion that the short arm of the Y/neo-Y chromosome corresponds to YD . The rDNA cluster maps adjacent to the centromere on the short arm of the Y chromosome , which suggests that this part is derived from the original Y ( i . e . , Yanc ) of Drosophila . Interestingly , hybridization studies have shown that the Y/neo-Y chromosome of D . miranda contains about 70 copies of the telomere repeat [34] and displays an intensely labeled internal telomere-repeat block adjacent to the centromere [54] . Indeed , our assembly recovers a large internal block of telomere-repeat sequences close to the centromere ( Fig 6C ) , bordering fragments of the Y chromosome of different evolutionary origin ( i . e . , they are found between fragments derived from Muller D versus Muller C versus the original Yanc ) . Telomere repeats within the Y/neo-Y may present the remnants of a “telomere-to-telomere” type chromosomal fusion that created the neo-Y/Y chromosomal arrangements in this species .
Here , we create a genome assembly of unprecedented quality and contiguity for the fruit fly D . miranda , a species that has served as a model for sex chromosome research . In D . miranda , chromosomal fusions at different time points independently created de novo sex chromosomes or led to the reversal of a former Y to an autosome , and our high-quality assembly allows us to reconstruct the evolutionary events creating and dismantling sex chromosomes . Our assembly recovers entire chromosomes and notoriously difficult regions to assemble , including entire centromeres or large stretches of repetitive sequences , such as the rDNA cluster . All chromosome arms of D . miranda—including its Y chromosome—are contained in a single , chromosome-sized scaffold , and in almost all cases , chromosome arms are flanked by telomere sequences on one end and centromeric repeats on the other . This demonstrates that long molecule sequencing approaches have great potential to assemble highly repeat-rich regions , such as Y chromosomes and centromeres [55–57] , which will allow studying the function , biology , and evolution of repetitive regions in many species , including gene family expansions and contractions , identification and characterization of centromeres , heterochromatin function , genomic analysis of Y chromosomes , repeat evolution , or identification of novel genes embedded in heterochromatin . In one instance , we assemble an entire chromosome , fully sequence through the pericentromeric DNA and the centromere , and recover telomeres on both ends . Our high-quality assembly allows us to infer the centromeric satellite DNA motif in D . miranda , which shares no sequence similarity with other centromeres but has characteristics typical of centromeric repeats , including a 10-bp periodicity of AA/TT/AT repeats . This sequence feature presumably helps to stabilize centromeric nucleosomes that may be under tension during anaphase , because a single turn of the DNA double helix is approximately 10 bp , and sequences with 10-bp periodicity in AA , TT , or AT dinucleotides favor wrapping of nucleosomes by reducing the bending energy of wrapping [58 , 59] . Lack of sequence conservation of centromeric repeats confirms that centromeres turn over quickly [37] , and will allow the functional characterization and investigation of centromere biology in this group . For the first time , we also assemble an entire Y chromosome using shotgun sequencing approaches . In particular , the recovered Y/neo-Y sequence is over 100 Mb large , which is over three times the size of that of its former homolog , the neo-X , or its autosomal ortholog in D . pseudoobscura . Thus , rather than shrinking—the fate that is typically ascribed to animal Y chromosomes—we find that early Y chromosome evolution instead is characterized by a global DNA gain . Large young Y chromosomes have been observed in plants , and like in D . miranda , their length increase is primarily due to an accumulation of repetitive DNA [60 , 61] . We show that the D . miranda Y chromosome provides a hodgepodge of sequences that have been male limited for different amounts of time , and display various stages of degeneration . The ancestral Y chromosome of Drosophila , on the other hand , has become linked to an autosome in D . miranda , and we reconstruct the genomic and epigenetic changes that occurred to revert this former Y to an autosome . Thus , our new highly improved genome assembly will provide the basis for further evolutionary and functional research on repetitive sequences and the recently formed neo-sex chromosomes of D . miranda .
We chose the inbred MSH22 strain for D . miranda , which was previously used to generate a BAC library [19] , and for genome assembly using short Illumina reads [20] . We used a mix of MSH22 males and extracted high molecular weight DNA using a QIAGEN Gentra Puregene Tissue Kit ( Cat #158667 ) , which produced fragments >100 kbp ( measured using pulsed-field gel electrophoresis ) . DNA was sequenced on the PacBio RS II platform . In total , this produced 28 Gb spanning 2 , 407 , 465 filtered subreads with a mean read length of 12 , 818 bp and an N50 of 17 , 116 bp ( S1 Table , S18 Fig ) . DNA was extracted from flash frozen male larvae . Purified DNA was embedded in a thin agarose layer and was labeled and counterstained following the IrysPrep Reagent Kit protocol ( BioNano Genomics ) . Samples were then loaded into IrysChips and run on the Irys imaging instrument ( BioNano Genomics ) . This produced 90 , 977 molecules ( molecule length: minumum 150 , 000 , median 191 , 400 , and maximum 1 , 957 , 000 and N50 of 209 , 014; S9 Table; S19 Fig ) . The IrysView ( BioNano Genomics ) software package was used to produce single-molecule maps and de novo assemble maps into a genome map ( S4 Table ) . The BioNano assembly has 401 contigs with an N50 of 0 . 5 Mb and assembled length of about 178 Mb . HybridScaffold was then used to produce hybrid maps from the BioNano contigs and the genomic scaffolds from our scaffolded PacBio assembly , and IrysView was used to visualize alignments of the BioNano contigs and genomic scaffolds to the hybrid ones . S4 Table shows coverage of hybrid scaffolds by BioNano contigs and NGS contigs ( genomic scaffolds ) . An initial PacBio assembly was built with the Falcon assembler [23] , using 40× error corrected reads . Twenty-eight-Gb of long reads ( NR50 = 17 , 116 bp; NR50 is the read length , such that 50% of the total sequence is contained within reads of this length or longer ) were assembled using Falcon assembler ( v1 . 7 . 5 ) [23] running on Sun Grid Engine in parallel mode . For assembly , reads longer than 10 kb and 17 kb were used as seed reads for initial mapping and preassembly . The options for read correction , overlap filtering , and consensus building were provided in the config file as follows: pa_HPCdaligner_option = -v -dal128 -t16 -e . 70 -l1000 -s1000; ovlp_HPCdaligner_option = -v -dal128 -t32 -h60 -e . 96 -l500 -s1000; pa_DBsplit_option = -x500 -s400; ovlp_DBsplit_option = -x500 -s400; falcon_sense_option = —output_multi—min_idt 0 . 70—min_cov 4—max_n_read 200—n_core 6; overlap_filtering_setting = —max_diff 30—max_cov 60—min_cov 5—n_core 24 . This assembly had 629 scaffolds and a total assembled length of 274 , 803 , 116 bp with an N50 value equal to 2 , 188 , 952 bp . We polished this assembly using the software Quiver [62] , followed by the software Pilon [63] , which resulted in an assembly with 625 scaffolds , with an N50 value of 2 , 232 , 625 bp and total assembled length equal to 271 , 223 , 447 bp . We also produced a second PacBio assembly using Canu [24] , with default parameters . This assembly consisted of 521 scaffolds and a total assembled length of 296 , 012 , 170 bp , with an N50 value of 3 , 884 , 273 bp . The Canu and the Falcon assemblies both contained some regions that were missing from the other one , and the two assemblies were merged using Quickmerge [25] , with default parameters . The resulting merged assembly was then merged a second time to the finished Falcon assembly , producing a superior Quickmerge assembly consisting of 271 scaffolds and total length equal to 295 , 213 , 648 bp and an N50 value of 5 , 177 , 776 bp . Hi-C libraries were created from sexed male and female third instar larvae of MSH22 , following [64] . Briefly , chromatin was isolated from male and female third instar larvae of D . miranda , fixed using formaldehyde at a final concentration of 1% , and then digested overnight with HindIII and HpyCH4IV . The resulting sticky ends were then filled in and marked with biotin-14-dCTP , and dilute blunt end ligation was performed for 4 hours at room temperature . Cross-links were then reversed , and DNA was purified and sheared using a Covaris instrument LE220 . Following size selection , biotinylated fragments were enriched using streptavidin beads , and the resulting fragments were subjected to standard library preparation following the Illumina TruSeq protocol . For females , 38 . 4 and 194 . 5 million 100-bp read pairs were produced for the HpyCH4IV and HindIII libraries , respectively . For males , 28 . 0 and 179 . 2 million pairs were produced . We mapped Illumina male and female genomic paired-end reads and classified contigs as autosomal , X-linked , or Y-linked based on genomic coverage . We created two pools of contigs: autosomes or X-linked , and Y-linked , and scaffolded them separately . We used Juicer [65] to align female Hi-C reads to the autosomal/X-linked scaffolds and also to align a subset of male Hi-C reads ( that did not map to autosomes ) to the Y-linked scaffolds . There were 22 , 168 , 695 Hi-C contacts: 2 , 921 , 250 interchromosomal and 19 , 247 , 445 intrachromosomal contacts for the autosomal/X-linked scaffolds . For the Y-linked scaffolds , there were 795 , 487 Hi-C contacts , including 173 , 147 interchromosomal and 622 , 340 intrachromosomal contacts . The output alignment files from Juicer were then used to scaffold the genome using 3D-DNA [66] . Using a custom Perl script , we then scaffolded the PacBio assembly fasta based on the 3D-DNA output suffixed . asm , which contains information about the positions and orientations of contigs; scaffolded contigs are gapped by 50 Ns . With the Hi-C scaffolded assembly , we then realigned the Hi-C reads using bwa mem [67] single-end mode on default settings . The resulting sam files were then used to generate a genome-wide Hi-C interaction matrix using the program Homer [68] . For visualization , we plotted the interaction matrix as a heatmap in R , with demarcations of the PacBio contigs and Hi-C scaffolds . Iteratively , we visually examine the heatmap to identify possible anomalies as scaffolding errors and manually curate the . asm file output to improve the heatmap . At each stage of the assembly process , genome completeness was assessed using BUSCO ( v 3 . 01 ) [29] , using the arthropod database ( odb9 ) . Bacteria were cultured in Terrific Broth with 25 μg/mL chloramphenicol . Overnight cultures ( 500 μL ) were inoculated with starter cultures grown from glycerol stocks , covered with AreaSeal films , and incubated at 37 °C with shaking for 12–14 hours . Overnight cultures were pelleted by centrifugation , resuspended in 60 μL [Tris-HCl ( 50 mM , pH 8 ) and EDTA ( 50 mM ) ] , and lysed by adding 120 μL [NaOH ( 200 mM ) and SLS ( 1% ) ] . Cells were incubated at room temperature for 5 minutes , 270 μL [KOAc ( 5 M , pH 5 ) ] was added and chilled on ice for 10 minutes , and then centrifuged for 1 hour . DNA was precipitated with isopropanol , washed with 70% and 80% ethanol and eluted in Qiagen EB ( 50 μL ) . Nextera libraries were prepared from the BAC DNA , following Illumina’s protocol with the following modifications: reaction volumes were scaled to 1 μL input BAC DNA ( @ 1–3 ng/μL ) , and SPRI bead cleanup steps after tagmentation and PCR amplification were skipped . Barcoded libraries were pooled , and a two-sided Ampure XP size selection removed fragments <200 bp and minimized fragments >800 bp . The pooled libraries were sequenced on a HiSeq 4000 with 100-bp paired-end reads . For each BAC clone , Nextera reads were first adapter trimmed using cutadapt ( http://code . google . com/p/cutadapt/ ) and filtered to remove concordantly mapping read pairs from pTARBAC-2 . 1 and E . coli DH10B using Bowtie2 [69]and SAMtools [70] . The remaining trimmed , filtered reads were mapped to our D . miranda assembly using bwa [67] . The BAC's location was determined by filtering regions of high coverage ( at least 50× mean ) and significant length ( at least 20 kb ) . First , regions with average coverage of at least 50× were extracted , and any regions within 250 kb of each other were merged using BEDtools [71] . When this resulted in a merged region longer than 250 kb , the merging step was repeated on this long region using a maximum distance of 5 kb . If only one region remained , this was defined as the putative BAC location . If multiple regions were found , they were ranked by average coverage , and any region with less than half the average coverage of the region with the highest average coverage was considered cross contamination . Finally , regions less than 20-kb long were removed . To confirm that reads mapping to these BAC locations included both edges of the BAC insert , we found discordantly mapping read pairs with one read mapping to the vector and its mate mapping to our assembly . Filtered reads were mapped to pTARBAC-2 . 1 using bwa [67] , and discordantly mapping reads from either end were filtered from the . sam file , keeping "start" and "end" reads separated ( reads mapping to a region within 4 , 000 bp of the vector's start position were considered "start" reads , and reads mapping within 4 , 000 bp of the vector's end position were considered "end" reads ) . The mates of these start/end reads were extracted , merged , and counted using BEDtools [71] and filtered to find edge read pileups within 10 kb of the putative BAC edges . To confirm that these edge reads are at either end of each BAC location , IGV snapshots with three tracks ( all mapped reads , "start" reads , and "end" reads ) were reviewed manually . To confirm that our assembly of the neo-X and neo-Y were highly specific and accurate , the genomic region on the neo-sex chromosome from which a specific BAC clone was derived was masked using BEDtools [71] , and the BAC clone reads were mapped back to this masked assembly and then filtered and merged , as described above . Regions of primary and secondary mapping were reviewed using IGV to confirm that little cross-mapping occurs in our assembly; after masking and remapping , we found significant mapping to homologous regions of its homologous neo-sex chromosome , but mapped reads typically contained many SNPs and many gapped regions ( S14 Fig ) . To identify large-scale , erroneously duplicated regions , we took advantage of the fact that when reads are mapped equally well to multiple regions , they are randomly assigned to one of the regions; we mapped Illumina reads to the assembly twice and identified >100-kb regions where roughly half of the reads map to another region in the two mappings ( see S4 Fig ) . For erroneous duplications and mis-scaffolded contigs in the PacBio assembly identified , we used IGV to visualize the quality of Illumina reads mapping , in order to determine the precise coordinates to modify our assembly ( S2 Table ) . For erroneous duplications , we identified the position in which Illumina reads are no longer uniquely mapping around the duplicated areas; one of the two duplications is then removed . Mis-scaffolded contigs are typically caused by misassembly around repetitive elements; therefore , we also relied on visual inspection of nonuniquely mapping reads to separate contigs . For the previously published genome assembly and the various intermediate assemblies produced here during generating the current version , we estimated quality statistics using the variant caller LUMPY [72] . To do this , we first aligned reads from two separate male Illumina libraries ( with 626-bp and 915-bp insert sizes , respectively ) to our current assembly and its intermediates using SpeedSeq , which does a BWA-MEM alignment and produces discordant and split reads bam files . We ran the software lumpyexpress [72] using these bam files , which produced a vcf file with several categories of structural variants: BND = trans-contig associations , DEL = deletions , DUP = Duplications , INV = Inversions . High numbers of these variants are indicative of potential assembly errors and provide a meaningful way to assess assembly quality . For repeat masking the genome , we annotated repeats using REPdenovo ( downloaded November 7 , 2016 [26] ) and RepeatModeler version 1 . 0 . 5 [27] . We ran REPdenovo on raw sequencing reads using the parameters MINREPEATFREQ 3 , RANGEASMFREQDEC 2 , RANGEASMFREQGAP 0 . 8 , KMIN 30 , KMAX 50 , KINC 10 , KDFT 30 , GENOMELENGTH 176000000 , ASMNODELENGTHOFFSET -1 , MINCONTIGLENGTH 100 , ISDUPLICATEREPEATS 0 . 85 , COVDIFFCUTOFF 0 . 5 , MINSUPPORTPAIRS 20 , MINFULLYMAPRATIO 0 . 2 , TRSIMILARITY 0 . 85 , and RMCTNCUTOFF 0 . 9 . We ran RepeatModeler with the default parameters . We used tblastn ( https://www . ncbi . nlm . nih . gov/BLAST/ ) with the parameters -evalue 1e-6 , -numalignments 1 , and -numdescriptions 1 to blast translated D . pseudoobscura genes ( release 3 . 04 ) from FlyBase [73] to both ( REPdenovo and RepeatModeler ) repeat libraries . We eliminated any repeats with blast hits to D . pseudoobscura genes . After filtering , our REPdenovo repeat annotation had 999 repeats totaling 964 , 435 base pairs . We also made a REPdenovo annotation using a subset of female reads , for which we also filtered out repeats blasting to D . pseudoobscura genes . This annotation had 716 repeats totaling 544 , 702 base pairs . We used RepeatMasker version 4 . 0 . 6 [27] and blastn ( https://www . ncbi . nlm . nih . gov/BLAST/ ) with the parameters -evalue 1e-6 , -numalignments 1 , and -numdescriptions 1 to blast this annotation to the Repbase Drosophila repeat annotation ( downloaded March 22 , 2016 , from www . girinst . org ) in order to classify repeats from this annotation . Our RepeatModeler repeat annotation had 1 , 009 repeats totaling 1 , 290 , 513 base pairs . Of the 1 , 009 repeats , 103 were annotated as DNA transposons , 145 as LINEs , 365 as LTR transposons , 42 as Helitrons , and 1 as a SINE . We concatenated our filtered REPdenovo and RepeatModeler repeat annotations to repeat-mask the genome with RepeatMasker [74] . To run Maker [28] , we first build transcriptome assemblies . RNA-seq reads from several adult tissues ( male and female heads , male and female gonads , male accessory gland , female spermatheca , male and female carcass , male and female whole body , and whole male and female third instar larvae; see S10 Table ) were aligned to the genome assembly using HiSat2 [75] , using default parameters and the parameter -dta needed for downstream transcriptome assembly . The alignment produced by HiSat2 was then used to build a transcriptome assembly using the software StringTie [76] with default parameters , which produced a transcript file in gtf format . Fasta sequences of the transcripts were then extracted using gffread to be used with Maker . The genome was repeat-masked using RepeatMasker and our de novo repeat library as well as the Repbase ( http://www . girinst . org/ ) annotation . We ran three rounds of Maker [28] to iteratively annotate the genome . For the first Maker run , we used annotated protein sequences from FlyBase for D . melanogaster and D . pseudoobscura as well as the de novo assembled D . miranda transcripts and the genes predictors SNAP [77] and Augustus [78] to guide the annotation . We used the SNAP D . melanogaster hmm and the Augustus fly model , with the parameters est2genome and protein2genome set to 1 in order to allow Maker to create gene models from the protein and transcript alignments . Before running Maker a second time , we first trained SNAP using the results of the previous Maker run and set the est2genome and protein2genome parameters to 0 . We then used our new hmm file and the Augustus fly model to annotate the genome . The third iteration was done similarly to the second one by training SNAP on the results of the previous Maker run . This procedure resulted in a total of 17 , 745 annotated genes . The repeat and gene densities were plotted for the major chromosomal arms and scaffolds using the software DensityMap [79] . We used TRF [38] on recommended settings to identify tandemly repeating motifs across the assembly . To identify variants or multimers of the same motif , the identified motifs are then blasted pairwise to themselves . Those that are over 90% identical for over 90% of the length are grouped together and collapsed into the same motif . Satellites’ abundances were parsed from the TRF output and RepeatMasker output using the identified motifs as the repeat library . Telomeric protein sequences for D . pseudoobscura and D . persimilis from [33] were aligned to the de novo repeat library using BLAST . Hits with a score greater than 50 and percent identity greater than 75 were classified as telomeric and RepeatMasker was used to identify their genomic locations . A heatmap showing the number of bases masked in 10-kb windows was then plotted along the genome using R . We identified orthologous proteins by aligning D . pseudoobscura proteins to our list of de novo annotated D . miranda proteins using BLAST and BLAT . For 16 , 378 of the total 17 , 745 genes in our annotation , we were able to reliably identify orthologs in the D . pseudoobscura annotation . We used blastp to align protein sequences of the remaining 1 , 367 genes to annotated D . melanogaster proteins and were able to identify D . melanogaster orthologs for 285 of these 1 , 367 genes . Thus , we were unable to identify orthologs for 1 , 082 genes in both the D . pseudoobscura and the D . melanogaster genome . Whole genome alignments were performed using Nucmer ( from the MUMmer package [80] ) and dot plots were produced using mummerplot , symap42 [81] , or YASS [82] . Scaffolds from a male-only D . pseudoobscura assembly were aligned to a female-only D . pseudoobscura assembly using Nucmer ( from the MUMmer package [80] ) to identify scaffolds only present in the male assembly ( i . e . , putative Y-linked scaffolds ) . Male Illumina reads were then aligned to these scaffolds using bowtie2 [69] and unaligned reads were discarded . The aligned reads were then mapped to the female genome and any reads that mapped were discarded to further enrich for only male-specific reads . These reads were then mapped to the D . miranda Y/neo-Y-linked scaffolds , and coverage was calculated in 10-kb nonoverlapping windows . The density of nonzero coverage windows was plotted along the three largest Y scaffolds .
|
Y chromosomes determine the gender in many species , but their molecular investigation has been hampered by a lack of high-quality sequence assemblies . Here , we create a genome assembly of unprecedented quality and contiguity for the fruit fly Drosophila miranda , a model for Y chromosome research , which allows us to reconstruct the evolutionary events that create and dismantle sex chromosomes . Our assembly recovers entire chromosomes and notoriously difficult regions to assemble , including entire centromeres , large repetitive gene families embedded in heterochromatin , and more than 100 Mb of the highly repetitive and heterochromatic Y chromosome . We identify the putative centromeric repeat in this species , which shows no sequence homology to centromere motifs of other Drosophila species . The recovered Y/neo-Y sequence is over three times the size of its former homolog , the neo-X , challenging a paradigm of sex chromosome evolution: rather than shrinking—the fate that is typically ascribed to Y chromosomes—we find that early Y evolution is instead characterized by a global DNA gain . The ancestral Y chromosome of Drosophila , by contrast , has become linked to an autosome in D . miranda , and we reconstruct the genomic and epigenetic changes that likely occurred to revert this former Y to an autosome .
|
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2018
|
De novo assembly of a young Drosophila Y chromosome using single-molecule sequencing and chromatin conformation capture
|
Bang sensitive ( BS ) Drosophila mutants display characteristic seizure-like phenotypes resembling , in some aspects , those of human seizure disorders such as epilepsy . The BS mutant parabss1 , caused by a gain-of-function mutation of the voltage-gated Na+ channel gene , is extremely seizure-sensitive with phenotypes that have proven difficult to ameliorate by anti-epileptic drug feeding or by seizure-suppressor mutation . It has been presented as a model for intractable human epilepsy . Here we show that cacophony ( cacTS2 ) , a mutation of the Drosophila presynaptic Ca++ channel α1 subunit gene , is a particularly potent seizure-suppressor mutation , reverting seizure-like phenotypes for parabss1 and other BS mutants . Seizure-like phenotypes for parabss1 may be suppressed by as much as 90% in double mutant combinations with cacTS2 . Unexpectedly , we find that parabss1 also reciprocally suppresses cacTS2 seizure-like phenotypes . The cacTS2 mutant displays these seizure-like behaviors and spontaneous high-frequency action potential firing transiently after exposure to high temperature . We find that this seizure-like behavior in cacTS2 is ameliorated by 85% in double mutant combinations with parabss1 .
Human seizure disorders are a substantial neurological health problem because of the large number of affected individuals , and heterogeneity underlying the many syndromes . An estimated 1% of the U . S . population , nearly 3 million Americans , is affected by the more than 40 different syndromes that comprise the epilepsies [1 , 2] . Seizures occur because of an imbalance in excitation and inhibition: excitation can be excessive , inhibition can be inadequate , or both . The resulting seizure activity involves large numbers of neurons firing uncontrollably and synchronously , usually in a rhythmic pattern . Multiple and different molecular aspects of electrical signaling appear to be responsible for the triggering of seizures at the site of initiation or focus , their subsequent spread from the focus to adjacent regions of nervous tissue , and their eventual termination . In this study , we examine the contribution of basic synaptic transmission to seizure-susceptibility in a Drosophila model using mutations of the cacophony ( cac ) gene , responsible for neurotransmitter release . The cac gene encodes the α1 subunit of the Drosophila voltage-gated presynaptic Ca++ channel , homologous to the mammalian N-type channel [3–7] . The allele used here , cacTS2 , shows conditional and reversible phenotypes dependent on temperature: a behavioral paralysis phenotype and a loss of neurotransmitter release phenotype [5–7] . At restrictive high temperatures , evoked synaptic currents are markedly reduced in cacTS2 mutants , returning to wild-type levels when temperature is lowered to permissive temperatures . We report here that the cacTS2 mutation affects seizure susceptibility in complex ways including seizure-sensitivity and seizure-resistance , under different conditions . As reported [8] , cac temperature-sensitive mutants display spontaneous seizure-like activity when shifted to restrictive temperature . We find here that at permissive temperature , cacTS2 is a seizure-resistant mutation and a potent seizure-suppressor . In double mutant combinations with bang-sensitive ( BS ) seizure-sensitive mutants , cacTS2 is one of the strongest seizure-suppressors that we have identified in the fly , to date . In particular , the cacTS2 mutation is found to ameliorate seizure-like phenotypes in homozygous parabss1 , a Na+ channel gain-of-function mutation , the most severe of Drosophila seizure-sensitive mutations [9 , 10] and resembling , in some aspects , Na+ channel loss-of-function mutations responsible for intractable epilepsy [11 , 12] . The cacTS2 mutation is a good suppressor of parabss1 phenotypes comparable to malelessnapts and stronger than heat-treated shibirets1 and gilgamesh ( Table 1 ) [13 , 14 , 15 , 16] . At restrictive temperatures , cacTS2 exhibits complex phenotypes including TS seizure-like activity , synaptic failure and paralysis . We found that all cacTS2 phenotypes are reciprocally suppressed in double mutant combination with parabss1 . Suppression of TS seizure-like behaviors in cacTS2 by a Na+ channel mutation indicates that the combination of two ion channel alleles involved in epilepsy can have beneficial clinical effects when present in the same individual organism: that is , each of the two mutations co-suppresses seizures caused by the other , similar to observations reported for mouse [17] .
The behaviors of cacTS2 mutants are unexceptional at room temperature ( 24°C ) : feeding , grooming , and mating behaviors appear normal . Overall activity levels are unaltered: flies are neither sluggish nor hyperactive . The cacTS2 mutants show no bang-sensitive ( BS ) behavioral paralysis phenotype and are unaffected by mechanical stimulation . Using the adult giant fiber ( GF ) neurocircuit as a proxy for holo-nervous system function , the electrophysiology phenotype for cacTS2 at room temperature generally resembles wild-type [18] . Thus , single pulse stimulation of the GF produces evoked potentials and synaptic currents in the dorsal longitudinal muscle ( DLM ) that are normal in appearance ( S1 Fig ) [5] , have a threshold of 0 . 96 ± 0 . 12 V ( mean ± s . e . m . , n = 9 ) and a latency of 1 . 1 ± 0 . 04 msec ( mean ± s . e . m . , n = 5 ) . Seizure-like electrical activity in cacTS2 mutants can be evoked with high-frequency stimuli ( HFS; 0 . 5 msec stimuli at 200 Hz for 300 msec; Fig 1A ) , similar to discharges observed for other Drosophila mutants [19 , 20] . Large HFS voltages were characteristically required to evoke seizures at room temperature indicating that cacTS2 behaves as a seizure-resistant mutant . Seizure threshold for cacTS2 was ( 58 . 3 ± 1 . 0 V HFS , mean ± s . e . m . , n = 13 ) , nearly twice that of Canton-Special wild type flies ( 24 . 64 ± 2 . 83 HFS , mean ± s . e . m . , n = 10; Fig 1A–1C ) . The seizure threshold for cacTS2 is comparable to previously-reported seizure-resistant mutants such as paralyticts1 , ShakerKS133 and shakingB2 that have high seizure thresholds and can also act as seizure-suppressor mutations in double mutant combinations with BS mutants [19] . Several cac alleles , especially cacTS2 and cacNT27 , are notable for their temperature-sensitivity ( TS ) with essentially normal behavior and neurology at room temperature which is permissive; and displaying complicated neurological phenotypes at high temperature ( >38°C ) which is restrictive [5 , 8] . The shift from permissive to restrictive temperature , causes a transient period of nervous system hyperexcitability lasting several seconds [8] , followed by a prolonged period of hypoexcitability with synaptic failure and behavioral paralysis [5] . The hyperactive period is characterized by spontaneous seizure-like behaviors: leg-shaking , abdominal twitching , wing scissoring , and proboscis extensions . These are accompanied by spontaneous seizure-like firing of the DLM motor neurons in electrophysiology recordings ( Fig 1D ) , similar to that described previously [8] . Seizure-like activity for cacTS2 at elevated temperature is interesting considering the seizure-resistant phenotype observed at room temperature . The spontaneous seizure-like DLM activity generally resembles that observed during evoked seizure-like activity ( Fig 1 ) . We were unable to determine a reliable evoked seizure-threshold for cacTS2 at restrictive temperature . Immediately following the shift to restrictive temperature , the seizure-threshold is still high , resembling the threshold of cacTS2 at room temperature . Spontaneous seizure-like activity ensued soon after the shift to restrictive temperature and their nearly continuous occurences made it difficult to distinguish them from stimulus-evoked seizures . Taken together , these findings indicate that cacTS2 is apparently a seizure-resistant mutant at room temperature , changing to a seizure-sensitive mutant after shift to restrictive temperature . In order to test for genetic interactions , we constructed double mutants between cacTS2 and different BS mutants . This resulted in suppression of the BS phenotype as exemplified by hemizygous double mutant male flies cacTS2/Y;;sda that showed 12% behavioral BS paralysis ( indicating 88% phenotypic suppression , n = 147; P < 0 . 0001 , chi- square test; Fig 2A; Table 1 ) at room temperature ( 24°C ) , compared to the sda single mutant control flies which showed 100% BS paralysis ( P < 0 . 0001 ) . This finding of suppression at room temperature was a little unexpected since cacTS2 has previously been described as a temperature-sensitive mutation and permissive temperature phenotypes have not been reported . This result may be related to the observation above that cacTS2 is seizure-resistant at room temperature; heretofore the only other difference from wild type that we have seen at room temperature . In order to examine if temperature has an effect on BS suppression , we examined double mutants at elevated temperatures within the nominally permissive range , that is below 38°C , to avoid cacTS2 behavioral paralysis . We found that seizure-suppression by cacTS2 is increased at elevated temperatures . In hemizygous double mutant flies cacTS2/Y;;sda , a brief heat shock ( HS; 3 min at 30°C ) , completely suppressed all sda bang-sensitivity ( 0% paralysis , 100% suppression , n = 93; P < 0 . 0001 , chi-square test; Fig 2A; Table 1 ) . A similar brief HS delivered to control single mutant sda flies had no effect on bang-sensitivity: 100% of control flies continued to show BS paralysis ( P < 0 . 0001 ) . The cacTS2 mutation is a general seizure-suppressor , not limited to suppression of BS phenotypes in sda mutants: modest seizure-suppression is also observed for eas mutants . In hemizygous double mutant male flies eas cacTS2/Y , BS was 90% ( 10% suppression , n = 147; P = 0 . 0002 , chi- square test; Fig 2B; Table 1 ) at room temperature compared to 100% BS in eas single mutant controls . In eas , suppression by cacTS2 was also increased with exposure to elevated temperature . In hemizygous double mutant flies eas cacTS2/Y , bang-sensitivity was 54% ( 46% suppression , n = 93; P = < 0 . 0001 , chi-square test; Fig 2B; Table 1 ) following a brief HS ( 3 min at 30°C ) . HS had no effect on the bang sensitivity of eas single mutant control flies: 100% of the control flies showed BS paralysis ( P < 0 . 0001 ) . Thus , cacTS2 acts as a general suppressor of BS behavior , reverting phenotypes of both sda and eas BS mutants in double mutant combinations . Some suppression occurs at room temperature , although suppression increases with increases in temperature within the permissive temperature range . Previous studies have also shown that BS phenotypes in sda mutants are easier to suppress than for eas mutants [21 , 22] . We investigated genetic interactions between cacTS2 and parabss1 by constructing the appropriate double mutant combinations . Previous studies have found that seizure-like phenotypes are difficult to suppress in parabss1 mutants , that carry a gain-of-function voltage-gated Na+ channel defect [10 ( Table 2 ) ] . We find here that cacTS2 is an effective suppressor of parabss1 behavioral phenotypes . For hemizygous double mutant males ( genotype: parabss1 cacTS2/Y ) , BS paralysis was 36% ( 64% suppression; n = 658; P < 0 . 0001 , chi-square test ) at room temperature ( Fig 2C; Table 1 ) . Suppression by cacTS2 was also increased at elevated temperature . After a brief HS , BS paralysis decreased to 13% ( 87% suppression; n = 650; P < 0 . 0001 , chi-square test ) in hemizygous double mutants ( Fig 2C; Table 2 ) . Homozygous double mutant females ( genotype: parabss1 cacTS2 ) showed 23% BS paralysis at room temperature ( 77% suppression ) which decreased to 8% ( 92% suppression ) following HS ( Table 2 ) . In control parabss1 flies , there was no effect of HS: 100% of flies showed BS paralysis ( P < 0 . 0001; Table 2 ) . The cacTS2 mutation is an especially effective suppressor of parabss1/+ heterozygote behavioral phenotypes . In double mutant flies ( genotype: parabss1 cacTS2/para+ cacTS2 ) BS paralysis was 2% ( 98% suppression ) at room temperature , compared to 62% BS paralysis seen in control parabss1/+ heterozygotes without the cacTS2 suppressor ( n = 60; P < 0 . 0001 , chi-square test; Fig 2D; Table 2 ) . The salient consequence of cacTS2 suppression is the increased percentage of flies escaping BS paralysis , but flies that undergo paralysis are also influenced by the suppressor: observed as a reduction in the time required for recovery . Control parabss1/Y mutant males when paralyzed ordinarily have a long recovery time 195 sec . In contrast , paralyzed flies carrying the suppressor ( genotype: parabss1 cacTS2/Y ) have about a four-fold reduction in the time to recovery 46 sec ( n = 45; P < 0 . 0001 , unpaired student t-test ) . Moreover , cacTS2 reduced the refractory time period for hemizygous double mutant male flies parabss1 cacTS2/Y . Double mutants show a shorter refractory time period of 17 min , compared to 25 min for parabss1 single mutant flies ( n = 34; P = 0 . 0005 , unpaired student t-test ) . Seizure suppression by cacTS2 is also observed in evoked seizure-like neuronal activity recorded electrophysiologically . This analysis shows an unusual seizure-suppression of parabss1 by cacTS2 . Immediately following HS , there is considerable suppression of parabss1 ( Fig 3A–3D ) , but this suppression is transient and short-lasting ( Fig 3D ) . Thus , immediately following the HS ( 3 min at 30°C ) , seizure-threshold for parabss1 cacTS2 double mutants is high ( 51 . 6 ± 1 . 2 V HFS , mean ± s . e . m . , n = 7; P < 0 . 0001 , ANOVA test; Fig 3D ) . This is greater than the seizure threshold for the parabss1 by about a factor of ten , and greater than wild type seizure-threshold , by nearly a factor of two; flies with seizure-thresholds in this range are seizure-resistant mutants ( Table 3 ) [14] . Seizure-threshold quickly decreases when maintained at room temperature and the steady-state seizure-threshold of parabss1 cacTS2 double mutants at room temperature is ( 3 . 82 ± 0 . 2 V HFS , mean ± s . e . m . , n = 10 ) , similar to the parabss1 single mutant ( 3 . 2 ± 0 . 1 V HFS , mean ± s . e . m . , n = 8; Fig 3A ) . The time course of the threshold change is difficult for us to determine with our present electrophysiology protocols , but it appears similar to changes in BS behavior following HS , about 5–7 min . Electrophysiology analysis also shows cacTS2 suppression of other BS mutants . The cacTS2;;sda double mutant has a seizure-threshold of ( 20 . 5 ± 2 . 42 V HFS , mean ± s . e . m . , n = 7 ) following HS and tested at room temperature , about 3-fold higher than the threshold of the sda single mutant ( 6 . 2 ± 0 . 3 V HFS , mean ± s . e . m . , n = 5 , P < 0 . 0001 , unpaired student t-test; Fig 3E ) . That is , in the double mutant , there is a reversion of BS electrophysiology by cacTS2 to nearly the wild-type range of seizure-threshold . The cacTS2 mutation also suppresses eas seizure-like activity . Hemizygous double mutant flies eas cacTS2/Y have a seizure-threshold of ( 8 . 7 ± 1 . 1 V HFS , mean ± s . e . m . , n = 11 ) following HS , about two-fold higher than the low threshold of the eas single mutant ( 3 . 8 ± 0 . 1 V HFS , mean ± s . e . m . , n = 6; P < 0 . 01; unpaired student t-test; Fig 3D; Table 3 ) . To further study cac seizure-suppression , we generated loss-of-function cac genotypes using cacRNAi to knockdown cac expression; these were tested for BS mutant suppression . Flies utilizing a pan-neuronal GAL4 driver and one copy of cacRNAi were viable and had largely normal behavior . Similar to the cacTS2 mutation , cacRNAi suppressed BS behavioral phenotypes in double mutant male parabss1 flies . Males ( genotype: elavc155-GAL4 parabss1/Y;;UAS-cacRNAi/+ ) showed BS paralysis in 64% of flies ( 36% suppression; n = 212; P < 0 . 0001 , chi-square test; Fig 4A ) at room temperature . Suppression of BS by cacRNAi was more effective in eas mutants . Males ( genotype: elavc155-Gal4 eas/Y;;UAS-cacRNAi/+ ) showed BS paralysis in 15% of flies ( 85% suppression , n = 74; P < 0 . 0001 , chi- square test; Fig 4B ) . Although cacRNAi was effective at suppressing BS phenotypes , in other respects it was different than cacTS2 mutations because it did not cause temperature-sensitive phenotypes . Thus , male cacRNAi flies ( genotype: elavc155-GAL4/Y;;UAS-cacRNAi/+ ) at 38°C showed netiher spontaneous seizure-like behaviors no behavioral paralysis . Double mutant parabss1 cacTS2 flies were examined following a temperature shift from room temperature to 38°C , the restrictive temperature for cacTS2 . Interestingly , some temperature-sensitive phenotypes , prominent in the cacTS2 single mutant , were reduced in the double mutant , apparently suppressed by the presence of parabss1 in the double mutant combination . In parabss1 cacTS2 flies the TS spontaneous seizure-like electrophysiological phenotype was greatly reduced ( Fig 5A and 5B ) . Electrophysiological recordings from cacTS2 single mutants show the number of spontaneous seizure-like discharges was 10 ± 1 spontaneous discharges/HS ( mean ± s . e . m . , n = 10; HS = 3 min at 38°C . Fig 5A and 5C ) . In contrast , recordings from parabss1 cacTS2 double mutants show 2 . 5 ± 0 . 42 spontaneous discharges/HS ( mean ± s . e . m . , n = 20 , P = 0 . 0003 , unpaired student-t test; Fig 5B and 5C ) . In addition to the number of spontaneous discharges being reduced , there also appeared to be a reduction in discharge duration ( Fig 5A and 5B ) . The temperature-sensitive behavioral paralysis phenotype of cacTS2 was also suppressed by parabss1 ( Fig 5D ) . For the cacTS2 single mutant , 100% of flies undergo paralysis when the temperature is increased from room temperature to 38°C , as described in previously [5] . In contrast , for parabss1 cacTS2 double mutants , only 20% of flies are paralyzed at 38°C ( 80% suppression , n = 76; P < 0 . 001 , chi-square test , Fig 5D ) .
We find that cacTS2 is a general seizure-suppressor mutation , reverting neurological phenotypes of several BS mutants: sda , eas , and parabss1 . Suppression of parabss1 is especially notable because it is a BS mutant that has previously been difficult to modify by suppressor mutation [21 , 22] or antiepileptic drug [23–27] . Recently , directed efforts to target parabss1 by suppressors have identified two: gilgamesh ( gish ) and shibirets ( shits ) , although both appear somewhat weaker than cacTS2 [15–16 ( Table 1 ) ] . Suppression by gish is unusual because it is selectively effective against parabss1/+ heterozygotes; gish does not suppress homozygous parabss1 . Also , gish does not suppress other BS mutants , such as sda or eas . [16] . For shits , suppression of parabss1 is not evident at room temperature , but occurs with increased temperature that causes interference with endocytosis during synaptic vesicle recycling [15] . BS suppression reported here for cacTS2 is comparable or better than for gish and shits . The major questions arising from this study are: how does cacTS2 suppression work ? And what is it about the cacTS2 mutation that makes it such an effective suppressor of parabss1 primary phenotypes , BS behavior and seizure threshold ? A complete answer to these questions remains unclear from the experiments we are able to perform here , but leads to speculation about mechanisms of seizure , and about how seizure-suppression might be accomplished . The cacTS2 allele behaves as a recessive loss-of-function mutation with reduced neurotransmitter release at the neuromuscular junction and paralysis at high temperature [5] . Also at high temperature , the mutant displays considerable spontaneous seizure-like activity seen in muscle fiber recordings [8] . At first , it might appear that this seizure-like activity is inconsistent with the cacTS2 phenotype of reduced transmitter release , especially if this reflects an overall reduction in excitability . The cacTS2 seizure-like activity must be due to spontaneous action potential bursting in adult and larval motor neurons; the activity recorded in the muscle fiber is reflecting seizure-like motor neuron firing . We suggest that this motor neuron firing may be due to a loss of inhibitory synaptic activity impinging on them , possibly causing some type of post-inhibitory rebound excitation within the motor neurons . That is , as excitatory transmitter reduction by temperature is observed at the neuromuscular junction , synaptic inhibition that ordinarily limits motor neuron firing is concurrently reduced leading to spontaneous seizure-like activity observed in muscle . About fifteen mutations have been identified previously as seizure-suppressors [reviewed in 22] . Some of these suppressors encode well-studied gene products that have not heretofore been associated with neuronal signaling or membrane excitability such as the de-ubiquitinase USP9X [28] and DNA topoisomerase I [29] . Some of the seizure-suppressor genes encode neuronal signaling molecules that have allowed us to consider previously three likely mechanisms for how seizure-like activity might be suppressed by second-site mutations; here , suppression by cacTS2 suggests to us a fourth mechanism . Previously , we found that: The signaling molecules responsible for the process of chemical synaptic transmission are a potentially rich source for identifying seizure-suppressor mutations . Seizure-suppressors are most logically expected from among mutations enhancing inhibitory GABAergic synaptic transmission or mutations diminishing excitatory cholinergic transmission . Some other mutations are most logically expected to enhance seizure phenotypes such as mutations decreasing GABAergic function or enhancing cholinergic transmission . It is more difficult to anticipate the effect on seizures of mutations affecting general synaptic transmission properties , that is , molecules that are common to both excitatory and inhibitory synaptic processes . The cacTS2 mutation examined here is such a mutation , the cac gene encodes the α1 , primary structural subunit of the voltage-gated Ca++ channel responsible for triggering regulated synaptic vesicle release at both excitatory and inhibitory synapses [4 , 34] . Thus , it was surprising that cacTS2 was not only a seizure-suppressor mutation , it was one of the most effective suppressors that we have identified . Because of this , we propose that cacTS2 suppression may work via a somewhat different mechanism than we have observed previously , generally , using neurocircuitry to cause seizure suppression . We presume that the suppression works by interfering with chemical synaptic transmission in many or most circuits in the fly . Modest interference in synaptic transmission at room temperature is sufficient to suppress weak BS mutants , such as sda . Stronger disabling of synaptic transmission following a heat pulse is necessary to suppress the stronger BS parabss1 . We thought it possible to identify specific circuits responsible for suppression by the differential GAL4/UAS expression of cacRNAi . Our initial attempts expressed cacRNAi selectively in excitatory interneurons ( cha-GAL4 driver ) , or inhibitory interneurons ( GAD-GAL4 driver ) . Expression of cacRNAi in different interneuronal populations was a little less effective than pan-neuronal expression , but differences were small ( S2 Fig ) . From this limited investigation , we do not find indications for specific circuits suppressing seizures or , if they exist , how we might go about discovering them . We entertain the interesting possibility that cac suppression may not be due to the disabling of particular circuits , but is a general block of seizure-like activity by an overall poorly-transmitting nervous system . It remains surprising that such a putative mechanism of seizure-suppression would be especially effective at reverting parabss1 seizure phenotypes which are severe . The cac gene is one of the most interesting Drosophila neurological genes . The gene is predicted to encode 15 annotated transcripts and 14 unique polypeptides . Numerous mutations have been identified ( 72 alleles ) and functions ascribed to different subsets of cac mutations [35–37] . Male courtship song alteration is one of the canonical phenotypes of cac exemplified by the original cacS mutation . Subsequently cacTS2 and cacNT27 were also shown to have alterations in courtship song [37] . All of the mutations in this subset show motor defects , seizure-like activity , and behavioral paralysis . These mutations and several other cac alleles in this subset all fail to complement each other . The cacTS2 mutation is due to a mis-sense mutation that is thought to alter Ca++-dependent inactivation [38] . Thus , although cacTS2 is recessive , it could behave as a gain-of-function mutation . Nevertheless , RNAi experiments presented here show that cac loss-of-function can cause seizure-suppression . However , flies carrying cacRNAi show neither seizure-like activity nor paralysis , suggesting these phenotypes could be due to gain-of-function phenotypes of cacTS2 . These issues remain to be determined in future experiments . Another interesting finding in this study is the co-suppression by parabss1 of the cacTS2 spontaneous seizure-like phenotype induced by high temperature . We presume that this must be due to a loss of spontaneous motoneuron spiking , since activity in the DLM muscle fiber reflects post-synaptic potentials from neuromuscular transmission . The mechanism responsible for this loss of motoneuron spiking is unclear; there are not previously described functions of parabss1 that easily account for it . The parabss1 sodium channel mutation causes gain-of-function phenotypes and leads to hyper-excitability in neurons . It is this hyper-excitability that makes parabss1 mutants more prone to seizures . The cacTS2 mutation causes a less functional Ca2+ channel and hence a decrease in release of neurotransmitter . So , bringing two defective ion channels with different effects on membrane excitability effects leads to the suppression of epilepsy . This Drosophila suppression resembles seizure-suppression findings in mice [17] . Double mutant mice carrying mutations in two epilepsy genes , Cacna1and Kcna1a showed improvement in both absence epilepsy and limbic seizure phenotypes caused by these mutations [17] .
Drosophila strains were maintained on standard cornmeal-molasses agar medium at room temperature ( 24°C ) . The cacophony ( cac ) gene is located on the X chromosome at 10F-11A on the cytological map and encodes a voltage-gated Ca++ channel α1 subunit implicated in neurotransmitter release [3–8] . The cacTS2 allele is a recessive mutation caused by a substitution ( P1385S ) at the C-terminus [4] . This position is adjacent to an EF hand motif thought to be involved in calcium dependent inactivation . The cacTS2 mutation causes temperature-sensitive paralysis: apparently due to a reduction , and then loss of synaptic current as the temperature is raised from permissive to restrictive values [4] . The paralytic ( para ) gene is located at map position 1–53 . 5 and encodes a voltage-gated Na+ channel [39–40] . The allele use here is a bang-sensitive ( BS ) paralytic mutation , parabss1 , previously named bss1[14] It is the most seizure-sensitive of fly mutants , the most difficult to suppress by mutation and by drug , and has been proposed as a model for human intractable epilepsy [10] . The parabss1 allele is a gain-of-function mutation caused by the substitution ( L1699F ) of a highly conserved residue in the third membrane-spanning segment ( S3b ) of homology domain IV [10] . The easily shocked ( eas ) gene is located at 14B on the cytological map and encodes an ethanolamine kinase [41] . The BS allele used in this study is easPC80 , which is caused by a 2-bp deletion that introduces a frame shift; the resulting truncated protein lacks a kinase domain and abolishes all enzymatic activity [22] . The slamdance ( sda ) gene is located at 97D and encodes an aminopeptidase N . The allele used in this study is sdais07 . 8 caused by a 2-bp insertion in the 5’ untranslated region [42] . The UAS-cacRNAi line was obtained from Bloomington Drosophila Stock Center . The insert for UAS-cacRNAi is located on the 3rd chromosome . The double mutants used in this study were constructed by standard genetic crosses and then verified for the presence of both the BS mutation ( sda , eas or parabss1 ) , as well as cacTS2 . The presence of cacTS2 in the homozygous double mutant stock was verified by testing for behavioral paralysis after heat shock ( 37°C for 5 min ) , which is characteristic for this mutation; BS mutants do not paralyze under such conditions . The presence of the homozygous BS mutation in the double-mutant stocks was verified by backcrossing each double mutant stock to females of the appropriate BS genotype . The progeny from those crosses , which should be homozygous for the BS mutation and heterozygous for cacTS2 , were then tested for the BS behavioral phenotype . All of the genotypes arising from the back cross phenotypically resembled BS homozygous flies . The lack of any obvious effects among the different genetic backgrounds tested also indicated the alterations in seizure-sensitivity reported here were due to the homozygous presence of cacTS2 in the double mutant combinations and not likely due to nonspecific genetic background differences . Behavioral testing for BS paralysis was performed on flies 3d after eclosion , as described previously [16] . Flies were anesthetized with CO2 before collection and tested the following day . For testing , 10 flies were placed in a clean food vial and stimulated mechanically with a VWR vortex mixer at maximum speed for 10 s . The parabss1 , eas , and sda mutants ordinarily show 100% penetrance of BS paralytic behavior with this test . Suppression by cacTS2 was initially manifest as a reduced percentage of BS behavioral paralysis in the double mutant compared to the single BS mutant . Recovery from BS paralysis was determined by counting the number of flies standing at different intervals following stimulation . Recovery time was the time at which 50% of flies had recovered from paralysis . For genotypes that display partial penetrance of BS paralysis , only those flies that displayed paralysis were used for recovery time analysis . For BS behavioral analysis , pools of flies are combined for each genotype from among the separate trials ( in total , n ≈ 100 for each genotype ) . For analyses using heat shock ( HS ) , a single fly was placed in a clean food vial and tested the following day . The vial was submerged in a water bath ( 30°C for 3 min ) , rested at room temperature ( 24°C for 30 seconds ) , and then tested for BS behavioral paralysis . For construction of double mutant stocks , flies were tested similarly for the presence of the cacTS2 mutation except that water bath temperature was 37°C , and the assay was temperature-sensitive behavioral paralysis . In vivo recording of seizure-like activity and seizure threshold determination in adult flies was performed as described previously [16] . Flies 2–3 days post-eclosion were mounted in wax on a glass slide , leaving the dorsal head , thorax , and abdomen exposed . Stimulating , recording , and ground metal electrodes were made of uninsulated tungsten . Seizure-like activity was evoked by high-frequency electrical brain stimulation ( 0 . 5 msec pulses at 200 Hz for 300 msec ) and monitored by dorsal longitudinal muscle ( DLM ) recording . During the course of each experiment , the giant fiber ( GF ) circuit was stimulated by single-pulse electrical brain stimulation and monitored continuously as a proxy for holobrain function . For each genotype tested n ≥ 10 . Chi-square tests were used to compare the penetrance of seizures . Student’s t-test and ANOVA were used to compare recovery times and seizure thresholds across genotypes , as appropriate . For ANOVA analysis , where the null hypothesis was rejected by the overall F ratio , multiple comparisons of data sets were performed by Fisher’s least significant difference with t-test significance set at P < 0 . 05 . For Figures ( 1–3 and 5 ) error bars represents standard error of the mean , and statistical significance is indicated by * P < 0 . 01 , ** P < 0 . 001 and *** P < 0 . 0001 .
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Seizure disorders , such as epilepsy , are a serious health concern because of the large number of patients affected and a limited availability of treatment options . About 10% of the population will have at least one seizure during their lifetime , and 1% will experience persistent , recurrent epileptic seizures . Moreover , for about one-third of patients , epilepsy is intractable with seizures that are not controlled with any available drugs . Genetic seizure suppressors are modifier mutations that are capable of reverting seizure susceptibility to wild type levels when combined with seizure-prone mutants in double mutant individuals . Suppressors are valuable in providing an experimental approach that can provide insight into mechanisms underlying seizure susceptibility . Also , they identify novel gene products that may be targets for therapeutic drug development . In the present study we show that a severe seizure phenotype of the Drosophila paralyticbss1 ( parabss1 ) mutant is 90% suppressed by the N-type calcium channel mutation cacophonyTS2 ( cacTS2 ) . The effect of suppression is not restricted to parabss1 , but cacTS2 can also revert seizure-like phenotypes of other Drosophila mutants like easily-shocked ( eas ) and slamdance ( sda ) . Thus , cacTS2 acts as a highly potent , general seizure suppressor mutation . A surprising finding in this study is co-suppression: parabss1 also suppresses a seizure phenotype in cacTS2 mutants induced by elevated temperature . A current view of complex diseases such as epilepsy , is that multiple genes and environmental factors can each contribute small , additive effects that can summate to produce a disease state when some threshold value is exceeded . Our findings indicate that different pathogenic ion channel mutations can sometimes form therapeutic combinations with effects that mask one another .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2016
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Mutations of the Calcium Channel Gene cacophony Suppress Seizures in Drosophila
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The study of processes evolving on networks has recently become a very popular research field , not only because of the rich mathematical theory that underpins it , but also because of its many possible applications , a number of them in the field of biology . Indeed , molecular signaling pathways , gene regulation , predator-prey interactions and the communication between neurons in the brain can be seen as examples of networks with complex dynamics . The properties of such dynamics depend largely on the topology of the underlying network graph . In this work , we want to answer the following question: Knowing network connectivity , what can be said about the level of third-order correlations that will characterize the network dynamics ? We consider a linear point process as a model for pulse-coded , or spiking activity in a neuronal network . Using recent results from theory of such processes , we study third-order correlations between spike trains in such a system and explain which features of the network graph ( i . e . which topological motifs ) are responsible for their emergence . Comparing two different models of network topology—random networks of Erdős-Rényi type and networks with highly interconnected hubs—we find that , in random networks , the average measure of third-order correlations does not depend on the local connectivity properties , but rather on global parameters , such as the connection probability . This , however , ceases to be the case in networks with a geometric out-degree distribution , where topological specificities have a strong impact on average correlations .
Analyzing networks of interacting elements has become the tool of choice in many areas of biology . In recent years , network models have been used to study the interactions between predator and prey [1] , gene interactions [2] and neural network dynamics [3 , 4] . A fundamental question in the study of complex networks is how the topology of the graph on which a dynamic process evolves influences its activity . A particularly interesting issue is the emergence of synchronized , or correlated patterns of events . While it is obvious that the presence or absence of such patterns of activity depends largely on how individual nodes in the network are connected , it is by no means a trivial task to explain exactly how this happens . In theoretical neuroscience , the connection between network topology and correlated activity continues to be an important topic of study . Not only are correlations between neuronal spike trains believed to have an important function in information processing [5 , 6] and coincidence detection [7] , but they are also believed to be tied to expectation and attention ( see [7] for details ) . In addition , it been shown that nerve cells can be extremely sensitive to synchronous input from large groups of neurons [8] . While there has been much work on elucidating the causes and effects of pairwise correlations between spike trains [3] , it seems that correlations beyond second order also have a role to play in the brain . For example , it was indicated that a nonlinear neuron’s firing rate profile depends on higher-order correlations between the presynaptic spikes [9] . Higher-order correlations have also been reported in the rat somatosensory cortex and the visual cortex of the behaving macaque [10] . Indeed , it has been suggested that these correlations are inherent properties of cortical dynamics in many species [11 , 12] . As a result , neural data has recently been intensively investigated for signs of higher-order synchrony using classical means such as maximum entropy models [13–18] . In addition , new methods are being developed in order to shed more light on what seems to be a very important property of networks in the brain [19–21] . In this work , we study the relation between the topology ( i . e . synaptic connectivity ) and correlations of third order between neuronal spike trains . Our aim was to show how triplet correlations depend on topological motifs in a network with known connectivity . We hope our results can be used to facilitate thought experiments to relate hypothetical connectivity to third-order correlations by , for example , assuming specific network topologies and then computing how these assumptions affect the dynamics . In the following text , the word “connection” is meant to be translated as “synapse” . While this might be a point of contention , in previous work , it was clearly shown that that a mapping between synaptically coupled spiking networks ( e . g . comprising LIF neurons ) and statistical , point process models , such as Hawkes process exist , with exactly the same underlying connectivity [22] . In addition , it has been demonstrated that synaptic connectivity can be reconstructed from simulated spike trains with very high fidelity , provided the network has a connectivity which is not too dense and not too sparse [23] . On the basis of these two results , we feel enough confidence to claim that in the Hawkes process network models considered here “connections” in terms of coupling kernels can be safely identified with “synapses” in a spiking neuronal network . However , we would also like to point out that knowing the true connectivity in an experimental setting is close to impossible . Indeed , the connectivity matrices , obtained by statistical inference methods applied to neural data are rarely more than a proxy for the actual “anatomical” connectivity . In other words , the existence of a statistical relationship between the firings of two neural cells ( “correlation” ) does generally not imply the existence of an actual synapse between them . In addition , the inference of connectivity from neural data is confounded by undersampling . One can typically only record from a tiny fraction of all neurons that constitute the network , while most of the population remains effectively hidden to the experimenter . Similar work , pertaining to the influence of connectivity on correlations of second order has already been published [3 , 24–26] . In it , the authors dissect the contribution of specific structural motifs to the emergence of pairwise correlations in a recurrent network of interconnected point processes , meant to represent neurons communicating via spikes . Interpreting known mathematical results [27] in an original fashion , they show how the influence of recurrent input can be disentangled to take into account not only effects of direct connections , but also indirect connectivity . However , no such result exists in the case of more complex patterns , stemming from correlations of higher order . With this paper , we aim to fill this gap . Analogously to [3] , we show that measures of third-order correlations ( known in the statistical literature as “third-order joint cumulants” ) are also heavily influenced by the presence of certain topological motifs in the network graph . We find that the motifs in question can be thought of representing “common input to triplets of neurons” and that , in graph theory terms , they represent rooted trees with three leaf nodes . Furthermore , we obtain an expansion of the joint third cumulants in terms of a sum of weights of all such subgraphs and show that , in a regular network ( that is , a network with fixed in- and out-degrees ) , this expansion can be approximated by a formula that doesn’t depend on the specific adjacency matrix , but rather on global connectivity parameters , such as the connection probability p . In addition , our result extends to large random Erdős-Rényi type networks , as they are approximately regular when the number of nodes grows without bound . We find that the formula we derive is a useful approximation for quantifying the level of third-order correlations in networks with a narrow out-degree distribution . In addition , we look at networks of highly interconnected hubs and show that , in this case , the average joint third cumulant depends strongly on the details of the connectivity pattern .
To study higher-order correlations in networks of spiking neurons with a fixed network topology , we apply a point process model introduced in [27 , 28] , which we will refer to as the “Hawkes process” . As the theory of Hawkes processes is rich and rather technical , we will only summarize the important definitions and equations needed to present our results . A more formal and thorough treatment of the model can be found in Hawkes’ original papers . In what follows , we will use capital letters to denote matrices . Vectors will not be explicitly marked , as their identity will be clear from the context . Individual components of matrices and vectors are referred to by indices attached to the symbol . Furthermore , note that , from here onwards , the phrase “third-order correlations” should always be interpreted as referring to “third-order joint cumulants” ( defined below ) . Our spiking neuronal network consists of N neurons , of which NE are excitatory and NI are inhibitory . Spike trains of neuron i , S i ( t ) = ∑ n δ ( t - t n i ) , are modeled as realizations of point processes with time-dependent firing rates Λi ( t ) . In other words , we have Λ i ( t ) = E [ S i ( t ) | S j ( t ′ ) , t ′ ≤ t , 1 ≤ j ≤ N ] , ( 1 ) where E [ · ] is the ( conditional ) expectation operator . In the Hawkes process framework , the vector Λ ( t ) of instantaneous firing rates ( conditional on Si ( t′ ) , for t′ ≤ t ) is given by Λ ( t ) = μ + ∫ - ∞ t G ( t - t ′ ) · S ( t ′ ) d t ′ ≡ μ + ( G ⋆ S ) ( t ) . ( 2 ) The vector μ can be interpreted as the rate of spontaneous activity ( due to constant external input ) in the network . The neurons in the network would independently spike at rates , given by components of vector μ , if there were no synaptic connections between neurons in the network . Recurrent synaptic interaction in the network is governed by the matrix of interaction kernels G ( t ) , an N × N matrix of causal functions gij ( t ) , describing the influence of a spike in neuron j imposed on the future rate of neuron i . Typically , this is a sparse matrix with most entries being zero , and only few of them being nonzero . In principle , all of the functions gij ( t ) can be different . However , for the sake of simplicity , we will assume that all source neurons in the excitatory subpopulation have interaction kernels equal to gE ( t ) to contact their targets , and all inhibitory neurons have interaction kernels gI ( t ) . Thus , the total synaptic weight of excitatory neurons equals gE ≡ ∫gE ( t ) dt and is positive , i . e . gE > 0 . Similarly , for inhibitory neurons , gI ≡ ∫gI ( t ) dt < 0 . The number gE represents the expected number of extra spikes in the postsynaptic ( target ) neuron induced by a spike of the presynaptic ( source ) neuron . Analogously , for inhibitory neurons , the number gI represents the expected reduction in the total number of spikes produced by the postsynaptic neuron . The exact connectivity between neurons in the network is chosen randomly , according to various rules , as will be explained in the sections to follow . One important thing to note is that the Hawkes model only allows for pairwise interactions , and yet possesses correlations of all orders . Furthermore , the Hawkes process is a probabilistic spike generator and , as such , may exhibit a different behavior than an encoder with a deterministic threshold mechanism . It is , however , important to realize that real neurons that are embedded in a large network possess both stochastic and deterministic features . Another potential limitation of the Hawkes model is that it provides a good approximation when synapses are weak , but strong synapses may more thoroughly explore neuronal nonlinearities . Finally , the Hawkes process is formally correctly defined only for positive interaction kernels . Negative interactions may lead to a rate vector Λ ( t ) with negative entries , which is of course not a meaningful configuration . Thus , technically , one should use the rectified rate [Λ ( t ) ]+ as a basis for spike generation in simulations . In the following , we will assume that the probability of having negative entries in the rate vector is negligibly low and will ignore the rectifying non-linearity . The goodness of this approximation is illustrated in Fig 1 . At equilibrium , the expected firing rate vector of the Hawkes process , E [ Λ ( t ) ] , no longer depends on time . We can compute the stationary rate vector , denoted Λ , as follows Λ = μ + ∫ - ∞ + ∞ Λ G ( t - t ′ ) d t ′ = μ + Λ ∫ - ∞ + ∞ G ( t ) d t , ( 3 ) from which we obtain the stationary rate of the network as Λ = ( I - G ) - 1 μ , ( 4 ) where we have used G as a shortcut for the matrix of integrated interaction kernels , i . e . G ≡ ∫G ( t ) dt and I denotes the N × N unit matrix . A summary of symbols , used in the text can be found in Table 1 . In what follows , we will also restrict ourselves to systems in which the spectral radius of the matrix G ( the largest eigenvalue of G ) , which we denote by ρ ( G ) , is less than 1 . Indeed , this condition insures the existence of the matrix inverse in the rate Eq 4 . Furthermore , if ρ ( G ) > 1 , it may happen that no stable equilibrium of the system exists and the spiking activity exhibits runaway solutions . An important result , originally presented in Hawkes’ original work [27 , 28] , was that the lagged cross-covariance of spike trains of different neurons can be analytically computed directly from the matrix of interaction kernels G ( t ) . More precisely , we can formally define the covariance density matrix , denoted by C ( τ ) , as C ( τ ) = E [ S ( t + τ ) S ( t ) T ] - Λ Λ T . ( 5 ) As was discussed before , intuitively , the entry ( i , j ) in C ( τ ) can be thought of as representing the probability that a spike of neuron j causes a spike of neuron i after time lag τ , minus the probability that this happens by chance ( which , assuming stationarity , equals ΛΛT ) . As noted in [27 , 28] , it is possible to rewrite C ( τ ) as C ( τ ) = D δ ( t ) + C 0 ( τ ) - Λ Λ T , ( 6 ) where D ≡ diag ( Λ ) is a diagonal matrix , with the entries of the rate vector Λ on the diagonal . Furthermore , C0 ( τ ) denotes the continuous part of the covariance density matrix , which is the solution to the matrix convolution equation C 0 ( τ ) = G ( τ ) D + ( G ⋆ C 0 ) ( τ ) , τ > 0 , ( 7 ) where the convolution of two matrix functions F ( t ) and G ( t ) equals a matrix function H ( t ) ≡ ( F ⋆ G ) ( t ) with H i j ( t ) = ∫ - ∞ t F ( t - s ) · G ( s ) d s = ∑ k ∫ - ∞ t F i k ( t - s ) G k j ( s ) d s , ( 8 ) where ⋅ denotes the usual product of two numerical matrices . An important result in [28] is that the Fourier transform of the covariance density matrix , i . e . C ^ ( ω ) ≡ ∫ - ∞ + ∞ C ( τ ) e - i ω τ d τ can be expressed in terms of the Fourier transform G ^ ( ω ) of the matrix of interaction kernels G ( t ) . More precisely , we have C ^ ( ω ) = ( I - G ^ ( ω ) ) - 1 D ( I - G ^ * ( ω ) ) - 1 , ( 9 ) where * denotes the conjugate transpose of a matrix . Recently , it has been shown [29 , 30] that , component-wise and in the time domain , the previous equation can be written as C i j ( τ ) = ∑ k = 1 N Λ k ∫ - ∞ + ∞ R i k ( u ) R j k ( u + τ ) d u , ( 10 ) where Λk is the k-th component of the previously defined stationary rate vector , and the matrix R ( t ) is a function of G ( t ) . Namely , we have that R ( t ) is a “convolution power series” of G ( t ) or , more precisely , R ( t ) = ∑ n ≥ 0 G ⋆ n ( t ) . ( 11 ) Here , the matrix G⋆n ( t ) denotes the n-th convolution power of the interaction kernel G ( t ) , defined recursively by G ⋆ 0 ( t ) = I δ ( t ) , ( 12 ) G ⋆ n ( t ) = ∫ - ∞ t G ⋆ ( n - 1 ) ( t - s ) · G ( s ) d s , n ≥ 1 , ( 13 ) where ⋅ again denotes a matrix product . We have the following heuristic interpretation of the matrix elements Rij ( t ) : R i j ( t ) d t ≡ P { spike of neuron j at 0 causes neuron i to spike at t } . ( 14 ) This heuristic offer an interesting interpretation of Eq 10 . Indeed , we can see the product Λk Rik ( u ) Rjk ( u + τ ) du as representing the probability that neuron k , spiking at its stationary rate Λk , causes neuron i to spike at u and neuron j at u + τ . The covariance density Cij ( τ ) of neurons i and j at lag τ is then nothing more than this probability , summed over all possible spikes times of neuron i ( hence the integral w . r . t . u ) and over all possible “presynaptic” neurons k . Thus , Cij ( τ ) can be seen as a sum of all possible ways in which a neuron k can induce activity in neurons i and j , with spikes that are τ apart . Moreover , a simple graphical representation of Cij ( τ ) is now available . As was first shown in [3] , the product Λk Rik ( u ) Rjk ( u + τ ) du can be represented as a rooted tree with leaves i and j ( see Fig 2 ) . Then , it can be shown that the lagged cross-covariance of spiking activity between neurons i and j is a sum of integral terms , each corresponding to a rooted tree with leaves i and j in the underlying network ( for more details , see [3] and [29] ) . We now move on to the problem of analyzing cumulants of higher order in networks of spiking neurons and introduce the tools necessary to do so . In statistics , a quantifier of third order correlations , analogous to the well-known covariance operator , is the third order joint cumulant , often denoted as κ3[X , Y , Z] . It measures above-chance level third order dependence in the same way that covariance does for second order . It is defined , for random variables X , Y and Z , as ( see S3 Appendix . for a full derivation of the formula ) κ 3 [ X , Y , Z ] = E [ X Y Z ] - E [ X Y ] E [ Z ] - E [ X Z ] E [ Y ] - E [ Y Z ] E [ X ] + 2 E [ X ] E [ Y ] E [ Z ] . ( 15 ) Let i , j and k be three distinct neurons in a recurrent neuronal network . Let further A = { ( i , t1 ) , ( j , t2 ) , ( k , t3 ) } denote a spike pattern , where neuron i spikes at time t1 , neuron j at t2 and neuron k at t3 . If we now plug in the variables Si ( t1 ) , Sj ( t2 ) and Sk ( t3 ) into Eq 15 and denote κ i j k ( t 1 , t 2 , t 3 ) ≡ κ 3 [ S i ( t 1 ) , S j ( t 2 ) , S k ( t 3 ) ] , ( 16 ) we see that the newly introduced function κijk ( t1 , t2 , t3 ) measures the likelihood of the pattern A occurring not due to chance and not due to pairwise correlations . Next , let Ni ( T ) represent the number of spikes of neuron i in a time bin of size T . Then , clearly , N i ( T ) = ∫ 0 T S i ( t ) d t . ( 17 ) Now , using Fubini’s theorem , we find that κ i j k ( T ) ≡ κ 3 [ N i ( T ) , N j ( T ) , N k ( T ) ] = ∫ 0 T ∫ 0 T ∫ 0 T κ i j k ( t 1 , t 2 , t 3 ) d t 1 d t 2 d t 3 . ( 18 ) In other words , while the function κijk ( t1 , t2 , t3 ) encodes the probability of occurrence of a single pattern A , the “integrated cumulant” κijk ( T ) ( that is , the joint third cumulant of spike counts ) measures the probability of the non-chance occurrence of any pattern of neurons i , j and k in a time bin of duration T . We will call the function κijk ( t1 , t2 , t3 ) the ( 3rd order ) cumulant density , as one needs to integrate it in order to obtain the 3rd cumulant of spike counts , i . e . κijk ( T ) . Assuming stationarity , the density κijk ( t1 , t2 , t3 ) can be written ( with slight abuse of notation ) as a function of only the ( two ) time lags between spike events at t1 , t2 and t3 κ i j k ( t 1 , t 2 , t 3 ) = κ i j k ( t 2 - t 1 , t 3 - t 1 ) ≡ κ i j k ( τ 1 , τ 2 ) , ( 19 ) where we have defined τ1 = t2 − t1 and τ2 = t3 − t1 . In that case , we get ( see S1 Appendix ) κ i j k ( T ) = κ 3 [ N i ( T ) , N j ( T ) , N k ( T ) ] T = ∫ - T T ∫ - T T κ i j k ( τ 1 , τ 2 ) d τ 1 d τ 2 . ( 20 ) Thus , we obtain an alternative interpretation of κijk ( T ) : It represents the third joint cumulant of spike counts of neurons i , j and k in a bin of size T , normalized by the bin size . As such , it is a quantity that can be easily computed from data , using unbiased estimators of higher-order cumulants , called k-statistics [31] . A recent result in the theory of Hawkes processes [29] shows that all 3rd order cumulant densities κijk ( t1 , t2 , t3 ) can be computed , just as in the pairwise case , as sums of integral terms , each corresponding to a relevant topological motif ( a subtree of the graph on which the process evolves ) , present in the underlying network . However , in the case of triplet correlations , the relevant rooted trees are somewhat more complicated ( see Fig 3 ) . Algebraically , we have κijk ( t1 , t2 , t3 ) =∑m=1NΛm∫−∞+∞Rim ( t1−u ) Rjm ( t2−u ) Rkm ( t3−u ) du+∑m , n=1NΛn∫−∞+∞Rin ( t1−u ) ( ∫−∞+∞Rjm ( t2−v ) Rkm ( t3−v ) Ψmn ( v−u ) dv ) du+∑m , n=1NΛn∫−∞+∞Rjn ( t2−u ) ( ∫−∞+∞Rim ( t1−v ) Rkm ( t3−v ) Ψmn ( v−u ) dv ) du+∑m , n=1NΛn∫−∞+∞Rkn ( t3−u ) ( ∫−∞+∞Rim ( t1−v ) Rjm ( t2−v ) Ψmn ( v−u ) dv ) du , ( 21 ) where Λn ( the stationary rate of neuron n ) and Rij ( t ) ( the rate change at time t in neuron i caused by a spike of neuron j at 0 ) have been defined previously , and Ψ ( t ) = R ( t ) - I δ ( t ) = ∑ n ≥ 1 G ⋆ n ( t ) , ( 22 ) which , heuristically , simply means that Ψ i j ( t ) d t ≡ P { spike of neuron j at 0 causes neuron i ≠ j to spike at t ≠ 0 } . ( 23 ) Unfortunately , this formula is cumbersome , impractical and difficult to work with . However , a much more elegant expression is obtained if one considers the previously defined joint cumulants of spike counts , κijk ( T ) . Formally , considering infinitely large time bins κ i j k ≡ lim T → + ∞ κ i j k ( T ) = ∫ - ∞ + ∞ ∫ - ∞ + ∞ κ i j k ( τ 1 , τ 2 ) d τ 1 d τ 2 , ( 24 ) and letting B ≡ ( I - G ) - 1 , where G is the previously defined integrated matrix of interaction kernels , we have [29] κ i j k = ∑ m Λ m B i m B j m B k m + ∑ m , n Λ n B i m B j m ( B m n − δ m n ) B k n + ∑ m , n Λ n B j m B k m ( B m n − δ m n ) B i n + ∑ m , n Λ n B i m B k m ( B m n − δ m n ) B j n . ( 25 ) This can be considered as a generalization of the pairwise correlation result from [3] . Indeed , if we let ω = 0 in Eq 9 and set C ≡ C ^ ( 0 ) = ∫ C ( τ ) d τ , we have C i j = B D B * = ∑ m = 1 N Λ m B i m B j m . ( 26 ) The problem , of course , is that the collection of all integrated cumulants {κijk}i , j , k represents a three-dimensional tensor , and as such cannot be represented in terms of a common matrix multiplication . For this reason , we must express κijk as weighted sums and double sums of entries of the matrix B in formula 25 . Finally , let us touch upon the link between integrated covariances Cij , cumulants κijk , and moments of the population count distribution Npop ( T ) which we define as the sum of activity of all neurons in the network N pop ( T ) ≡ ∑ m = 1 N N m ( T ) . ( 27 ) From the general properties of cumulants [32] , one can prove that lim T → + ∞ Var [ N pop ( T ) ] T = ∑ i , j C i j . ( 28 ) In other words , the variance of the population activity is equal to the sum of all integrated covariances , normalized by bin size . Of course , this is only strictly true for infinitely large time bins , but we have found that Eq 28 is still a very good approximation whenever the size of bin T is much bigger than the temporal width of any entry in the matrix of interaction kernels G ( t ) . Likewise , one can prove that lim T → + ∞ κ 3 [ N pop ( T ) ] T = ∑ i , j , k κ i j k . ( 29 ) Thus , the sums of all integrated cumulants of order 3 is equal to the third cumulant of population activity , normalized by bin size [31] . To understand why it is important to know the third cumulant κ3[Npop ( T ) ] consider that , for a normally distributed random variable X , all cumulants of order 3 and higher are zero X ∼ N ( 0 , 1 ) ⇒ κ n [ X ] = 0 , for all n ≥ 3 . ( 30 ) Therefore , in a sense , non-zero cumulants of order 3 and higher measure the departure from normality of the variable Npop ( T ) . Furthermore , in statistics , a measure of skewness of the distribution of a random variable X is defined as the ( scaled ) third cumulant κ3[X] . As the Gaussian distribution is symmetric about 0 ( and thus κ3[X] = 0 ) , any significant deviation of κ3[Npop ( T ) ] indicates right ( negative ) or left ( positive ) skewness . The simulation of linearly interacting point processes was conducted using the NEST simulator [33] . We simulated a network of 1000 neurons , of which 800 were excitatory and 200 inhibitory . The spikes of each neuron were generated according to a time-dependent rate function Λ ( t ) , defined by Eq 2 . Negative values of Λ ( t ) were rectified to zero , resulting in no spike output . Neurons received external Poissonian drive with constant rate of 10 Hz . Incoming spikes induced an increment of amplitude 1 . 5 Hz and −7 . 5 Hz for excitatory and inhibitory spikes , respectively , which decayed with a time constant of 10 ms . In the Hawkes process framework , this corresponds to an exponential interaction kernel with total integral gE = 0 . 015 and gI = −0 . 075 , respectively . The synaptic delay was set to 2 ms . The simulation time step was 0 . 1 ms . The total simulation time was 5000 s = 5 ⋅ 106 ms . Spike data from simulations were sampled in time bins of duration T = 100 ms , producing 5 ⋅ 104 bins . We found that the theoretical results concerning infinite sized bins are still largely valid when the bin size T is at least one order of magnitude larger than the interaction kernel time constant . The rates , pairwise covariances and joint third cumulants were estimated from a data matrix with 1000 rows ( representing individual neurons ) and 50000 columns ( representing time bins ) using k-statistics [31] , which are known to be unbiased estimators of cumulants of any order . Note that pairwise covariances are nothing more that joint cumulants of second order .
In this section we explain how recurrent connectivity affects joint third cumulants of triplets of neurons in a spiking neuronal network . As was mentioned before , the matrix of integrated interaction kernels G can be interpreted as an effective connectivity matrix , as each entry ( i , j ) represents the excess number of spikes in neuron i , caused by an individual spike in neuron j . With this in mind , let us now take a moment to develop a topological interpretation of Eq 25 . Firstly , as ρ ( G ) <1 has been assumed , we have a power series expansion for the matrix B = ( I - G ) - 1 , namely B = ∑n Gn . In order to develop intuition , we first consider what happens to Eq 26 when we plug the power series expansion of B into it ( as was done in [3] ) . The formula for Cij reads C i j = ∑ m = 1 N ∑ r = 0 + ∞ ∑ s = 0 + ∞ Λ m G i m r G j m s . ( 31 ) We now interpret the matrix Gr in the sense of graph theory , i . e . as a matrix whose entry ( i , j ) corresponds to the sum of compound weights of all paths from node j to node i in exactly r steps . Indeed , a typical entry of matrix Gr equals G i j r = ∑ k 1 , k 2 , ⋯ , k r - 1 G i k 1 G k 1 k 2 ⋯ G k r - 1 j . ( 32 ) We observe that each of the summands in the above equation is the average number of excess spikes , caused by an individual length r chain of spiking events , originating in neuron j . The entry G i j r is then the sum over all such chains , i . e . over all possible intermediary neurons k1 , k2 , ⋯kr−1 . Thus , a procedure for computing Cij would go as follows: Note that r = 0 ( s = 0 ) is a distinct possibility ( as the first term in the power series expansion of B is G0 ≡ I ) . In that case , we identify neurons m and i ( m and j ) and our “two-pronged tree” becomes a single branch with neuron i ( j ) on top and neuron j ( i ) on the bottom . Our previous discussion shows that the integrated covariance density Cij can be equivalently expressed as C i j = ∑ T ∈ T i j m w ( T ) , ( 33 ) where the sum goes over the set T i j m of all rooted trees T with root m , containing nodes i and j . Here , w ( T ) denotes the weight of tree T , defined as the product of weights of all edges , contained in T , times the weight of the root m , defined as being equal to Λm . Now , since , in the stationary case ( see S1 Appendix ) C i j = lim T → + ∞ cov [ N i ( T ) , N j ( T ) ] T , ( 34 ) we have that , for infinitely large time bins , the probability ( normalized by bin size ) of the non-chance occurrence of ANY pattern of neurons i and j in a bin of size T can simply be computed as the sum of weights of ALL possible rooted trees with leaves i and j . Thus , in a nutshell , the only way pairwise interaction can arise between neurons i and j is through shared input by a neuron k , that can be arbitrarily far upstream from both i and j . This is the main result of [3] . With our intuition primed by consideration of the simpler , pairwise correlation case , we are ready to tackle the computation of κijk . Once again , plugging the power series expansion of matrix B into Eq 25 yields κ i j k = ∑ T ∈ T i j k m w ( T ) , ( 35 ) where T i j k m is the set of all rooted trees with root m containing nodes i , j , k , and w ( ⋅ ) is the already defined weight function . As we have that ( see S1 Appendix ) κ i j k = lim T → + ∞ κ 3 [ N i ( T ) , N j ( T ) , N k ( T ) ] T , ( 36 ) the interpretation of the “sum over trees” formula is analogous . In other words , for infinitely large time bins , the probability ( normalized by bin size ) of the non-chance occurrence of ANY pattern of neurons i , j and k in a bin of size T can simply be computed as the sum of weights of ALL possible rooted trees , containing nodes i , j and k . The only difference from the pairwise correlation case is that the topological motifs contributing to triplet correlations are different and more numerous . What are the subtrees , contributing to κijk ? We can get our first hint by comparing the formula 25 and the trees in Fig 3 . Indeed , the first term in Eq 25 corresponds to the left , “three-pronged” tree in Fig 3—in fact , it is the combined weight of all such structures found in the graph with adjacency matrix G , summed over all possible identities of the root node m and over all possible lengths of the tree branches terminating at i , j and k . However , as any of the three branches can also be of length 0 , the left tree in Fig 3 actually represents 4 different contributions to κijk , one corresponding to the tree depicted , in which case all of the branches are of length at least 1 , and three other “two-pronged” trees obtained by collapsing one of the three branches and identifying the node m with node i , j or k ( see first row of Fig 4 ) . Algebraically , this can also be seen by replacing one of the B matrices in the first row of formula 25 by the identity matrix I . Indeed , placing I instead of B in any of the tree slots yields three possible contractions . In the right tree in Fig 3 , each of the last three terms in Eq 25 corresponds to one copy of it , the only difference among them being the label of the rightmost node . Indeed , the second term represents a tree in which the rightmost node is labeled k , for the third term the rightmost node is i , and for the last one it is j . Each of these terms contains three B matrices , and thus , each of these three terms will yield three additional trees whose weight will contribute to the overall sum , defining κijk ( see the second row of Fig 4 ) . Like before , all of these are obtained by replacing one of the B matrices with the identity matrix I and performing the corresponding summation . Notice that the last three terms in Eq 25 also depend on entries of the matrix B - I . This signifies the fact that the link between nodes n and m in Fig 3 can only “telescope out” , i . e . it cannot be contracted to 0 ( indeed , it corresponds to the power series ∑n ≥ 1 Gn in which the term of order 0 is not present ) . For reasons as to why this branch does not allow contractions , see [29] . To summarize , the six different tree shapes depicted in Fig 4 all contribute terms that , when summed up , yield κijk . Likewise , as was mentioned previously , each branch , incident to each of the trees pictured , can have arbitrarily many intermediate nodes in between the two vertices shown . We are interested in computing the average third cumulant in the network , defined as 1 N 3 ∑ i , j , k κ i j k , ( 37 ) where κijk represent the integrated joint third cumulants of neurons i , j and k , considered previously . From Eq 29 , we have that the previous sum equals lim T → + ∞ κ 3 [ N pop ( T ) ] T N 3 , ( 38 ) the third cumulant of population activity for an infinitely large time bin T , normalized by network size and bin width . Note that the sum in Eq 37 goes over ALL indices i , j and k . Thus , we have three distinct cases: The number of summands in the first case is equal to N ( N − 1 ) ( N − 2 ) , in the second case it is simply N , and in the third one it equals 3N ( N − 1 ) . Thus , we have κ ¯ 3 = 1 N 3 ∑ i , j , k κ i j k + ∑ i , j κ i i j + ∑ i κ i i i . ( 39 ) In the limit of large networks , the first term becomes dominant , as lim N → + ∞ 3 N ( N - 1 ) N 3 = 0 , lim N → + ∞ N N 3 = 0 , but lim N → + ∞ N ( N - 1 ) ( N - 2 ) N 3 = 1 . ( 40 ) Therefore , in all calculations that follow , we will assume that i , j and k are all different κ ¯ 3 = 1 N 3 ∑ i ≠ j ≠ k κ i j k . ( 41 ) Furthermore , we assume the following about the underlying network topology: In other words , the probability of a directed connection between any pair of nodes is equal to p , and each node is of a single type l and as such , only makes outgoing connections of type l . Here , L denotes the set of type labels . The derivations that follow can still be done under these general assumptions . Also , note that , even though the first assumption allows for random topologies , the results obtained in this section hold true for regular networks as well , as very large random networks are approximately regular . However , in the interest of concreteness , we will assume that L = {E , I} . In short , each node j can either be of type E ( excitatory ) or type I ( inhibitory ) . Thus , for a given “excitatory” node j , gij is either 0 ( with probability 1 − p ) or gE ( with probability p ) , for every neuron i . Likewise if the neuron is inhibitory ( in that case , gij equals gI ) . We now compute the average input to a neuron , embedded in the network . First , we note that , mathematically , the total input to node i can be computed as ∑j Gij . Given our previous considerations , we have that the total input equals p ( N E g E + N I g I ) = N p N E N g E + N I N g I ≡ N μ i n , ( 42 ) where NE and NI are the numbers of excitatory and inhibitory neurons in the network , respectively . We have also μin as p ( N E N g E + N I N g I ) , the average strength of the total input to a neuron . Now , if we set the external input μ to 1 , the stationary rate of neuron i can be seen to equal Λ i = ∑ j ∑ n G n i j = ∑ j ( δ i j + G i j + G i j 2 + ⋯ ) = 1 1 - N μ i n ≡ Λ ¯ . ( 43 ) Unsurprisingly , since the external input to all neurons is the same , the stationary rates are all equal ( Λ i = Λ ¯ , ∀ i ) . The computation of the average cumulant κ ¯ 3 can be done in much the same way ( for details , see S2 Appendix ) . Note that , to simplify derivation , we assume that all neurons ( irrespective of their type ) have the same in-degree and out-degree . The final formula then reads κ ¯ 3 = − Λ ¯ N 3 N 4 p 2 μ ( 3 ) ( 1 − μ ( 1 ) N ) 3 + 3 Λ ¯ N 3 N 3 p μ ( 2 ) ( 1 − μ ( 1 ) N ) 2 − 3 Λ ¯ N 3 N 4 p μ ( 1 ) μ ( 2 ) ( 1 − μ ( 1 ) N ) 3 − 6 Λ ¯ N 3 N 4 p μ ( 1 ) μ ( 2 ) ( 1 − μ ( 1 ) N ) 3 + 6 Λ ¯ N 3 N 3 [ μ ( 1 ) ] 2 ( 1 − μ ( 1 ) N ) 2 + 3 Λ ¯ N 3 N 5 p 3 [ μ ( 2 ) ] 2 ( 1 − μ ( 1 ) N ) 4 , ( 44 ) where each term in the equation corresponds to one of the tree shapes in Fig 4 . We have chosen not to perform any simplifications in the formula , as we feel that this would obscure the correspondence each term has to its tree counterpart . Here , we have defined μ ( k ) as the average common input , shared by k neurons , equaling μ ( k ) = p N E N g E k + N I N g I k . ( 45 ) Note that in this formalism , μ ( 1 ) is the “average common input shared by one neuron” , equal to μin , the average total input to a neuron . The precise nature of this relation between formula 44 and the topology of specific trees is covered in S2 Appendix . However , heuristically , the relationship is as follows Eq 44 can be used as an approximation whenever the degree distribution of the network in question is narrow–formally , it is only exactly true for a regular network , in which all neuron have the same in- and out-degrees . For large random networks of the Erdős-Rényi type , this is true as the resulting Binomial distributions have a standard deviation that vanishes with increasing network size . The numerical efficacy of such an approximation can be found in the following section . A final thing to note about Eq 44 is what happens when N → +∞ . Firstly , note that , once we perform all possible cancellations of terms in eq 44 , we find , after rearranging κ ¯ 3 = 3 p 3 μ ( 2 ) 2 N 2 Λ ¯ 5 - 9 p μ ( 1 ) μ ( 2 ) + p 2 μ ( 3 ) N Λ ¯ 4 + ( 3 p μ ( 2 ) + 6 [ μ ( 1 ) ] 2 ) Λ ¯ 3 . ( 46 ) Thus , in the limit of large networks , the most important term is the one corresponding to tree T6 in Fig 4 κ ˜ 3 ≡ 3 Λ ¯ N 3 N 5 p 3 μ ( 2 ) 2 ( 1 - μ ( 1 ) N ) 4 = 3 p 3 μ ( 2 ) 2 N 2 Λ ¯ 5 , ( 47 ) since we have 1 / ( 1 - μ ( 1 ) N ) = Λ ¯ . More precisely , we obtain the relation κ ¯ 3 = κ ˜ 3 + O ( N ) + O ( 1 ) . ( 48 ) As is now evident , the contributions from all trees of this shape to κ ¯ 3 grows as a quadratic function of N . The reason for this is that , in large networks , the number of “more complicated” subgraphs grows faster than the number of simpler ones . To see why this is true , consider counting all possible trees with k nodes and k − 1 edges in a random graph . Since each edge is generated independently , the number of such trees equals ( N k ) p k − 1 ( 1 − p ) ( k 2 ) − k + 1 , ( 49 ) Thus , as long as k ≤ ⌊N/2⌋ , the number of tree structures with k nodes in a random graph of size N will increase with increasing k . This is , in a nutshell , why the most relevant contribution to κ ¯ 3 comes from the “most complicated” tree , i . e . T6 . With the previous discussion in mind , one may expect that , for N → +∞ , the quadratic term κ ˜ 3 is a good approximation for κ ¯ 3 . Indeed , Fig 5 illustrates this . Thus , we are able to conclude that , in the limit of large networks , the dominating contribution to the average joint third cumulant κ ¯ 3 comes from the trees of topology T6 present in the network . One more thing to note is that the leading term κ ˜ 3 is proportional to a power of the stationary rate Λ ¯ . Let us briefly consider what happens to Λ ¯ in very large networks , for N → +∞ . We have Λ ¯ = 1 1 - N p N E N g E + N I N g I → 0 , N → + ∞ , ( 50 ) assuming we keep all other parameters fixed . As a result of this , the product N 2 Λ ¯ 5 in κ ˜ 3 , will decay to zero with increasing network size . Thus , when the size of the network considered grows without bounds , two things happen: The second point shouldn’t be too surprising . Indeed , once we remember that κ ¯ 3 is proportional to the skewness of the population activity ( defined as the sum of spike counts of all neurons in the network , in a bin of size T ) , its asymptotic vanishing is a straightforward consequence of the Central Limit Theorem . As N increases , the population activity is behaving more and more like a Gaussian random variable and , as a consequence , its skewness inevitably decays to zero . This effect is reflected by the horizontal asymptote in Fig 5 . In this section , we will analyze the contributions of terms , corresponding to tree shapes in Fig 4 with fixed branch length . More precisely , let us consider once again Eq 25 , plugging in the power series expansion of matrix B and exchanging the order of summation over “branch length” ( i . e . summation over powers of the G matrix ) and summation “over nodes” ( i . e . summation over i , j and k , used to define κ ¯ 3 ) , we get κ ¯ 3 = Λ ¯ N 3 ∑ l 1 , l 2 , l 3 [ ∑ i , j , k , m G i m l 1 G j m l 2 G k m l 3 ] + 3 Λ ¯ N 3 ∑ l 1 , l 2 [ ∑ i , j , k G i k l 1 G j k l 2 ] + 3 Λ ¯ N 3 ∑ l 1 , l 2 , l 3 [ ∑ i , j , k , m G i m l 1 G j m l 2 G m k l 3 ] 6 Λ ¯ N 3 ∑ l 1 , l 2 , l 3 [ ∑ i , j , k , n G i j l 1 G j n l 2 G k n l 3 ] + 6 Λ ¯ N 3 ∑ l 1 , l 2 [ ∑ i , j , k G i j l 1 G j k l 2 ] + 3 Λ ¯ N 3 ∑ l 1 , l 2 , l 3 , l 4 [ ∑ i , j , k , m , n G i m l 1 G j m l 2 G m n l 4 G k n l 3 ] . ( 51 ) The terms in the square brackets can be interpreted as the total weight of all relevant trees ( see Fig 4 ) present in the network , with lengths of all branches fixed . Under the regularity assumption , i . e . if all neurons have the same in-degree and out-degree , it is straightforward to conclude that the “square bracket term” of a tree T with n nodes and l leaves , embedded in a network of size N , can be computed as ( see S2 Appendix ) N n p l - 1 ∏ v μ ( k v ) μ ( 1 ) N l 1 + ⋯ + l n - 1 - n + 1 , ( 52 ) where the product is over all internal nodes ( i . e . nodes that are not leaves ) of T and kv is the out-degree of node v . The numbers l1 , … , ln−1 encode the lengths of branches of T , of which there are exactly n − 1 in a tree with n nodes . In fact , it is this result that greatly simplifies the “summation over branch lengths” one needs to perform in order to obtain Eq 44 . Furthermore , from formula 52 we see that the only relevant characteristics of a tree T that determine the weight of the contribution are the number of its nodes n , the number of its leaves l and the out-degrees of its internal nodes . Note that the root counts as an internal node here . Trees with a large total branch length contribute relatively little to κ ¯ 3 . Indeed , as | μ ( 1 ) N | = | p N E g e + N I g I | < 1 , ( 53 ) we have that , when the total length of all branches tends to infinity ( i . e . when the sum sn ≡ l1 + ⋯ + ln−1 grows beyond all bounds ) , the corresponding term ( μ ( 1 ) N ) s n decays to zero . Lastly , we consider the issue of determining the signs of various contributions to κ ¯ 3 . This can be done by once again closely analyzing formula 52 . First , note that the common input terms μ ( k ) are positive for even and negative for odd k . Indeed , as we assume that underlying network in inhibition-dominated ( that is , if we assume that the total input to a neuron is negative ) we have , in mathematical terms that N E g E + N I g I < 0 ⇔ g I < - N E N I g E . ( 54 ) Thus , μ ( 2 r + 1 ) = p ( N E N g E 2 r + 1 + N I N g I 2 r + 1 ) < p ( N E N g E 2 r + 1 + ( − 1 ) 2 r + 1 N E N ( N E N I ) 2 r g E 2 r + 1 ) . Therefore , μ ( 2 r + 1 ) < p N E N 1 - N E N I 2 r g E 2 r + 1 < p 1 - N E N I 2 r g E 2 r + 1 < 0 , ( 55 ) since gE > 0 , NE > NI and 0 ≤ p ≤ 1 . In the same way , one can show that μ ( 2r ) > 0 . Therefore , the out-degree sequence of the internal nodes of the tree affects the sign of the corresponding contribution . If , for example , the tree has two internal nodes , with out-degrees 1 and 2 , respectively , this will contribute an overall negative sign to the term . However , the out-degree sequence alone does not completely determine the sign of the contribution . Another factor is the parity of the total length of all branches , i . e . the sum sn ≡ l1 + … + ln−1 . To see why , note that Nμ ( 1 ) < 0 , by our previous discussion , and likewise μ ( 1 ) N s n - n + 1 ( 56 ) is either negative or positive , depending on whether sn = 2r + 1 or sn = 2r . ( Note that sn ≥ n − 1 . ) To summarize , the resulting sign of the total contribution to the average third cumulant , of a specific tree with n nodes , l leaves , a given out-degree sequence and branch lengths depends on both the parity of the product of the internal node out-degrees and the parity of the total branch length . What this means in practice is that the presence of certain trees increases the overall level of third order correlation , while the existence of others can actually have the opposite effect . Whether the latter or the former is the case depends solely on the tree’s topological structure , i . e . how the internal nodes branch and how many edges it contains . As an illustration , the signs and sizes of contributions of two sample trees in a recurrent random network are depicted in Fig 6 . One can clearly see which trees increase third-order correlations in the network , and which trees actually decrease them . One last thing to note is how quickly the contributions , involving higher matrix powers of G ( i . e . those trees with higher total branch length ) decay to zero as the total branch length increases . This behavior is essentially governed by the spectral radius ρ ( G ) of the connectivity matrix . For example , in a large random network of both excitatory and inhibitory neurons , the spectrum consists of a single eigenvalue of size N μ ( 1 ) = N p ( N E N g E + N I N g I ) and a bulk spectrum , contained within a circle in the complex plane [34] . Its radius r is asympotically given by r 2 = N p ( 1 - p ) N E N g E 2 + N I N g I 2 . ( 57 ) While , as was already mentioned , the quantity Nμ ( 1 ) corresponds to the total average input to a neuron , the radius r of the circle encompassing the bulk spectrum corresponds to the variance of this input . Thus , if the variance of the total input to a neuron in a random network is not too big ( r < 1 ) , it will exhibit the aforementioned decay of contributions from trees with higher total branch lengths . In the previous sections , we have demonstrated that the average third cumulant in networks with narrow degree distributions is determined by global parameters such as the number of neurons N , the connection probability p , and the average strength of input shared by k neurons , μ ( k ) . Of course , in networks with a wide degree distribution , the regular network approximation ( which we used to derive the equation in S2 Appendix ) is no longer valid . To demonstrate some of the new phenomena by simulation , we consider a network model with a geometric degree distribution , originally introduced in [3] . In short , the out-degrees k of excitatory and inhibitory neurons are chosen from a geometric distribution with parameter k0 ( representing the mean out-degree ) according to P ( k ) = 1 - 1 k 0 k - 1 1 k 0 . ( 58 ) This distribution exhibits a mean connection probability of 1/k0 and a long tail . After the sampling of out-degrees , excitatory neurons are divided into “hubs” ( out-degree k > k0 ) and “non-hubs” ( k ≤ k0 ) . Postsynaptic neurons for non-hubs and inhibitory neurons are chosen randomly from the population consisting of all other neurons . However , for hub neurons , a fixed fraction f of all outgoing connections goes to other hubs . By varying f between 0 and 1 , one can choose how densely connected the subnetwork of hubs will be . The “critical value” to keep in mind here is f0 = 0 . 35 . If f > f0 , hub neurons have a preference to connect to other hubs . Such a network is called “assortative” , otherwise it is called “disassortative” , see [3] for details . Similar networks have been studied in [35 , 36] . The effect of the geometric out-degree distribution on the distribution of network motifs is depicted in Fig 7 . If excitatory hubs preferentially connect to other hubs ( for assortative networks ) , the number of relevant tree motifs with high total branch length grows in the network , and so does their combined strength . This is one major difference between assortative and random networks , and a reason why the contributions of longer trees in networks with hubs tend to be much larger than in Erdős-Rényi topologies . Of course , along the same lines , the number of “short” motifs ( i . e . those with small total branch length ) decreases ( in comparison to their “longer” counterparts ) . This phenomenon is illustrated in Fig 7 . This discrepancy can also be used to say something about the topology of the network that generated a given set of recorded spike data . Indeed , once the connection probability and third order correlations have been estimated ( e . g . with the help of k-statistics ) , one could compare the regular network theory predictions with the third order cumulants obtained from data . A large disparity between the two could imply , for example , the presence of hubs and a wide in- and out-degree distribution in the network that generated the data .
In this work , we have studied connections between topology and measures of average third-order correlations in networks of spiking neurons . We have compared different connectivity rules with respect to their effect on the average joint third cumulant , κ ¯ 3 . Furthermore , we showed which topological motifs in the network contribute to the overall strength of third-order correlations . While our focus was on network models arising in neuroscience , we feel that the results presented here could as well be relevant in other fields , where correlations of higher-order play an important role . As a handy computational model of spiking neuronal activity , we have used the Hawkes point process [27 , 28] , which was originally introduced as a model of earthquake activity . It is sufficiently rich in order to model interesting dependencies between various types of events ( in our case , spikes of different neurons ) , but still simple enough to be tractable . Indeed , these are the exact properties that make Hawkes processes quite useful models in neuroscience . They have been employed in the analysis of pairwise correlations between spike trains [3 , 37] , modeling spike-timing dependent plasticity [38 , 39] , and , very recently , to model single unit activity recorded on a monkey during a sensory-motor task [40] . Using the Hawkes process theory , we have shown that a linear stochastic point process model can reproduce not only the event rates and pairwise correlations in networks ( as was already shown in [3] ) , but also its third-order joint cumulants , which are statistical measures of correlations between groups of three nodes . These cumulants can be seen as a quantification of “non-Gaussian” properties of the total population activity observed in time bins of a given size . The problem of quantifying higher-order correlations is of some importance in computational neuroscience . It has been suggested a long time ago [41 , 42] that understanding the cooperative dynamics of populations of neurons would provide much needed insight into the neuron-level mechanisms of brain function . Indeed , there is now a large body of experimental evidence that supports the idea of computationally relevant correlations between neurons in a network [7 , 43–45] . The evidence for coordinated activity of neuronal spike trains , however , mostly relies on the correlations between pairs of nerve cells [46–50] . Unfortunately , it is becoming increasingly clear that pairwise correlations cannot explain the intricate dynamics of neuronal populations [9 , 12 , 51 , 52] and that higher-order moments of spiking activity need to be taken into account . Traditionally in neuroscience , higher-order synchrony has been almost exclusively investigated with the help of classical tools borrowed from statistical physics such as maximum entropy models [13–18 , 53] . In this approach , the quantifiers of higher-order coordination are the so-called “interaction parameters” of the binary exponential family . However , an alternative measure , commonly used in statistical literature , also exists—it is the joint cumulant . As already mentioned in [54 , 55] , cumulant correlations are not identical to the higher order exponential family parameters ( for details , see [54] ) . In a sense , it can be said that non-zero cumulants indicate the presence of additive common input ( a well-known model for correlated stochastic signals , see [56–58] ) , while the interaction parameters of maximum entropy models measure multiplicative interactions . The mathematical differences between the two types of dependence are currently under investigation [59–61] . As our neuronal network model each neuron “feels” only the linear sum of spiking activity of its presynaptic partners , in this work we have opted for quantifying synchrony using joint cumulants . Finally , it may be worthwhile to note that there are other ways of generating time structured correlations of higher order in computational models ( see , for example , [9] , but also [62] ) . In addition , by generalizing the result in [3] , we have found that integrated third-order correlations ( κijk ) also admit a representation in terms of sums of weights of certain topological sub-motifs in the network . While in the case of pairwise correlations between neurons these motifs were simple binary trees ( see Fig 2 ) , when dealing with third-order interactions the motifs become more complex ( Fig 3 ) “trees with three leaves” , which are still manageable computationally . More precisely , it is the combined “strength” of all such trees containing a triplet of neurons that determine how often , on average , the activity of such a triplet exhibits coordinated spiking . Sadly , no concise matrix product formula is available for the whole third cumulant tensor {κijk}i , j , k and one has to resort to writing down equations for individual components , which still offer the possibility of efficient estimation . Indeed , computing the theoretical cumulants κijk for ( close to ) regular networks is much less computationally intensive than estimating them from data via k-statistics and only relies on simple algebraic manipulations of the connectivity matrix G . We have also studied analytically the average third-order cumulant κ ¯ 3 , derived from the sum of joint cumulants of all possible triplets of neurons in the network . We have shown that the value of κ ¯ 3 in random networks of Erdős-Rényi type does not depend on fine-scale topological structure and is instead a function of global network parameters , such as the network size N , the connection probability p and total common input to groups of neurons . Furthermore , we have shown that , in the limit of very large networks , the dominating contribution to κ ¯ 3 comes from the combined weight of all trees with a specific topology ( which we denoted T6 , see Fig 4 ) present in the network . Thus , for large , random networks , it is tree-like connectivity motifs of this topology that affects the average third cumulant most . We were able to show that the contributions of individual subtrees to the average joint cumulant depend on specific topological properties of the tree , such as its number of branches , number of nodes and , interestingly , the out-degrees of its internal nodes ( nodes that are not leaves as they have a nonzero out-degree ) . Not surprisingly , in a stable network ( whose connectivity matrix G has a spectral radius less than 1 ) , the absolute contributions of trees with a large number of branches decays to 0 as the number of branches increases . However , the sign of the total contribution turns out to depend both on the parity of the sum of all internal node out-degrees and the parity of the total branch length . This , in principle , allows one to determine whether the presence of a particular sub-tree in a network will increase or decrease the third cumulant , and thus allow to compute the total size of third-order interactions . Finally , we considered a case in which our regular network approximation fails , networks with interconnected hub neurons . Similar networks were already considered in [3] . Their main characteristic is a heavy-tailed out-degree distribution ( in the case we considered , it was geometric ) . Such networks are , in a sense , the opposite of an Erdős-Rényi type random network . The presence of interconnected hubs increases the number of subtrees in the network with large total branch length and , consequently , their overall contribution to the average joint third cumulant . Thus , such networks illustrate nicely how “higher-order” motifs can , for certain networks , influence the overall third-order cumulant structure , which is not possible in networks with narrow out-degree distributions . As far as the limitations of our approach are concerned , it is important to note that the linear theory of Hawkes processes which we resorted to [29] is strictly valid only for purely excitatory networks , as the instantaneous rate function is not allowed to become negative . For the case discussed here , this may happen , as the networks are inhibition-dominated . However , in accordance with what was already mentioned in [27] , the theoretical results remain approximately valid for networks with negative interactions , as long as the probability of the rate being negative is small . Still , an interesting generalization of our model , and the results achieved with it , would be the case of multiplicative interaction [63] . More generally , a point process model in which an non-negative nonlinearity is applied to Eq 3 yields a necessarily positive rate for any choice of interaction kernels . The computational approach one would have to use in this case in order to study the effect of topology on higher-order correlations would be quite different , though , as almost no analytical results exist for such models [64 , 65] .
|
Many biological phenomena can be viewed as dynamical processes on a graph . Understanding coordinated activity of nodes in such a network is of some importance , as it helps to characterize the behavior of the complex system . Of course , the topology of a network plays a pivotal role in determining the level of coordination among its different vertices . In particular , correlations between triplets of events ( here: action potentials generated by neurons ) have recently garnered some interest in the theoretical neuroscience community . In this paper , we present a decomposition of an average measure of third-order coordinated activity of neurons in a spiking neuronal network in terms of the relevant topological motifs present in the underlying graph . We study different network topologies and show , in particular , that the presence of certain tree motifs in the synaptic connectivity graph greatly affects the strength of third-order correlations between spike trains of different neurons .
|
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"Abstract",
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"Discussion"
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2016
|
Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks
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The phosphorylation state of the C-terminal domain ( CTD ) of the RNA polymerase II plays crucial roles in transcription and mRNA processing . Previous studies showed that the plant CTD phosphatase-like 1 ( CPL1 ) dephosphorylates Ser-5-specific CTD and regulates abiotic stress response in Arabidopsis . Here , we report the identification of a K-homology domain-containing protein named SHINY1 ( SHI1 ) that interacts with CPL1 to modulate gene expression . The shi1 mutant was isolated from a forward genetic screening for mutants showing elevated expression of the luciferase reporter gene driven by a salt-inducible promoter . The shi1 mutant is more sensitive to cold treatment during vegetative growth and insensitive to abscisic acid in seed germination , resembling the phenotypes of shi4 that is allelic to the cpl1 mutant . Both SHI1 and SHI4/CPL1 are nuclear-localized proteins . SHI1 interacts with SHI4/CPL1 in vitro and in vivo . Loss-of-function mutations in shi1 and shi4 resulted in similar changes in the expression of some stress-inducible genes . Moreover , both shi1 and shi4 mutants display higher mRNA capping efficiency and altered polyadenylation site selection for some of the stress-inducible genes , when compared with wild type . We propose that the SHI1-SHI4/CPL1 complex inhibits transcription by preventing mRNA capping and transition from transcription initiation to elongation .
In eukaryotes , gene transcription includes several co-transcriptional processes such as mRNA 5′ capping , splicing and polyadenylation . These co-transcriptional processes are executed by protein enzymes and factors that are recruited to the carboxyl terminal domain ( CTD ) of the largest subunit of RNA polymerase II ( Pol II ) during gene transcription . The factors to be recruited to the CTD are determined by the phosphorylation patterns of the highly conserved tandem repeats ( Y1S2P3T4S5P6S7 ) in the CTD that is regulated by site-specific CTD kinases and phosphatases [1] . Phosphorylation status of the Ser-2 and Ser-5 in the heptapeptide repeat of the CTD is thought to be important for the co-transcriptional processes and recycling of the RNA polymerase II . 5′capping of the nascent transcript occurs shortly after the transcription initiation and requires CTD phosphorylation at the Ser-5 by the general transcription factor TFIIH [1] , [2] , while phosphorylation of the Ser-2 residues by the positive transcription elongation factor b ( P-TEFb ) is believed to promote transcription elongation , splicing , and 3′end processing [3] . Recycling of Pol II requires dephosphorylation of the CTD and several CTD phosphatases are known to function in this process . In yeast , SCP1 [4] , [5] and Ssu72 [6] are for the dephosphorylation of Ser-5 , while FCP1 is for the dephosphorylation of Ser-2 [7] . However , in Encephalitozoon cuniculi , Fcp1 dephosphorylates both Ser-5 and Ser-2 [8] . The Fcp1 protein has a conserved N-terminal Fcp1 homology ( FCPH ) region with the DXDX ( T/V ) signature motif important for its catalytic activity . In Arabidopsis , the FRY2/CPL1 protein also possesses the FCPH domain at its N-terminus that is essential for its CTD phosphatase activity . FRY2/CPL1 dephosphorylates Ser-5 rather than Ser-2 in the CTD repeat polypeptides in vitro [9] , [10] . In addition , the FRY2/CPL1 contains two dsRNA binding domains at its C-terminus that may be important for its association with RNA . FRY2/CPL1 was initially identified in genetic screenings in Arabidopsis for mutants showing altered expression of luciferase reporter gene driven by the stress-inducible promoter Rd29A . The fry2 mutant was recovered from an EMS mutagenized population [11] and the cpl1 mutant was identified from a T-DNA insertion mutagenized population [12] . Mutations in FRY2/CPL1 resulted in significant increases in the expression of luciferase reporter gene and other stress-responsive genes , indicating that FRY2/CPL1 is a repressor for stress inducible genes . fry2/cpl1 mutant plants do not show apparent growth and development phenotypes under normal growth conditions except that the mutants flower later than wild type [11] , [12] . However , fry2 mutants display phenotypes in response to salt , ABA , freezing treatments , low iron availability and cadmium toxicity [11] , [13] . It was proposed that FRY2/CPL1 functions as a negative regulator of gene expression by inhibiting the formation of elongation complex or mRNA capping via dephosphorylation of the Ser-5-PO4 of the CTD within the initiation complex or the early elongation complex [9] . Moreover , a recent study using fast-forward genetics has identified the CPL1 as an important player in miRNA biogenesis [14] . In this study , the CPL1 was shown to interact with and dephosphorylate HYL1 within the miRNA microprocessor complex , which is required for accurate miRNA processing and strand selection . Studies so far on FRY2/CPL1 have suggested that this CTD phosphatase is a multi-functional protein involving in different cellular and biochemical processes . During transcription and post-transcriptional processes , mRNAs are always associated with RNA-binding proteins ( RBPs ) [15]–[17] . Generally , RBPs have one or more RNA-binding domains of the RNA recognition motif ( RRM ) , the K-homology ( KH ) domain , or the combination of these two most widely present RNA-binding domains [15] , [18] , [19] . The KH domain was named due to its first discovery from the human protein heterogeneous nuclear ribonucleoprotein K ( hnRNP K ) [20] . KH domains were then found in many other proteins functioning in diverse processes including transcription , mRNA stability , translational silencing and mRNA localization [21] . KH domain proteins have been implicated in human diseases . For example , fragile X mental retardation syndrome is caused by lack of functional fragile X mental retardation protein ( FMRP ) containing two KH domains . A single mutation ( Ile304 to Asn ) in the KH2 of FMRP is responsible for this syndrome in a particularly pernicious case [22] , [23] . The KH splicing regulator protein/fuse binding protein 2 ( KSRP/FBP2 ) contains four KH domains and plays important roles in ARE mediated mRNA decay [24] . In Arabidopsis , 26 KH domain-containing proteins were found through sequence analysis [18] . Up to now , only three of the 26 predicted KH domain-containing proteins have reported functions . The first KH domain-containing protein with a reported function is HEN4 ( HUA ENHANCER 4 ) [25] . HEN4 contains five or four KH domains depending upon exclusion or inclusion of the last intron in the transcripts due to alternative splicing . HEN4 , together with HUA1 and HUA2 , promote AGAMOUS pre-mRNA processing and play a critical role in floral morphogenesis [25] . Another KH domain containing protein in Arabidopsis is FLK ( Flowering Locus KH Domain ) with three KH domains and acts as a repressor of FLC gene to regulate flowering time [26] . The three KH domain containing protein PEP in Arabidopsis functions in controlling vegetative growth and pistil development by interacting with elements of the CLAVATA signaling pathway [27] . In this paper , we present a study of a previously uncharacterized KH domain containing protein named SHINY1 ( SHI1 ) in Arabidopsis . The shi1 mutant was isolated from a forward genetic screening for mutants showing elevated expression of the luciferase reporter gene driven by a salt inducible promoter . We show here that SHI1 interacts with the CTD phosphatase FRY2/CPL1 to modulate co-transcriptional processes such as mRNA capping and polyadenylation . The SHI1-FRY2/CPL1 complex , together with other unidentified protein components , functions to repress stress-inducible gene expression .
In an attempt to identifying regulators of stress-inducible genes , we established a forward genetic screening for mutants showing elevated expression of the luciferase reporter gene driven by a salt inducible promoter from the sulfotransferase gene AtSOT12 ( At2g03760 ) . The AtSOT12 gene expression is highly induced by salt and osmotic stress according to our previous finding [28] and a microarray analysis [29] . To test whether the AtSOT12 promoter is a salt-inducible promoter , a chimeric gene consisting of the firefly luciferase gene driven by the AtSOT12 promoter was transformed into Arabidopsis ecotype Columbia-0 . A homozygous transgenic line showing normal morphology , growth and development was selected for further study . Both Northern hybridization and luciferase imaging revealed that the luciferase expression is highly induced by salt stress ( Figure S1 ) in the homozygous line , indicating that the AtSOT12 promoter is indeed a salt inducible promoter . Seeds of the homozygous transgenic line ( referred to as wild type ) were mutagenized with EMS and the M2 seeds from 20 pools were subjected to mutant screening using the luciferase imaging system . A number of mutants showing higher expression of luciferase after salt stress treatment were identified . These mutants were named shiny ( shi in short ) mutants because of their bright luminescence imaging . One shiny mutant , designated shi1 , is studied in the present paper . As shown in Figure 1A , the shi1 mutant displayed an elevated luciferase expression comparing with the wild type under both normal condition and after salt treatment . Quantitative analysis of luminescence intensity further confirmed that luciferase activity in the shi1 seedlings was much higher than that in the wild type with or without NaCl treatment ( Figure 1B ) . To determine whether the increased luciferase activity in shi1 mutant was due to increased luciferase transcript level , RNA blot analysis was carried out . Figure 1C shows that the luciferase gene transcript was not detectable in both wild-type and shi1 mutant plants without stress treatment , whereas shi1 mutant exhibited substantially higher luciferase transcript level than the wild type after 200 mM NaCl treatment for 5 hours . Quantification of the transcript levels indicated that the fold change of luciferase transcript is much lower than the fold change of luciferase activity ( Figures 1B and 1D ) , which suggests that the increased transcription level of luciferase gene only partly contributes to the increase luciferase activity in shi1 mutant . After extensive phenotyping of the shi1 mutant in response to different abiotic stresses and plant hormones , the shi1 mutant was found to be more resistant to ABA in seed germination and more sensitive to low temperature during vegetative growth ( Figure 2 ) . The germination rate of shi1 seeds at 7 d was reduced to 84 . 0% relative to 35 . 8% of the wild-type seeds in the presence of 0 . 5 µM ABA . When the concentration of ABA increased to 1 . 0 µM , the germination rate of shi1 decreased further to 53 . 5% comparing with 17 . 9% of the wild-type seeds ( Figure 2B ) . Under normal growth conditions , shi1 plants essentially resembled the wild type plants in growth and development ( Figure 2C ) . However , when growing under cold condition at ∼4°C with 16 h light/8 h dark , the shi1 mutant plants showed yellow leaves and smaller rosette comparing with the wild-type plants ( Figure 2C ) . The flowering shi1 plants exhibited apparent smaller size comparing with the flowering wild type plants when growing under such cold condition ( Figure 2C ) . We also tested other stress treatments , such as ABA , NaCl , LiCl , mannitol and UV-light on the root growth and the shi1 mutant showed similar response to these stress conditions with wild type . To determine the effects of the shi1 mutation on stress-responsive gene expression , we selected a set of genes , including CBFs , COR genes and DREB2A that have been used as marker genes for cold , ABA and salt response [11] . The transcript levels of these stress-responsive genes were analyzed by using RNA blot . As shown in Figure 3 , CBF3 transcript levels were higher in the shi1 mutant than in wild type plants after cold treatments . At the time point of 12 hours of cold treatment , the shi1 mutant still showed strong induction of CBF3 gene expression , while wild type did not . CBF2 expression levels were similar between the shi1 and wild type after cold treatments , while shi1 mutant exhibited slightly higher CBF2 transcript levels than the wild type plants when treated by NaCl or ABA . The shi1 mutation had opposite effect on the expression of two COR ( cold-responsive ) genes , COR15A and COR47 . The expression of COR15A was substantially lower in the shi1 mutant than in the wild type , while the expression of COR47 was higher in the shi1 mutant than in the wild type under some tested stress conditions ( Figure 3 ) . The major differences in induced gene expression of CBF3 , COR15A and COR47 were further verified by using quantitative RT-PCR ( Figure S2 ) . These data indicate that SHI1 is involved in the regulation of abiotic stress responsive genes . Genetic analysis verified that the shi1 mutation is a single nuclear recessive mutation . To determine the molecular identity of the SHI1 gene , map-based cloning was employed using F2 seeds of the shi1 mutant crossed with Landsberg erecta wild type as a mapping population . Mutant seedlings from the F2 mapping population were selected and the shi1 mutation was mapped with simple sequence length polymorphism ( SSLP ) markers . The mutation was first mapped to the Chromosome 5 and then further narrowed down to between the BAC clones MNB8 and MFH8 ( Figure 4A ) . After sequencing several candidate genes within this region , a nucleotide change of G1494A was found in the At5g53060 gene in the shi1 mutant . This nucleotide change resulted in an amino acid substitution of E369K in the third KH domain of this KH domain-containing protein ( Figure 4A ) . To confirm whether the mutation in At5g53060 is responsible for the phenotype of shi1 mutant , the shi1 mutant was crossed with two T-DNA lines SALK_143161 and SALK_001448 with T-DNA insertions in the SHI1 gene . The F1 seedlings resulted from these genetic crosses displayed elevated luciferase expression comparing with the wild type ( Figure 4B ) . For molecular complementation assay , a genomic fragment containing the SHI1 open reading frame along with 1910 bp promoter sequence upstream of the translation start codon ( corresponding to position 21513445 , Chromosome5 ) and 262 bp of sequence downstream of the translation stop codon ( corresponding to position 21518401 , Chromosome5 ) was amplified from the BAC clone MINB8 and introduced into the shi1 mutant by using the Agrobacterium-mediated floral dip transformation method [30] . The wild type SHI1 gene recovered the luciferase expression level of the shi1 mutant to the level in the wild type ( Figure 4B ) , which further supports that the shi1 mutation in At5g53060 gene is indeed responsible for the shi1 mutant phenotype . The expression of the SHI1 gene in plant was analyzed by using promoter-GUS assay and RNA blot analysis . SHI1 is expressed in roots , leaves , flowers , and siliques , but its expression is low in stems ( Figures 5A and 5B ) . SHI1 is a nuclear-located protein , which was revealed by examining the SHI1-GFP fusion protein expressed in a transgenic Arabidopsis plant ( Figure 5C ) . The expression of SHI1 gene was sharply reduced by treatments with high concentrations of salt such as NaCl , NaNO3 , KCl and LiCl , hyperosmotic stress treatment with sorbitol , and treatments with ABA , low or high pH ( Figure 5D ) . However , cold treatment did not significantly change the SHI1 expression level ( Figure 5D ) . Interestingly , the effect of NaCl treatment on the SHI1 expression appears to have a clock rhythm . SHI1 gene expression was quickly and sharply reduced by NaCl treatment for 10 min and this inhibition lasted up to 2 hours of NaCl treatment . The SHI1 expression level gradually recovered to the control level after salt treatment from 3 to 6 hours . After 12 hours NaCl treatment , the SHI1 transcript was again reduced to very low level and then recovered substantially after 24 hours of NaCl treatment ( Figure 5D ) . To better understand the molecular function of SHI1 in Arabidopsis , a yeast two-hybrid screen for SHI1-interacting proteins was performed . 18 independent clones representing FRY2/CPL1 cDNA showing interaction with SHI1 bait protein were identified from the prey cDNA library ( TAIR Cat . No . CD4-30 ) . Among the 18 clones , three different sizes of cDNAs were obtained: the longest cDNA corresponding to 476–967 aa sequence , the medium sized cDNA corresponding to 533–967 aa sequence , and the shortest cDNA corresponding to 666–967 aa sequence of the C-terminus of the FRY2/CPL1 protein . The full length protein of FRY2/CPL1 was also confirmed to interact with SHI1 in the yeast two-hybrid system ( Figure 6B ) . Protein deletion analysis was used to pinpoint the regions responsible for SHI-FRY2/CPL1 interaction . As shown in Figure 6A , the first KH domain and the third KH domain in the SHI1 protein could interact with FRY2/CPL1 . The shi1 mutation of Glu389 to Lysine change in the third KH domain disrupted the interaction of SHI1 with FRY2/CPL1 , suggesting that the formation of SHI1-FRY2/CPL1 protein complex is essential for SHI function and loss-of-function of shi1 mutation is probably due to disruption of such a complex formation . Deletion analysis also revealed that the first dsRNA binding motif is required for the interaction of FRY2/CPL1 with SHI1 ( Figure 6B ) . Direct physical interaction between SHI1 and FRY2/CPL1 was determined with protein pull-down assay . The amino acid sequence including the first dsRNA binding domain ( 666–855 aa ) of the FRY2/CPL1 was fused with 6XHIS tag ( HIS-cFRY2 ) and synthesized by using an in vitro translation system . GST-SHI1 tagged protein was expressed and purified from E . coli for in vitro pull-down assay . As shown in Figure 6C , the 35S-methonine radioactive labeled HIS-cFRY2 was pulled down together with GST-SHI1 , which confirms a physical interaction between SHI1 and FRY2/CPL1 . Interaction of SHI1 with FRY2/CPL1 in plant cells was further established by using a split luciferase complementation assay [31] and split YFP complementation assay . The SHI1 protein was fused with the N-terminal portion of the luciferase and the FRY2/CPL1 protein was fused with the C-terminal part of the luciferase and co-expressed in Arabidopsis protoplasts . Luciferase activity measurements indicated that co-expression of these two fusion proteins generated significantly higher luciferase activity than all controls tested ( Figure 6D ) , which suggests that SHI1 can interact with FRY2/CPL1 in plant cells . Split-YFP assay also confirmed the interaction of SHI1 with FRY1 in plant protoplasts ( Figure S3 ) . Furthermore , co-immunoprecipitation assay was carried out to determine in planta interaction of these two proteins . Transgenic plants expressing FLAG-SHI1 and FRY2-c-TAP tagged proteins were created and homozygous transgenic lines were generated . The F1 plants resulting from the cross between FLAG-SHI and FRY2-c-TAP plants were used for protein isolation and co-immunoprecipitation . Figure 6E shows that SHI1 and FRY2/CPL1 could mutually co-precipitate in plants , which strongly suggests that these two proteins can form a protein complex in plant for gene regulation . The shi4 mutation was first located in the chromosome 4 and then narrowed down to the region between the BAC clones F7K2 and F7J7 . In this region , the FRY2/CPL1 gene ( At4g21670 ) was previously identified as an important regulator of stress-responsive genes [11] , [12] , [32] . Sequencing of the FRY2/CPL1 gene in the shi4 mutant determined an allelic mutation of a G to A transition in the second exon resulting in an E116K substitution in the FRY2/CPL1 protein ( Figure 7A ) . This recessive loss-of-function mutation in FRY2/CPL1 was also identified in a forward genetic screening for mutations altering wounding-induced gene expression [32] . The shi4 mutant displayed elevated luciferase expression resembling the shi1 and the previously reported fry2/cpl1 mutants [11] , [12] . Besides , the shi4 mutant also exhibited cold sensitive phenotype similar to that of the shi1 mutant ( Figure 7B ) . Analysis of SHI4-GFP fusion protein revealed a nuclear localization of SHI4 ( Figure 7C ) . Study of the expression of stress inducible genes in shi4 indicated that both shi4 and shi1 mutations affected the expression of those cold , osmotic and ABA inducible genes in a similar way ( Figure 3 ) . Taken together , these results further support that SHI1 and SHI4/FRY2/CPL1 form a functional complex in Arabidopsis to regulate the expression of stress responsive genes . The FRY2/CPL1 protein has been shown to specifically dephosphorylate the Ser-5 at the CTD repeat of the RNA polymerase II [9] , [10] . The Ser-5 phosphorylation is known to be required for recruiting the capping enzyme and stimulating mRNA capping [1] , while dephosphorylation of the Ser-5 by CTD phosphatase has been shown to decrease mRNA capping [33] . To determine whether SHI1 and SHI4/FRY2/CPL1 are involved in mRNA capping , two methods were used to analyze the ratio of capped mRNA in total mRNA of individual genes . The first method was designed based on RNA Ligation Mediated Rapid Amplification of cDNA Ends ( RLM-RACE ) with modifications in which qRT-PCR was used instead of RACE . The total RNA was treated with Calf Intestine Alkaline Phosphatase to remove free 5′phosphate in the uncapped mRNA to prevent ligation of these mRNAs with the RNA adapter . The total RNA was then treated with Tobacco Acid Pyrophosphatase to remove the cap of the capped mRNA followed by a ligation of a RNA adapter with the treated RNA population . Only the de-capped mRNAs could be ligated with the RNA adapter . The RNA was reverse transcribed into cDNAs using random primers , and the ratio of capped transcripts in total transcripts of selected genes was determined by real-time PCR . This method was used to determine the relative mRNA capping ratio of five selected genes including the luciferase transgene , AtSOT12 , At5g25280 ( a constitutively higher expressed gene in shi1 and shi4 that was found from our unpublished microarray data , Figure S4 ) , COR15A , and COR47 . As shown in Figure 8A , shi4 mutant displayed substantially increased mRNA capping ratio of all five tested genes , while shi1 mutant exhibited differential regulation of capping event in these five genes . For the LUC transgene and the endogenous stress-inducible gene COR47 , shi1 mutant showed increases in capping ratios comparable to that in shi4 mutant . However , the shi1 mutation did not alter the capping ratio of the endogenous AtSOT12 mRNA and only caused marginal increases in capping ratios of At5g25280 and COR15A . These results suggest that SHI4/FRY2/CPL1 is the major player in modulating mRNA capping and SHI1 protein is involved in capping of some mRNAs by partnering with SHI4 . The second method was a 5′RACE-based method to determine the 5′-m7G cap that can be reverse transcribed into a C in the first strand of the cDNA [34] . This method was first verified by detection of capped mRNA captured by the Arabidopsis cap-binding protein eIF4E ( At4g18040 ) and uncapped mRNA incapable of binding by eIF4E . The Arabidopsis eIF4E was fused with GST and expressed and purified from E . coli . The binding specificity and kinetics of this fusion protein with capped mRNA were analyzed according to the previously published protocol [35] . The GST fused Arabidopsis eIF4E was found to specifically bind with capped mRNA and the binding constant is 0 . 18 nM ( Figure S5 ) . Purified GST-eIF4E proteins were incubated with Arabidopsis total RNA and capped mRNAs associated with the fusion protein were pulled down with the resin against the GST tag . 5′RACE results showed that 92% of the eIF4E-bound luciferase mRNAs have a 5′-cap that was reverse transcribed into the cDNA , while approximately 80% of the unbound luciferase mRNA did not show 5′ cap . This result supports that the 5′RACE based method is a reliable method for mRNA 5′ cap detection . Therefore , the 5′RACE-based method was used to detect the absolute ratio of capped transcripts in total transcripts of the selected genes . Figure 8B shows that the ratios of capped transcripts in total transcripts of luciferase , AtSOT12 , and At5g25280 genes in shi4 mutant were significantly higher than that in the wild type , while shi1 mutant showed significantly higher capping ratio of the luciferase mRNA , but exhibited no change in the endogenous AtSOT12 mRNA capping and slight increase in At5g25280 mRNA capping when compared with wild type . These results are consistent with the results showing in Figure 8A and strongly support that SHI1 and SHI4/FRY2/CPL1 act to negatively regulate mRNA capping . To determine whether SHI1 and SHI4/FRY2/CPL1 are involved in other co-transcriptional processes , a 3′RACE analysis was carried out to pinpoint the polyadenylation sites of the five selected genes transcripts . Major polyadenylation sites were found in four of the five genes , and the AtSOT12 gene transcripts exhibited a dispersed pattern of polyadenylation sites mainly downstream of the putative polyadenylation signal sequences ( Figure 9A ) . Two major polyadenylation sites were found in the luciferase mRNAs; one ( designated 1st PA ) is located at the 21th position upstream of the canonical polyadenylation signal ( cPA ) sequence AAUAAA and the other ( 2nd PA ) at the position of the 13th nucleotide downstream of the cPA ( Figure 9A ) . In wild type , polyadenylation at the 1st and 2nd PA sites were 44 . 4% and 33 . 3% , respectively . In shi1 and shi4 mutants , however , polyadenylation at the 1st PA site was reduced to about 20% , while polyadenylation at the 2nd PA site was increased to about 60% ( Figure 9B ) . AtSOT12 transcripts did not show a major polyadenylation site , but more than 70% of the AtSOT12 transcripts in wild type displayed polyadenylation downstream of the cPAs . This ratio was significantly increased in the shi1 and shi4 mutants ( Figure 9B ) . Both shi1 and shi4 mutations also strongly affected polyadenylation site selection in COR47 transcripts . Polyadenylation at the major PA site of COR47 in shi1 and shi4 mutants reduced remarkably when compared with that in wild type ( Figure 9B ) . shi4 , but not shi1 mutant showed significant reduction in polyadenylation at the major PA site of At5g25280 , and both mutants did not affect polyadenylation site selection of COR15A ( Figure 9B ) . These results indicate that the shi1 and shi4 mutations have profound influence on PA site selection of the LUC transgene and also affect some endogenous genes . SHI1 is likely to be involved in some , but not all genes that are regulated by SHI4 , as suggested by both capping and PA site selection analyses shown in Figure 8 and Figure 9 .
Gene regulation is central for growth , development and adaptation to environmental changes in all living organisms . In plants , many genes are environmentally regulated , and proper response of these genes is critical for stress response and tolerance . Stress-inducible genes must be repressed or silenced at normal growth conditions but can be readily activated upon stress treatments . In the past decades , intensive studies have been focused on the activation mechanisms of inducible genes in response to stress conditions . Consequently , a number of cis-elements and transacting proteins required for gene induction have been identified [36] . For instance , the regulatory element DRE ( dehydration responsive element ) was identified from the drought , salt and cold inducible promoters and found to be recognized by the transcription factors DREB1/CBF and DREB2 [37]–[39] . However , little attention has been paid to the repression mechanisms of stress inducible genes at normal growth conditions . In this study , we utilized a luciferase-based mutant screening system to identify repressor proteins for stress inducible genes . We uncovered two repressor proteins , SHI1 and SHI4/FRY2/CPL1 that can form a complex and repress gene expression by modulating transcription and co-transcriptional processes . Interestingly , the SHI1 protein was also identified as a negative regulator of heat-inducible genes in a recent study using forward genetic screening for mutations affecting luciferase expression driven by the cold-inducible CBF2 promoter [40] . Thus , SHI1 protein might be a general repressor for some of the stress-inducible genes . The cold and ABA responsive phenotypes of shi1 and shi4 protein could be attributed to mis-regulation of those cold and/or ABA-responsive genes as shown in Figure 3 . SHI1 protein belongs to the family of KH domain containing proteins comprising of 26 members in Arabidopsis . The nuclear localization of SHI1 ( Figure 5C ) indicated that SHI1 functions in a nuclear-based process . Moreover , we found that SHI1 can interact with the CTD phosphatase FRY2/CPL1 , a previously characterized protein that dephosphorylates the Ser-5 at the CTD of the RNA polymerase II [9] , [10] . Thus , it is conceivable that the SHI1 may modulate the CTD phosphorylation status through interacting with FRY2/CPL1 , thereby regulating transcription and co-transcriptional processes . Functional interaction between SHI1 and FRY2/CPL1 was evidenced by the following findings . First , our genetic screening also recovered a fry2/cpl1 allele named shi4 , and shi4 exhibited luciferase imaging and stress response phenotypes similar to the shi1 mutant ( Figure 7 ) . Second , SHI1-FRY2/CPL1 interaction was verified by several protein interaction techniques including yeast two-hybrid assay , pull-down assay , split-luciferase assay and in planta Co-IP analysis ( Figure 6 ) . These analyses indicate that SHI1 directly interacts with FRY2/CPL1 in plant cells . Third , the shi1 mutation disrupted the interaction between SHI1 and FRY2/CPL1 ( Figure 6 ) , which suggests that SHI1 requires FRY2/CPL1 for its function . Forth , shi1 and shi4 mutants exhibited very similar expression patterns of stress inducible genes ( Figure 3 ) . These evidences strongly support that SHI1-FRY2/CPL1 forms a functional complex to regulate gene expression . Both SHI1 and FRY2/CPL1 contain domains for interaction with nucleic acids . SHI1 contains five KH domains that have been considered as RNA or single stranded DNA binding domains , while FRY2/CPL1 possesses two dsRNA binding domains . Although both domains were proposed to interact with nucleic acids , our deletion assay for SHI1-FRY2/CPL1 interaction revealed that the third KH domain in SHI1 and the first dsRNA binding domain in FRY2/CPL1 are required for such interaction . This indicates that both KH domain and dsRNA binding domain can mediate protein-protein interaction . Interestingly , we found that , in addition to the third KH domain , the first KH domain in SHI1 is also sufficient to interact with FRY2/CPL1 ( Figure 6A ) . The deletion analysis showing in the Figure 6A also raised a possibility of intramolecular interactions within SHI1 because KH2 inhibits the interactions of KH1 and KH3 with FRY2/CPL1 . To test whether intramolecular interactions among the KH domains exist within the SHI1 protein , we carried out a yeast two-hybrid assay for each KH domain . We found that the KH2 can interact with both KH1 and KH3 , and KH3 alone can activate the reporter gene expression in yeast cells ( Figure S6 ) . Self-activation of the reporter gene expression by the KH3 indicates that the KH3 may be able to interact with and recruit the transcription machinery to the promoter for transcription . These results suggest that SHI1 protein may undergo structural rearrangement upon binding with FRY2/CPL1 . This structural rearrangement may promote SHI1 interactions with chromatin and components within the transcription machinery , thus acting as a bridging protein to recruit FRY2/CPL1 to the transcription initiation site through its KH domains that are capable of interacting with nucleic acids and proteins . SHI1-FRY2/CPL1 complex is involved in mRNA 5′-capping , which is supported by our findings shown in Figure 8 . This is consistent with the facts that FRY2/CPL1 functions as a Ser-5 specific CTD phosphatase [10] and the Ser-5 phosphorylation is required for recruiting 5′ capping enzymes [1] . Based on our results , we propose that , at normal growth conditions , the SHI1-FRY2/CPL1 complex is associated with the general transcription machinery and perhaps other unidentified negative regulators at the transcription initiation site of the stress inducible promoter . This repressor complex inhibits the transition from transcription initiation to elongation due to dephosphorylation of the Ser-5 in the CTD and compromising subsequent 5′ capping of the nascent transcripts . According to this model , there might be an abortive transcription at the stress inducible promoter that ensures correct initiation site for transcription and readiness for transcription upon stress treatments . In fact , we detected short transcripts ranging from 40 to about 200 nucleotides that were transcribed from the AtSOT12 promoter-luciferase fusion gene . Under stress conditions , the repressor complex could readily become an active transcription complex by simply removing the SHI1-FRY2/CPL1 proteins through binding of activators or modifications of the repressor components . The SHI1 transcript level is remarkably reduced by salt stress treatment ( Figure 5D ) , which represents a mechanism of de-repression of a stress inducible gene under stress conditions . Interestingly , amongst the five tested genes , SHI4/FRY2/CPL1 is required for inhibition of capping of all five genes transcripts , while SHI1 displays differential regulation of capping of the five genes . This suggests that SHI4/FRY2/CPL1 does not require SHI1 at all gene loci for modulation of mRNA capping . Another interesting observation is that shi1 and shi4 mutations had opposite effects on the stress-induced gene expression of COR15A and COR47 ( Figures 3 and S2 ) , while these two mutants showed different but not opposite effects on mRNA capping and polyadenylation site selection of these two genes ( Figures 8 and 9 ) . The expression patterns of COR15A and COR47 in shi1 and shi4 mutants highly resembles the expression patterns of these two genes in another shiny mutant named shi2 with a mutation in a gene encoding an mRNA splicing factor ( Shi lab , unpublished data ) . Thus , it is possible that reduced induction of COR15A by stress treatments in shi1 and shi4 mutants is due to mal-splicing of COR15A mRNA , whereas increased induction of COR47 in these two mutants is mainly attributed to elevated mRNA capping . In fact , shi1 and shi4 mutants exhibited stronger effects on COR47 mRNA capping and polyadenylation site selection than COR15A ( Figures 8 and 9 ) . In spite of the difference in the capping of endogenous genes transcripts , both SHI1 and SHI4 exhibit strong inhibition of capping of the transgene luciferase mRNA ( Figures 8 ) . In addition , strong effects of the shi1 and shi4 mutations on polyadenylation site selection of the transgene luciferase were also observed ( Figure 9 ) . Whether the SHI1-SHI4/FRY2/CPL1 complex is involved in transgene silencing through modulating co-transcriptional processes such as capping and polyadenylation of the transgenes deserves further investigation . Increased 5′ capping of the luciferase transgene in the shi1 and shi4 mutants could explain why the fold change on luciferase activity is significantly higher than the fold change on luciferase transcript level ( Figure 1B and 1D ) . We deduce that , due to more capped luciferase mRNAs in these two mutants than in the wild type , the translation efficiency of the luciferase mRNA is higher in the shi1 and shi4 than in the wile type . Substantial difference on the selection of polyadenylation sites between the mutants and wild type ( Figure 9 ) suggests that lacking a functional SHI1 or SHI4 in the mutants may have caused formation of a complex not only with low repression activity but also lacking components that are needed for polyadenylation site selection . These hypotheses need to be further verified . Identification of the components within the repressor complex involving SHI1-FRY2/CPL1 will greatly help our understanding about gene repression , which deserves further study .
The firefly luciferase ORF fragment was released from the RD29A-LUC construct by digestion with Hind III and Sma I and inserted into pCAMBIA1381Z at Hind III and Pmal I by replacing the original GUS gene to form pCAMBIA1381Z-LUC . The promoter and the entire 5′-UTR of At2g03760 was amplified using Pfu polymerase ( Stratagene ) with a forward primer ccccccggggaaggtttccaccttcacactc and a reverse primer aaaactgcagtgttgagacttgagagatcgatca with restriction sites underlined , then inserted into pCAMBIA1381Z-LUC at Xma I and Pst I to form a transcriptional fusion of AtSOT12P-LUC . Arabidopsis thaliana Columbia-0 plants expressing AtSOT12P-LUC were obtained by Agrobacterium-mediated transformation using the floral dip method [30] . A homozygous line ( named T3 9-1 ) showing normal growth and development and induced luciferase expression by salt stress treatment was selected as the parental line ( referred to as wild type ) for mutagenesis using ethyl methane sulfonate ( EMS ) . Seedlings of the M2 generation from the EMS-mutagenized seeds were screened for mutants with altered luciferase expression with or without NaCl treatment by using a charge-coupled device camera ( DU434-BV , Andor Technology , Connecticut ) according to the previously published protocol [41] . The putative mutants were transferred to soil and subjected to a re-screening process to eliminate the false positives . To determine the sensitivity of seed germination to ABA , the seeds were sterilized for 15 min in 20% Clorox bleach with 0 . 05% Triton X-100 , washed 3–5 times with sterilized water , suspended in 0 . 3% low melting point agarose and incubated at 4°C for 2 days . The seeds were then planted onto half MS agar medium with different concentrations of ABA and incubated at room temperature under 16 h/8 h fluorescent light cycle . Germination was scored when cotyledon was emerged . The test of plant sensitivity to cold conditions was carried out by transferring two-week old seedlings growing in soil into a 4°C cold room and incubated under 16 h/8 h light cycle . For map-based cloning , mutants were crossed with wild-type Landsberg erecta and the F1 plants were selfed to generate the F2 seeds . The F2 seedlings showing higher luciferase expression were selected for SSLP marker-assisted genetic mapping . The mutations were identified by sequencing candidate genes . For genetic complementation of the shi1 mutation , two T-DNA insertion lines SALK_143161 and SALK_001448 of the SHI1 were obtained from the Arabidopsis Biological Resource Center ( ABRC ) [42] . Homozygous T-DNA lines were isolated by using a PCR-based method . The shi1 mutant was crossed with the T-DNA lines and the F1 seedlings resulted from the genetic crosses were subjected to luciferase imaging . For molecular complementation assay , a genomic DNA fragment containing the SHI1 open reading frame along with 1910 bp of sequence upstream of the translation start codon and 262 bp of sequence downstream of the translation stop codon was amplified from the BAC clone MINB8 using Pfu polymerase ( Stratagene ) . The fragment was then inserted into BamH I and Not I sites of the Gateway entry vector pENTR1A and was recombined into the plant transformation Gateway vector pMDC100 ( ABRC stock number CD3-746 ) with Gateway LR Clonase II Enzyme Mix ( Invitrogen ) following the manufacturer's instruction . The resulting construct was transformed into shi1 mutant and the T2 transgenic lines were used for luciferase imaging . The promoter region of the SHI1 gene with 1847 bp upstream of the translation start codon was amplified using from the BAC clone MINB8 using Pfu polymerase ( Stratagene ) and inserted into BamH I amd Pst I sites of the binary vector pCAMBIA1381Z to create a transcriptional fusion of the SHI1 promoter with the GUS reporter gene . The resulting construct was transferred into Colunbia-0 wild-type plants by the floral dip method [30] . The T2 seedlings were stained with X-Gluc staining buffer ( 10 mM Tris pH 7 . 0 , 10 mM EDTA , 0 . 1% Triton X-100 and 2 mM 5-bromo-4-chloro-3-indolyl-beta-D-glucuronic acid ) for 12–24 hours at 25°C , followed by incubating in 70% ethanol to remove chlorophyll . For protein subcellular localization assay , the ORF of the SHI1 gene was recombined from pENTR1A into the PMDC43 vector [43] to create SHI1-GFP fusion and the ORF of FRY2 was recombined into pEarleyGate103 [44] for FYR2-GFP fusion . The fusion constructs were transformed into Arabidopsis by the floral dip method [30] and the T2 transgenic plants were used to examine the location of the GFP fluorescence using confocal microscope . For gene expression study , wild-type and shi1 mutant seeds were planted on half MS agar medium . Ten-day-old seedlings were subjected to NaCl , ABA and cold treatments as previously described [11] . To study the expression of SHI1 , 10-day-old wild type seedlings were treated with different stress conditions following the method described by Chung et al . [45] and different parts of plants were collected from soil-growing plants . Total RNA was extracted from the seedlings and analyzed by RNA blotting . The DNA probes for the tested genes were PCR-amplified by using the following primers: SHI1 , atggagagatctagatccaagagaaactac and tactgctgtcttgttgtccctgag; COR15A , aaagaaagcttcagatttcgtg and agaatgtgacggtgactgtgg; KIN1 , tctcttctcatcatcactaacc and tttggggagtttgatctttcgc; COR47 , cgacgagaaagcagaggattc and cgaggtgatcatgtgaataacg; CBF1 , cgatagtcgtttccatttttgt and ttgctagattcgagacgagcc; CBF2 , ttcgatttttatttccatttttgg and ccaaacgtccttgagtcttgat; CBF3 , taaaactcagattattatttccattt and aggagccacgtagagggcc; DREB2A , caaaacaatatgaagctttttgg and agtgtgtattattcattcctg; LUC , tggagagcaactgcataagg and tgacgcaggcagttctatgc; AtSOT12 , atgtcatcatcatcatcagttcctg and tcaagaagaaaatttaagaccagaacc; and β-tubulin gene ( AT5G23860 . 1 ) , cgtggatcacagcaatacagagcc and cctcctgcacttccacttcgtcttc . DNA probes were radioactively labeled with [α-32P] dCTP using the Prime-It II Random Primer Labeling Kit ( Stratagene ) . Quantitative RT-PCR to determine the expression levels of LUC , CBF3 , COR15A and COR47 was carried out as follows . 2 µg of total RNA isolated with Plant RNA Purification Reagent ( Invitrogen ) was reverse transcribed into cDNAs using the avian myeloblastosis virus ( AMV ) reverse transcriptase ( Promega ) and oligo dT ( 15 ) . The cDNAs were used as template for quantitative real-time PCR using ABI PRISM 7500 Real-Time PCR Systems ( Applied Biosystems ) and the iTaq SYBR Green Supermix with ROX kit ( Bio-Rad , Hercules , CA , USA ) . The following primers were used: tggagagcaactgcataagg and gttcacctcgatatgtgcatctgt for LUC; cgacgacggatcatggcttc and ctccataacgatacgtcgtcatc for CBF3; agatggtgagaaagcgaaagactac and gaactctgccgccttgtttg for COR15A; ttcaccagctgtcacgtcca and cttctcctccggatgttcca for COR47; ccgagtatgatgaggcaggtc and cccattcataaaaccccagc for actin2 for RNA normalization . The yeast two-hybrid screening with Saccharomyces cerevisiae strainY190 was performed in accordance with the previously described protocol [46] . The cDNA library for yeast two-hybrid screening was obtained from the ABRC ( stock no . CD4-300 ) [47] . The ORF of SHI1 from the cDNA clone G16563 ( ABRC ) was recombined into the destination vectors pDEST-GADT7 ( prey vector ) and pDEST-GBKT7 ( bait vector ) [48] using LR clonase kit ( Invitrogen ) . Self-activation test verified that the bait pGBKT7–SHI1 plasmid has no autonomous activity of the reporter genes in the yeast strain Y190 . For screening , yeast cells harboring the bait construct were transformed with the cDNA library and plated onto synthetic high-stringency selection medium lacking tryptophan , leucine and histidine supplemented with 25 mM 3-amino-1 , 2 , 4-triazole ( Sigma ) . The putative positive cDNA clones were further confirmed by the β-galactosidase assay and tested for specificity by co-transformation into Y190 , either alone or in combination with the empty pDEST-GBKT7 vector . The cDNA inserts from positive clones were sequenced using a Big-Dye Terminator Cycle Sequencing Kit ( Applied Biosystems ) and the ABI 3100 DNA sequencer . Deletion analysis was used to determine the domains required for interaction between SHI1 and FRY2 in the yeast strain Y190 . For a series deletions of the carboxyl terminus of SHI1 , the forward primer is acgcgtcgacatggagagatctagatccaagagaaactac with Sal I restriction site ( underlined ) , the reverse primers are cggaattcgtaacaagtggtaccgccattctg , cggaattcgttgttattaaattatctttatccggaataag , cggaattctcggagtagacattctcaccaactg , cggaattccctccaccaggtctaactccac with EcoR I restriction site ( underlined ) ; for the amino terminal deletions of SHI1 , the reverse primer is gatatctcggtccatcctcttgtatgctcaaaatgaag with EcoR V restriction sites ( underlined ) , the forward primers are acgcgtcgacatgagtgttcatgacaggattttggaga , acgcgtcgacatgtcatctcgtctaagggagagtcagc , acgcgtcgacatgttgcacattcaaactcagatcatagat and acgcgtcgacatggagatcagagctgctcggga with Sal I restriction sites ( underlined ) . For the Carboxyl terminal deletions of FRY2 , the forward primer is acgcgtcgacatgcttcatgagaatcgcaggc with Sal I restriction sites ( underlined ) , the reverse primers are cggaattcccagtgtgcctcatagaaccttct , cggaattcgctaaattctgtatagaagcttcagcag and cggaattcgtctccgttgctgagacacttcg with EcoR I restriction sites ( underlined ) ; for the amino terminal deletions of FRY2 , the reverse primer is cggaattcgcctccttcagtcttctctccac with EcoR I restriction sites ( underlined ) , the forward primers are acgcgtcgac atgacttcagctgatgttctacacgga , acgcgtcgacatggctgatggatatatgcgtgcaa , acgcgtcgac atgggctccattactgcactcaggg and acgcgtcgacatgtccagtgtgagatcaatgcttgg with Sal I restriction sites ( underlined ) . The entire ORF of FRY2 was amplified with the primers acgcgtcgacatgtatagtaataatagagtagaagtgtttcatggt with Sal I restriction site ( underlined ) and ataagaatgcggccgcgagtatcttcccgaagatggca with Not I restriction site ( underlined ) without stop codon from cDNA using Pfu polymerase ( Stratagene ) . The PCR fragments were cloned into the Gateway entry vector pENTR1A ( Invitrogen ) , then recombined into the destination vectors pDEST-GADT7 and pDEST-GBKT7 , respectively , using LR clonase kit ( Invitrogen ) . The resulting plasmids were transformed into Y190 containing pGBKT7-FRY2 or pGBKT7-SHI1 to test interactions between different forms of SHI and FRY2 . The ORF of SHI1 without start codon was amplified with the primers cgggatccgagagatctagatccaagagaaactaccac with restriction site BamH I ( underlined ) and cggaattccggtccatcctcttgtatgctc with restriction site EcoR I ( underlined ) using Pfu polymerase ( Stratagene ) and was cloned into pGEX2T to create a GST-SHI1 fusion construct . The resulting plasmid was transformed into E . coli Rosetta-gami 2 host strains ( Novagen ) and individual colonies were inoculated in LB medium and grown at 37°C overnight . The cultures were then diluted to approximately OD600 of 0 . 1 and grown at 37°C until they reached OD600 0 . 5–1 . 2 . The protein expression was induced with 0 . 5 mM isopropyl β-D-1-thiogalactopyranoside for an additional 16–24 h at 30°C on a shaker . Bacterial cells were pelleted and then resuspended in the lysis buffer ( 50 mM Tris–HCl pH 8 . 0; 100 mM NaCl and 1 mM EDTA ) . After sonication and centrifugation , the recombinant protein in the supernatant was purified by using GST Bind Resin ( Novagen ) . The fragment of FRY2 encoding the first dsRNA binding domain ( 666–855 aa ) in the pENTR1A vector was recombined into the pDEST17 vector to generate a HIS-tagged protein under the control of the T7 promoter . The plasmid was used for in vitro transcription-coupled translation in the presence of [35S]-Methionine using the TNT Quick Coupled Transcription/Translation Systems ( Promega ) according to the manufacturer's instructions . The purified GST-SHI1 and in vitro translated peptides of FRY2 were analyzed by protein gel blotting using anti-GST and anti-HIS antibodies , respectively . Pull-down experiments were performed as follows . GST ( as negative control ) or GST-SHI1 protein was immobilized to GST Bind Resin ( Novagen ) , which was incubated with [35S]-labeled peptides of FRY2 ( HIS-cFRY2 ) for 30 min at room temperature in 100 µL of the binding buffer ( 20 mM Tris-HCl , pH 7 . 2 , 10 mM MgCl2 , and 2 mM DTT ) . After extensive washing with PBS buffer , the beads were resuspended in 50 µL of the protein loading buffer and the proteins were resolved in 12% SDS–polyacrylamide gel . The gels were dried and placed in direct contact with the X-ray film ( Kodak ) in dark at room temperature for autoradiography . For split luciferase ( Renilla reniformis ) complementation assay , the SHI1 ORF was amplified with a forward primer acgcgtcgacatggagagatctagatccaagagaaactac with Sal I restriction site ( underlined ) and a reverse primer gatatctcggtccatcctcttgtatgctcaaaatgaag with eliminated stop codon using Pfu polymerase ( Stratagene ) . The PCR fragment was digested with Sal I only and inserted into pENTR1A after digested with Sal I and EcoR V . The SHI1 ORF was then recombined into pDUExAn6 vector and the FRY2 ORF in the pENTR1A vector was recombined into pDUEXDc6 vector [31] . For split YFP complementation assay , the SHI1 ORF was amplified with a forward primer ccgctcgagatggagagatctagatccaagagaaactac with a Xho I restriction site ( underlined ) and a reverse primer cggaattccggtccatcctcttgtatgctc with a EcoR I restriction site ( underlined ) without stop codon using Pfu polymerase ( Stratagene ) and inserted into pSAT4A-nEYFP-N1 [49] . The FRY2 ORF was fused to the C-terminal of YFP in the pSAT4A-cEYFP-N1 [49] , which was amplified using a forward primer ccgctcgagatgtatagtaataatagagtagaagtgtttcatggt with a Xho I restriction site ( underlined ) and a reverse primer cggaattcagagtatcttcccgaagatggca with a EcoR I restriction site ( underlined ) without stop codon using Pfu polymerase ( Stratagene ) . Preparation of Arabidopsis protoplasts and transformation of the constructs into the protoplasts with PEG-mediated method were performed essentially following Yoo et al . [50] . The protoplasts transformed with the constructs for split luciferase assays were transferred to a 96-well plate and subjected to luciferase imaging by using the luciferase imaging system ( DU434-BV , Andor Technology , Connecticut ) . Fluorescence imaging of YFP in the split YFP assay and Hoechst 33342 staining was carried out by using an inverted fluorescence microscope . For co-immunoprecipitation ( Co-IP ) experiments , the ORF of SHI1 was recombined into the pEarleyGate vector 203 [44] for Flag-SHI1 fusion . The ORF of FRY2 was recombined into pEarleyGate 205 [44] for FYR2-cTAP fusion . The fusion constructs were transformed into Arabidopsis by floral dip method [30] . The T2 transgenic plants of Flag-SHI1 crossed with FYR2-cTAP plants and the F1 seedlings were used for protein isolation . Co-IP assay was carried out essentially following the previously described method [44] . RLM-qRT-PCR was used to analyze the relative ratio of capped transcripts in total transcripts of LUC , AtSOT12 , At5G25280 , COR15A and COR47 genes . This method was developed based on the RLM-RACE method . Total RNA was first treated by using Firstchoice RLM-RACE Kit ( Invitrogen ) including cipping , decapping , RNA adapter ligation , and cDNA synthesis through reverse transcription using random primers , as described in the manufacturer's manual . The cDNAs were then used as templates for Quantitative real-time PCR analysis of the capped mRNA and total mRNA of an individual gene . Briefly , 10 µg of total RNA isolated with Plant RNA Purification Reagent ( Invitrogen ) was treated by Calf Intestine Alkaline Phosphatase ( CIP ) to remove free 5′-phospates from uncapped mRNA , rRNA or tRNA and leave full-length , capped mRNA intact . This step prevents the uncapped mRNA from ligation with the RNA adapter described below . The CIP-treated RNA was treated by Tobacco Acid Pyroposphatase ( TAP ) to remove the cap structure from the full-length , capped mRNA and leave a monophosphate at the 5′-end of them . An adapter oligonucleotide ( gcugauggcgaugaaugaacacugcguuugcuggcuuugaugaaa ) was then ligated to full-length , decapped mRNA using T4 ligase . Finally , 1 µg of treated RNA was reverse transcribed using the M-MLV reverse transcriptase and Random Decamers . The constructed cDNA was diluted 10 times , 20 times and 40 times and used as templates for Quantitative real-time PCR . Quantitative real-time PCR was performed by using ABI PRISM 7500 Real-Time PCR Systems ( Applied Biosystems ) and the iTaq SYBR Green Supermix with ROX kit ( Bio-Rad , Hercules , CA , USA ) . The following primers were used: tgatggcgatgaatgaacactg and tagaggatagaatggcgccg for capped LUC mRNA , gctggagagcaactgcataagg and tagcttctgccaaccgaacg for total LUC mRNA , tgatggcgatgaatgaacactg and gcaggaactgatgatgatgatgac for capped AtSOT12 mRNA , cttgggagatgaagatctgacaca and cgtttttggcagatcaagattc for total AtSOT12 mRNA , gctggagagcaactgcataagg and gacggtgatttggatcggag for capped At5G25280 mRNA , atcaaacggatctgcttcgc and acctgacgacgacggagatg for total At5G25280 mRNA , tgatggcgatgaatgaacactg and agccataccagtgagaacagctc for capped COR15A mRNA , gagctgttctcactggtatggct and ttctggccgactctgacagc for total COR15A mRNA , tgatggcgatgaatgaacactg and gaccgttggtgtctcgtgct for capped COR47 mRNA , aagaacaacgttcccgagca and cgttgtctcttgaggtttcacttc for total COR47 mRNA , caaccaatcgtgtgtgacaatg and acagccctgggagcatcat for actin2 for RNA normalization . Note that the forward primer used for capped mRNA amplification was derived from the RNA adapter , so the PCR only specifically amplified the decapped and RNA adapter ligated mRNA of an individual gene . The ratio between the capped transcripts and total transcripts was calculated and presented as the relative capping ratio of each gene shown in Figure 8A . 5′ RACE was used to analyze the capping ratio of the luciferase mRNAs . Briefly , 2 µg of total RNA isolated with RNeasy Plant Mini Kit ( Qiagen ) was reverse transcribed using the avian myeloblastosis virus ( AMV ) reverse transcriptase ( Promega ) following the manufacture's instruction . The first strand cDNA purified with the PCR purification kit ( Qiagen ) was added with a Poly ( dA ) tail using terminal transferase ( New England Biolabs ) . The cDNA having a poly ( A ) tail was amplified with a primer ctgatctagaggtaccggatcc-dT ( 17 ) and the luciferase gene specific primer gtttcatagcttctgccaacc for 5′RACE using GoTaq DNA Polymerase ( Promega ) . The PCR products were further amplified with an adaptor primer ctgatctagaggtaccggatcc and the nested luciferase gene specific primer gcagttgctctccagcggtt . The PCR fragments were then cloned into pGEM-T Easy vector ( Promega ) and sequenced using a Big-Dye Terminator Cycle Sequencing Kit ( Applied Biosystems ) on the ABI 3100 DNA Sequencer following a standard protocol . At least 20 independent clones were sequenced and the additional G at the very end of each cDNA was counted as from a capped mRNA . The polyadenylation sites of the mRNAs were determined by using 3′ RACE method . Briefly , 2 µg of total RNA isolated with Plant RNA Purification Reagent ( Invitrogen ) was reverse transcribed using the avian myeloblastosis virus ( AMV ) reverse transcriptase ( Promega ) and oligo dT ( 15 ) . The cDNA corresponding to the 3′ end of the target gene mRNA was then synthesized by PCR amplification using the adaptor-dT ( 15 ) ( ctgatctagaggtaccggatcc-dT ( 15 ) ) and the target gene specific primer ( LUC: gttttggagcacggaaagacg; AtSOT12: ttgccaaatggaatagagactaaaac; At5G25280: gcttatgagcctcgtcgtagtaga; COR15A: caaacaaggcggcagagttc; COR47: ttcaccagctgtcacgtcca ) . The PCR product was then used as template for a nested PCR amplification by using the adaptor primer ctgatctagaggtaccggatcc and the nested target gene specific primer ( LUC: cgtggattacgtcgccagtc; AtSOT12: ggagagatactttgagtgagtcattgg; At5G25280: tagactcgcatctatgtcgaaagc; COR15A: gttcgcggagggtaaagcag; COR47: tggaacatccggaggagaaga ) . The PCR-amplified fragments were then cloned into pGEM-T Easy vector and sequenced using a Big-Dye Terminator Cycle Sequencing Kit ( Applied Biosystems ) on the ABI 3100 DNA Sequencer following a standard protocol . At least 20 independent clones were sequenced and the polyadenylation sites were scored according to the sites linking with the PolyA .
|
Plants , including important economic crops , frequently grow under unfavorable conditions that largely reduce their production potential . Plants respond to these stress conditions by adjusting physiological status resulting from changes in gene expression . Many genes that are repressed at normal growth conditions are activated in response to stresses . The presented work here attempted to answer the question as to how stress inducible genes are repressed at normal growth conditions . We established a genetic system to identify genes that are essential for such repression and found a protein complex that plays crucial roles in regulating stress inducible gene expression . Our work also revealed important molecular processes that are modulated by the identified protein complex . These findings will help our understanding about gene expression and regulation in general and the molecular mechanisms governing plant stress response in particular .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"plant",
"science",
"plant",
"physiology",
"rna",
"processing",
"gene",
"expression",
"genetics",
"plant",
"genetics",
"molecular",
"genetics",
"biology",
"plants",
"flowering",
"plants",
"gene",
"function"
] |
2013
|
The Arabidopsis RNA Binding Protein with K Homology Motifs, SHINY1, Interacts with the C-terminal Domain Phosphatase-like 1 (CPL1) to Repress Stress-Inducible Gene Expression
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Streptococcus agalactiae ( Group B Streptococcus , GBS ) normally colonizes healthy adults but can cause invasive disease , such as meningitis , in the newborn . To gain access to the central nervous system , GBS must interact with and penetrate brain or meningeal blood vessels; however , the exact mechanisms are still being elucidated . Here , we investigate the contribution of BspC , an antigen I/II family adhesin , to the pathogenesis of GBS meningitis . Disruption of the bspC gene reduced GBS adherence to human cerebral microvascular endothelial cells ( hCMEC ) , while heterologous expression of BspC in non-adherent Lactococcus lactis conferred bacterial attachment . In a murine model of hematogenous meningitis , mice infected with ΔbspC mutants exhibited lower mortality as well as decreased brain bacterial counts and inflammatory infiltrate compared to mice infected with WT GBS strains . Further , BspC was both necessary and sufficient to induce neutrophil chemokine expression . We determined that BspC interacts with the host cytoskeleton component vimentin and confirmed this interaction using a bacterial two-hybrid assay , microscale thermophoresis , immunofluorescent staining , and imaging flow cytometry . Vimentin null mice were protected from WT GBS infection and also exhibited less inflammatory cytokine production in brain tissue . These results suggest that BspC and the vimentin interaction is critical for the pathogenesis of GBS meningitis .
Streptococcus agalactiae ( Group B Streptococcus , GBS ) is an opportunistic pathogen that asymptomatically colonizes the vaginal tract of up to 30% of healthy women . However , GBS possesses a variety of virulence factors and can cause severe disease when transmitted to susceptible hosts such as the newborn . Despite widespread intrapartum antibiotic administration to colonized mothers , GBS remains a leading cause of pneumonia , sepsis , and meningitis in neonates [1 , 2] . Bacterial meningitis is a life-threatening infection of the central nervous system ( CNS ) and is marked by transit of the bacterium across endothelial barriers , such as the blood-brain barrier ( BBB ) or the meningeal blood-cerebral spinal fluid barrier ( mBCSFB ) . Both consist of a single layer of specialized endothelial cells that serve to maintain brain homeostasis and generally prevent pathogen entry into the CNS [3–5] . Symptoms of bacterial meningitis may be due to the combined effect of bacterial adherence and brain penetration , direct cellular injury caused by bacterial cytotoxins , and/or activation of host inflammatory pathways that can disrupt brain barrier integrity and damage underlying nervous tissue . [6–8] Bacterial meningitis typically develops as a result of the pathogen spreading from the blood to the meninges . In order to disseminate from the blood into the brain , GBS must first interact with barrier endothelial cells [9] . A number of surface-associated factors that contribute to GBS-brain endothelium interactions have been described such as lipoteichoic acid ( LTA ) [10] , pili [11] , serine-rich repeat proteins ( Srr ) [12] , and streptococcal fibronectin-binding protein ( SfbA ) [13] . Pili , the Srr proteins , and SfbA have been shown to interact with extracellular matrix ( ECM ) components , which may help to bridge to host receptors such as integrins or other ECM receptors . However , a direct interaction between a GBS adhesin and an endothelial cell receptor has not been described . Antigen I/II family ( AgI/II ) proteins are multifunctional adhesins that have been well characterized as colonization determinants of oral streptococci [14] . These proteins mediate attachment of Streptococcus mutans and Streptococcus gordonii to tooth surfaces and can stimulate an immune response from the colonized host [14] . Genes encoding AgI/II polypeptides are found in streptococcal species indigenous to the human mouth as well as other pathogenic streptococci such as GBS , S . pyogenes ( Group A Streptococcus , GAS ) , and S . suis [14 , 15] . Intriguingly , the GAS AgI/II protein AspA ( Group A Streptococcus surface protein ) is absent in many GAS M serotypes and is found predominantly among M serotypes implicated in puerperal sepsis and neonatal infections , including M2 , M4 , and M28 . The gene encoding AspA is located within an integrative and conjugative element designated region of difference 2 ( RD2 ) , which likely originated in GBS and was acquired by invasive GAS serotypes through horizontal gene transfer ( Fig 1A ) . It has been proposed that genes carried within RD2 may contribute to pathogenicity of both GAS and GBS in pregnant women and newborns [16 , 17] . Supporting this , AspA has been shown to facilitate GAS biofilm formation and virulence in a murine model of GAS respiratory infection [18] . Recently , in silico analysis has revealed four AgI/II gene homologs in GBS , designated Group B Streptococcus surface proteins ( BspA-D ) , that are distributed among GBS of different capsular serotypes and sequence types [15 , 19 , 20] . Previous work has shown that BspA and BspB , which share 90% sequence identity , are found in GBS strain NEM316 . BspA has been demonstrated to be important in biofilm formation as well as adherence to epithelial cells and may play a role in facilitating colonization through its ability to bind to vaginal epithelium as well as interact with the hyphal filaments of Candida albicans [15 , 20] , a frequent fungal colonizer of the lower female reproductive tract . Other GBS strains contain the homolog BspC , or in some cases BspD , which is over 99% identical to BspC , with the major difference being that BspD is missing the leader peptide for targeting to the cell surface by the Sec translocation machinery . While most of the variability between Bsp proteins is in the alanine-rich and proline-rich repeats , the V domain shares 96 to 100% identity across all Bsp homologs [15 , 20] . To date , there have not been any studies examining the impact of the AgI/II proteins on GBS invasive disease . A previous study by Chuzeville et al . identified 75 GBS genomes which contain an antigen I/II homolog . Of those 75 CDS , only 40 were associated with transcription and translation signals and out of those , 36 were 2952 base pairs in size encoding the full length BspC protein [19] . Therefore , we chose to investigate the importance of the BspC antigen I/II homolog in the pathogenesis of meningitis . Using targeted mutagenesis , we show that BspC promotes adherence of bacteria to human cerebral microvascular endothelial cells ( hCMEC ) and interacts with the host cytoskeleton component , vimentin . Additionally , we found that BspC and vimentin contribute to the development of GBS meningitis in a mouse infection model . Lastly , we observe that BspC stimulates inflammatory signaling from brain endothelial cells in vitro and in vivo and that this immune signaling involves the NF-κB pathway .
BspC contains all six domains characteristic of the AgI/II protein family and shares high homology with other streptococcal AgI/II proteins , especially GAS AspA ( Fig 1B ) . The proposed domain organization of streptococcal AgI/II polypeptides comprises a stalk consisting of the α-helical A ( alanine-rich repeats ) domain and the polyproline II ( PPII ) helical P domain , separating the V ( variable ) domain and the C-terminal domain , which contains the LPXTG motif required for cell wall anchorage [14] . While the GBS BspC structure is not known , the structure of several regions of the GBS homolog , BspA , has been solved [15] . We generated a hypothetical model of full length BspC using PyMOL ( The PyMOL Molecular Graphics System , Version 2 . 1 Schrödinger , LLC ) for the purpose of showing the overall domain structure ( Fig 1C ) . Structures of individual BspC domains were generated using Phyre2 server [21] . The V- and C-domains were modeled on the V- and C-domains of BspA ( PDB entries 5DZ8 and 5DZA , respectively ) [15] , and approximately two-thirds of the A-domain sequence was modeled on human fibrinogen ( PDB entry 3GHG ) [22] . It was not possible to generate models for the N- and P-domains , so the N-domain is shown as a sphere and the P-domain shown is a mirror image of the A-domain . We performed precise in-frame allelic replacement to generate a ΔbspC mutant in GBS strain COH1 , a hypervirulent GBS clinical isolate that is highly associated with meningitis ( sequence type [ST]-17 , serotype III ) [23 , 24] , using a method described previously [10] . We further determined the expression of surface BspC in the WT and complemented strains compared to the ΔbspC mutant by flow cytometry and immunofluorescent staining with specific BspC antibodies ( S1A–S1G Fig ) . Growth curve analysis demonstrated that the ΔbspC mutant grew similarly to the WT parental strain under the conditions used here ( S1H Fig ) . Similarly , we observed no differences in hemolytic activity or capsule abundance between the WT and mutant strains ( S1I–S1L Fig ) . High-magnification scanning electron microscopy ( SEM ) images of COH1 strains showed that the ΔbspC deletion strain exhibits similar surface morphology to the isogenic wild type ( Fig 2A and 2B ) . However , lower-magnification SEM revealed that the ΔbspC mutant appeared to exhibit decreased interaction between neighboring cells ( Fig 2C and 2D ) . Since AgI/II proteins are known to demonstrate adhesive properties in other streptococci [14] , we hypothesized that BspC would contribute to GBS interaction with brain endothelium . Thus , we characterized the ability of the ΔbspC mutant to attach to and invade hCMEC using our established adherence and invasion assays [10 , 25] . The ΔbspC mutant exhibited a significant decrease in adherence to hCMEC compared to WT GBS , and this defect was complemented when BspC was expressed in the ΔbspC mutant strain ( Fig 2E ) . This resulted in less recovery of intracellular ΔbspC mutant ( Fig 2F ) , but together these results indicate that BspC contributes primarily to bacterial attachment to hCMEC . To determine if BspC was sufficient to confer adhesion , we heterologously expressed the GBS bspC gene in the non-adherent , non-pathogenic bacterium Lactococcus lactis . Flow cytometric analysis of L . lactis confirmed surface expression of BspC protein in the strain containing the pMSP . bspC plasmid ( S2 Fig ) . BspC expression resulted in a significant increase in L . lactis adherence to hCMEC compared to L . lactis containing the control vector , while invasion was not affected ( Fig 2G and 2H ) . These results demonstrate that BspC is both necessary and sufficient to confer bacterial adherence to hCMEC . Our results thus far suggest a primary role for BspC in GBS adherence to brain endothelium . We hypothesized that these in vitro phenotypes would translate into a diminished ability to penetrate the BBB and produce meningitis in vivo . Using our standard model of GBS hematogenous meningitis [10 , 26 , 27] , mice were challenged with either WT GBS or the ΔbspC mutant as described in the Methods . The WT GBS strain caused significantly higher mortality than the isogenic ΔbspC mutant strain ( Fig 3A ) . By 48 hours , 80% of mice infected with WT COH1 had succumbed to death , while all of the mice infected with the ΔbspC mutant survived up to or past the experimental endpoint . In a subsequent experiment mice were infected with a lower dose of either WT GBS or the ΔbspC mutant and were sacrificed at a defined endpoint ( 72 hrs ) to determine bacterial loads in blood , lung , and brain tissue . We recovered similar numbers of the ΔbspC mutant strain from mouse blood and lung compared to WT; however , we observed a significant decrease in the amounts of the ΔbspC mutant recovered from the brain tissue ( Fig 3B ) . To confirm these results using other GBS strains , we constructed bspC gene deletions as described in the Methods in two other GBS strains: GBS 515 ( ST-23 , serotype Ia ) and meningeal isolate 90356 ( ST-17 , serotype III ) . Mice infected with these mutant strains were also less susceptible to infection and exhibited decreased bacterial loads in the brain compared to the isogenic parental WT strains ( S2 Fig ) . Interestingly , the ΔbspC mutant in the 515 GBS background , which is a different sequence type and serotype from the other two strains , appeared to also exhibit diminished infiltration into the mouse lungs . As excessive inflammation is associated with CNS injury during meningitis , we performed histological analysis of brains from infected animals . In WT infected mice , we observed leukocyte infiltration and meningeal thickening characteristic of meningitis that was absent in the mice infected with the ΔbspC mutant strain ( Fig 3C and 3D ) . Representative images from 8 mice , 4 infected with WT ( Fig 3C ) and 4 infected with the ΔbspC mutant ( Fig 3D ) are shown where the major areas of inflammation were observed . In subsequent experiments to quantify the total inflammatory infiltrate , whole brains from uninfected mice and mice infected with either WT GBS or ΔbspC mutant GBS were processed and analyzed by flow cytometry as described in the Methods . There was no significant difference in the numbers of CD45 positive cells between the groups of mice , however within the CD11b positive population we observed higher numbers of Ly6C positive and Ly6G positive cells in the brains of animals infected with WT GBS compared to uninfected mice and mice infected with the ΔbspC mutant strain ( Fig 3E and 3F ) , indicating an increased population of monocytes and neutrophils . Consistent with these results , we further observed that mice challenged with WT GBS had significantly more of the neutrophil chemokine , KC , as well as the proinflammatory cytokine , IL-1β , in brain homogenates than ΔbspC mutant infected animals . ( Fig 3G and 3H ) To further characterize the role of BspC in stimulating immune signaling pathways we infected hCMEC with WT GBS , the ΔbspC mutant , or the complemented strain . After four hours of infection , we collected cells and isolated RNA for RT-qPCR analysis to quantify IL-8 and CXCL-1 transcripts . We focused on the neutrophil chemokines IL-8 and CXCL-1 as these cytokines are highly induced during bacterial meningitis [28] and we observed an increase in neutrophilic infiltrate in brain tissue during the development of GBS meningitis in our mouse model . Cells infected with WT GBS had significant increases of both transcripts compared to cells infected with the ΔbspC mutant . Complementation of the bspC mutation restored the ability of the bacteria to stimulate the expression of IL-8 and CXCL-1 ( Fig 4A and 4B ) . Additionally , treatment of hCMEC with purified BspC protein resulted in increased transcript abundance ( Fig 4C and 4D ) and protein secretion ( Fig 4E and 4F ) for both IL-8 and CXCL-1 compared to untreated cells or treatment with control protein , CshA from Streptococcus gordonii , that was similarly purified from E . coli . Nuclear factor-κB ( NF-κB ) represents a family of inducible transcription factors , which regulates a large array of genes involved in different processes of the immune and inflammatory responses , including IL-8 , CXCL-1 and IL-1 [29] . To assess whether the NF-κB pathway is activated by BspC , we utilized the Hela-57A NF- κB luciferase reporter cell line as described previously [30] . Cells infected with WT GBS had significantly higher luciferase activity than uninfected and ΔbspC mutant GBS infected cells , indicating that BspC contributes to NF- κB activation ( Fig 4G ) . Additionally , immunofluorescent staining of hCMEC revealed an increase in p65 expression , an indicator of NF-κB activation , during infection with WT GBS but not in response to infection with ΔbspC mutant GBS ( Fig 4H–4J ) . We next sought to identify the host protein receptor on brain endothelial cells that interacts with BspC . Membrane proteins of hCMEC were separated by 2-dimensional electrophoresis ( 2-DE ) , then blotted to a PVDF membrane . Following incubation with biotinylated BspC protein , the PVDF membrane was incubated with a streptavidin antibody conjugated to HRP . While many proteins were detected on the Coomassie stained gel , biotinylated BspC protein specifically interacted predominately with one spot in the PVDF membrane with molecular mass around 50–55 kDa and isoelectric point ( pI ) around 5 ( Fig 5A and 5B ) . The corresponding spot from the Coomassie-stained 2-DE gel was excised and digested with trypsin ( Fig 5C ) . Resulting peptides were analyzed by liquid chromatography-tandem mass spectrometry . The spectra from the spot yielded 158 peptide sequences which matched to human vimentin . The molecular weight , 53 . 6 kDa , and calculated pI , 5 . 12 , of vimentin match the values for the spot on the 2-DE gels . This procedure was repeated for membrane proteins from another human brain endothelial cell line ( hBMEC ) that has been used previously to study GBS interactions [31] . Mass spectrometry analysis also determined that BspC interacted with human vimentin ( S3A–S3C ) . The control far Western blot with the streptavidin antibody conjugated to HRP did not show any hybridization ( S3D Fig ) . To confirm these protein-protein interactions in vivo , we employed a bacterial two-hybrid system ( BACTH , "Bacterial Adenylate Cyclase-Based Two-Hybrid" ) [32] . This system is based on the interaction-mediated reconstitution of a cyclic adenosine monophosphate ( cAMP ) signaling cascade in Escherichia coli , and has been used successfully to detect and analyze the interactions between a number of different proteins from both prokaryotes and eukaryotes [33] . Using a commercially available kit ( Euromedex ) according to manufacturer’s directions and as described previously [34] , vimentin was cloned and fused to the T25 fragment as a N-terminal fusion ( T25-Vimentin ) , using the pKT25 plasmid , and bspC was cloned as a C-terminal fusion ( BspC-T18 ) using the pUT18 plasmid . To test for interaction , these plasmids were transformed into an E . coli strain lacking adenylate cyclase ( cyaA ) . We observed blue colonies when grown on LB agar plates containing X-gal , indicating β-galactosidase activity and a positive interaction between Vimentin and BspC compared to the empty vector control ( Fig 5D and 5E ) . A leucine zipper that is fused to the T25 and T18 fragments served as the positive control for the system ( Fig 5F ) . To quantify β-galactosidase activity , cells grown to log phase were permeabilized with 0 . 1% SDS and toluene and enzymatic activity measured by adding ONPG as described previously [34] . The E . coli strain containing both vimentin and BspC expressing plasmids exhibited increased β-galactosidase activity ( Miller units ) compared to the empty vector control strain ( Fig 5G ) . We also quantified the interaction between BspC and vimentin by performing microscale thermophoresis ( MST ) [35] as described in Methods . The dissociation constant ( Kd ) was 3 . 39μM as calculated from the fitted curve that plots normalized fluorescence against concentration of vimentin ( S4E Fig ) . These results demonstrate a direct interaction between BspC and vimentin . To visualize the localization of WT GBS and vimentin in brain endothelial cells we performed imaging flow cytometry of uninfected and WT GBS infected hCMEC . Cells were fixed , permeabilized , and incubated with antibodies to vimentin and GBS . We observed that vimentin protein was present throughout the cytoplasm of uninfected hCMEC ( Fig 6A and 6B ) , but during infection GBS co-localized with vimentin near the surface of infected cells ( Fig 6C and 6D ) . To further characterize the localization of GBS and vimentin , we performed immunofluorescent staining of hCMEC infected with either WT GBS or the ΔbspC mutant . Following infection , cells were fixed but not permeabilized to permit labeling of only extracellular bacteria and surface expressed vimentin . We observed that surface vimentin of hCMEC co-localized with WT GBS bacteria , while this was not seen for hCMEC infected with the ΔbspC mutant ( Fig 6E–6H ) . To quantify co-localization of GBS with vimentin , the number of bacteria that overlapped with the vimentin signal was divided by the total number of bacteria in each field of view ( Fig 6I ) . No staining of either GBS or vimentin was observed in IgG controls ( Fig 6J–6L ) . To first determine if BspC-mediated attachment to cells is dependent on vimentin , we infected HEK293T cells with lentiviruses containing either the vimentin expression plasmid pLenti-VIM or the vector control pLenti-mock . Immunofluorescent staining reveals that HEK293T pLenti-mock cells do not express vimentin while the HEK203T pLenti-VIM clone exhibits strong vimentin labelling ( Fig 7A and 7B ) . WT GBS was significantly more adherent to HEK293T cells that express vimentin while the ΔbspC mutant showed no difference in attachment to either cell line ( Fig 7C ) . Next , we assessed the effect of blocking the vimentin-GBS interaction by treating hCMEC with anti-vimentin antibodies prior to infection with GBS ( Fig 7D ) . Treatment with a vimentin antibody that recognizes the N-terminal epitope ( AA31-80 ) , as well as with IgG isotype controls did not alter adherence of the WT or ΔbspC mutant strains; however , pre-incubation with the mouse V9 antibody [36 , 37] , which reacts with the C-terminal of vimentin ( AA405-466 ) , reduced WT GBS adherence to levels comparable to the adherence of the ΔbspC mutant ( Fig 7E and 7F ) . These results indicate that the interaction between BspC and cell-surface vimentin is dependent on the C-terminus of vimentin . We obtained WT 129 and 129 vimentin KO mice and confirmed the absence of vimentin in the brain endothelium of the KO animals by immunofluorescent staining ( S5A and S5B Fig ) . To determine the necessity of vimentin in GBS meningitis disease progression , we infected WT and vimentin KO mice with WT GBS and observed that they were less susceptible to GBS infection and exhibited increased survival compared to WT animals ( Fig 8A ) . Further , significantly less bacteria were recovered from the tissues of KO mice compared to the tissues of WT mice ( Fig 8B ) . WT and vimentin KO mice infected with ΔbspC mutant GBS showed no difference in survival and tissue bacterial counts ( S6 Fig ) . Additionally , for animals infected with WT GBS , we detected significantly less KC and IL-1β in brain tissues of vimentin KO compared to WT mice , suggesting that vimentin contributes to the initiation of immune signaling pathways during GBS infection ( Fig 8C and 8D ) . Taken together these results indicate the importance of vimentin in GBS dissemination into the brain and meningitis disease progression .
Our studies reveal a unique requirement for the Group B streptococcal antigen I/II protein , BspC , to brain penetration by GBS , the leading agent of neonatal bacterial meningitis . A decreased ability by the GBS ΔbspC mutant to attach to brain endothelium and induce neutrophil chemoattractants in vitro was correlated with a reduced risk for development of meningitis and markedly diminished lethality in vivo . We identified that BspC interacts directly with host vimentin and that blocking this interaction abrogated BspC-mediated attachment to hCMEC . Further , vimentin deficient mice infected with GBS exhibited decreased mortality , bacterial brain loads , and cytokine production in brain tissue . These results corroborate the growing evidence that this intermediate filament protein plays important roles in the pathogenesis of bacterial infections [38] , and provide new evidence for the pivotal role of the BspC adhesin in GBS CNS disease ( Fig 9 ) . The oral streptococcal AgI/II adhesins range in composition from 1310–1653 amino acid ( AA ) residues , while GBS AgI/II proteins are smaller ( 826–932 AA residues ) [39] . The primary sequences of AgI/II proteins are comprised of six distinct regions ( Fig 1B ) , several of which have been shown to mediate the interaction to various host substrates . The S . mutans protein SpaP as well as the S . gordonii proteins SspA and SspB have been demonstrated to interact specifically with the innate immunity scavenger protein gp-340 . [40] Recently , the GAS AgI/II protein AspA , as well as BspA , the AgI/II homolog expressed mainly by the GBS strain NEM316 , have also been shown to bind to immobilized gp-340 [15 , 18] . Gp-340 proteins are involved in various host innate defenses and are present in mucosal secretions , including saliva in the oral cavity and bronchial alveolar fluid in the lung . They can form complexes with other mucosal components such as mucins and function to trap microbes for clearance . However , when gp-340 is immobilized , it can be used by bacteria as a receptor for adherence to the host surface . [15 , 41–44] . There is evidence that the Variable ( V ) regions of SspB , SpaP , AspA and BspA facilitate gp340-binding activity [15 , 45–47] . AgI/II family adhesins have also been shown to interact with other host factors including fibronectin , collagen , and β1 integrins to promote host colonization [14 , 48–50] , demonstrating the multifactorial nature of these adhesins . It is unknown if GBS BspC interactions with other host factors are similar to those of the AgI/II proteins from other streptococci , particularly since the respective V-domains of these homologs are distant enough to suggest different binding partners . Previous work by Chuzeville et al . suggests that the integrative and conjugative element which contains the bspC gene can contribute to bacterial adherence to fibrinogen [19] . Our MST experiments reveal the Kd for the interaction between BspC and vimentin to be 3 . 39 μM . This binding affinity is very similar to that observed for other multifunctional bacterial adhesins and their various host ligands . For example , the Kd for the interaction between fibronectin-binding protein B of Staphylococcus aureus and fibrinogen , elastin , and fibronectin has been demonstrated to be 2 μM , 3 . 2 μM , and 2 . 5 μM , respectively [51] . Whether BspC can promote adherence to other host factors requires further investigation as these interactions may be critical to GBS colonization of mucosal surfaces such as the gut and the vaginal tract . Here we show that GBS BspC interacts with host vimentin , an important cytoskeletal protein belonging to class III intermediate filaments . Vimentin is located in the cytoplasm and functions as an intracellular scaffolding protein that maintains structural and mechanical cell integrity [52] . However , vimentin is also found on the surface of numerous cells such as T cells , platelets , neutrophils , activated macrophages , vascular endothelial cells , skeletal muscle cells , and brain microvascular endothelial cells [53–60] . Vimentin also mediates a variety of cellular processes including cell adhesion , immune signaling , and autophagy [55 , 61 , 62] . Further , the role of cell surface vimentin as an attachment receptor facilitating bacterial or viral entry has been previously documented for other pathogens [38 , 63–65] . The BspC domain that mediates the vimentin interaction is currently under investigation . As the V domain is likely projected from the cell surface and has been implicated in host interactions for other streptococci , we hypothesize that this may be a critical domain for this interaction . Additionally , as the V-domain of other Bsp homologs share 96–100% identity with the V-domain of BspC , we predict that the other Bsp proteins might also interact with vimentin , but this would be a topic for future investigation . There is a growing body of evidence that various bacteria can interact with vimentin to promote their pathogenesis , including Escherichia coli K1 , Salmonella enterica , Streptococcus pyogenes , and Listeria monocytogenes . Thus , vimentin has been shown to be important in experimental models of infection at body sites other than the brain [38 , 57 , 60 , 66 , 67] . Interestingly , previous studies on the meningeal pathogen E . coli K1 have demonstrated that the bacterial surface factor , IbeA , interacts with vimentin to promote bacterial uptake into brain endothelial cells [60 , 68] . Similarly , while our study was underway , it was reported that another bacterium capable of causing meningitis , L . monocytogenes , uses InlF to interact with vimentin to promote brain invasion [67] . Along with our results presented here , this may suggest a common mechanism for meningeal bacterial pathogens to penetrate the BBB and cause CNS disease . However , our analysis of these three bacteria proteins showed no homology or predicted regions that might commonly interact with vimentin . Furthermore , the interaction between the E . coli receptor IbeA and the L . monocytogenes receptor InlF with cell-surface vimentin can be blocked by an antibody to the N-terminal region of vimentin [60 , 67] , while we demonstrate that the interaction between BspC and cell-surface vimentin can be blocked with an antibody to the C-terminal of vimentin . The implications of this unique interaction between a bacterial receptor and the C-terminal of vimentin remain to be explored . Neuronal injury during bacterial meningitis involves both microbial and host factors , and subsequent to attachment to the brain endothelium and penetration of the BBB , GBS stimulation of host immune pathways is the next important step in the progression of meningitis . The release of inflammatory factors by brain endothelial cells , microglia , astrocytes , and infiltrating immune cells can exacerbate neuronal injury [9] . Our data suggest that , like other streptococcal AgI/II family polypeptides , BspC plays a role in immune stimulation . AgI/II family proteins contain two antigenic regions ( the antigens I/II and II ) [69] and this ability to elicit an inflammatory response makes SpaP , the S . mutans AgI/II protein , an attractive candidate for vaccine development to prevent dental caries [14 , 70] . In this study we found that BspC can stimulate NF-κB activation and the release of the proinflammatory cytokines IL-8 and CXCL-1 from hCMEC . Both of these chemokines are major neutrophil recruiting chemoattractants and are the most highly induced during GBS infection [27 , 71] . We observed that mice infected with GBS mutants that lack BspC exhibited lower brain bacterial loads and less meningeal inflammation compared to animals challenged with WT GBS . Interestingly , WT and ΔbspC mutant bacterial loads were similar in the blood , indicating that BspC may not influence GBS survival and proliferation in the blood; however , further investigation is warranted . This study demonstrates for the first time the importance of a streptococcal AgI/II protein , BspC , in the progression of bacterial meningitis . Our data demonstrate that BspC , likely in concert with other GBS surface determinants mentioned above ( pili , Srr1/2 , SfbA ) , contributes to the critical first step of GBS attachment to brain endothelium . As the other described GBS surface factors have been shown to interact with ECM components , BspC may mediate a more direct interaction with the host cell as it facilitates interaction with vimentin . We have observed a unique requirement for vimentin to the pathogenesis of CNS disease; vimentin KO mice were markedly less susceptible to GBS infection and exhibited reduced bacterial tissue load and inflammatory signaling . Vimentin is also known to act as a scaffold for important signaling molecules and mediates the activation of a variety of signaling pathways including NOD2 ( nucleotide-binding oligomerization domain-containing protein 2 ) and NLRP3 ( nucleotide-binding domain , leucine-rich-containing family pyrin domain-containing-3 ) that recognize bacterial peptidoglycan and activate inflammatory response via NF-κB signaling [68 , 72 , 73] . Thus , continued investigation into the mechanisms of how BspC-vimentin interactions dually promote bacterial attachment and immune responses , as well as how BspC expression may be regulated and whether known GBS two-component systems are involved , is warranted . These studies will provide important information that may inform future therapeutic strategies to limit GBS disease progression .
Animal experiments were approved by the committee on the use and care of animals at San Diego State University ( SDSU ) protocol #16-10-021D and at University of Colorado School of Medicine protocol #00316 and performed using accepted veterinary standards . San Diego State University and the University of Colorado School of Medicine are AAALAC accredited; and the facilities meet and adhere to the standards in the “Guide for the Care and Use of Laboratory Animals . ” GBS clinical isolate COH1 ( serotype III ) [74] , 515 ( serotype Ia ) [20] , the recent meningitis isolate 90356 ( serotype III ) [75] and their isogenic ΔbspC mutants were used for the experiments . GBS strains were grown in THB ( Hardy Diagnostics ) at 37°C , and growth was monitored by measuring the optical density at 600 nm ( OD600 ) . Lactococcus lactis strains were grown in M17 medium ( BD Biosciences ) supplemented with 0 . 5% glucose at 30°C . For antibiotic selection , 2 μg/mL chloramphenicol ( Sigma ) and 5 μg/mL erythromycin ( Sigma ) were incorporated into the growth medium . BspC and CshA recombinant proteins , and the BspC antibody were purified as described previously [15 , 76] . The anti-BspC polyclonal antibody was further adsorbed ( as described in [77] ) against COH1ΔbspC bacteria to remove natural rabbit antibodies that react with bacterial surface antigens . Briefly , anti-BspC antibody was diluted to 2 . 28 mg/mL in PBS and incubated with COH1ΔbspC bacteria overnight at 4°C , with rotation . Bacteria were pelleted by centrifugation and the supernatant was collected and filtered using 0 . 22 μM cellulose acetate SpinX centrifuge tube filters ( Costar ) . A normal rabbit IgG antibody ( Invitrogen ) was adsorbed as described above , and utilized as a negative isotype control . The ΔbspC mutant was generated in COH1 and 90356 by in-frame allelic replacement with a chloramphenicol resistance cassette by homologous recombination using a method previously described [10] . A knockout construct was generated by amplifying up- and down-flanking regions of the bspC gene from COH1 genomic DNA using primer pairs of 5’flank-F ( GCAGACACCGATTGCACAAGC ) /R ( GAAGGCGATCTTGCCCTCAA ) and 3’flank-F ( GTCAGCTATCGGTTTAGCAGG ) /R ( CTATACACGCCTACAGGTGTC ) . The chloramphenicol resistance ( cat ) cassette was amplified with primers Cat-F ( GAGGGCAAGATCGCCTTCATGGAGAAAAAAATCACTGGAT ) and Cat-R ( CTGCTAAACCGATAGCTGACTTACGCCCCGCCCTGCCACT ) . Then the construct of two flanks along with the cat cassette was amplified with a pair of nest primers , Nest-xhoI ( CCFCTCGAGGATGCTCAAGATGCACTCAC ) and Nest-xbaI ( GCTCTAGACGAGCCAAATTACCCCTCCT ) , which was then cloned into the pHY304 vector [78] and propagated in E . coli strain DH5α [79] prior to isolation and transformation to COH1 and 90356 GBS . A ΔbspC mutant had been generated previously in 515 [20] . The complemented strain of ΔbspC mutant in COH1 was generated by cloning bspC into pDCerm , an E . coli-GBS shuttle expression vector . Gene bspC was amplified from GBS 515 genomic DNA using primers pDC . bspC . F ( TGGGTACCAGGAGAAAATATGTATAAAAATCAAAC ) and pDC . bspC . R ( CCGGGAGCTCGCAGGTCCAGCTTCAAATC ) , designed to encode a KpnI and SacI restriction site at its termini respectively . This bspC amplicon was then cloned into pDCerm and propagated in E . coli strain Stellar ( ClonTech ) , prior to isolation and transformation into COH1 GBS . A L . lactis strain expressing BspC had been generated previously [20] . GBS strains were grown to an OD600 of 0 . 4 , harvested by centrifugation , and resuspended in PBS . A total of 1 x 108 CFU was added to fresh sheep blood ( VWR ) in V-bottom 96-well plates ( Corning ) . The plates were sealed and incubated at 37°C with agitation for 1 h . The plates were centrifuged at 200 x g for 10 min , and 100 μl of the supernatant was transferred to a flat-bottom 96-well plate . The absorbance at 541nm ( A541 ) was read , and percent hemolysis was calculated by comparing the A541 values for GBS-treated wells to the A541 values for the wells with blood incubated with water . Flow cytometry to determine BspC and capsule expression was performed as described in [80] . Briefly , bacterial stocks were washed in sterile PBS containing 0 . 5% bovine serum albumin ( BSA ) ( VWR ) then incubated with a purified monoclonal anti-serotype III antibody or a purified monoclonal anti-serotype Ia isotype control at a 1:10 , 000 dilution , washed via centrifugation , and labeled with a donkey anti-mouse IgM conjugated to AlexaFluor647 ( Invitrogen ) at a 1:2 , 000 dilution . All incubations were performed at 4°C with shaking . Samples were washed again then resuspended and read on a FACScalibur flow cytometer ( BD Biosciences ) , and analyzed using FlowJo ( v10 ) software . The monoclonal antibodies were provided by John Kearney at the University of Alabama at Birmingham . To stain for surface BspC expression , GBS were grown to OD600 of 0 . 25 in EndoGRO-MV culture medium ( Millipore ) in order to mimic host infection conditions , pelleted by centrifugation , resuspended in PBS and frozen L . lactis strain stocks were thawed and washed in buffer . Approximately , 1 x 106 CFU of each strain was incubated with either adsorbed anti-BspC antibody or adsorbed anti-rabbit IgG at a 1:50 dilution at 4°C , overnight , with rotation . The next day , bacteria were washed via centrifugation , and labeled with a donkey anti-rabbit IgG conjugated to AlexaFluor488 ( Invitrogen ) at a 1:2 , 000 dilution for 45 minutes at room temperature with rotation . Samples were washed again then resuspended and read on a FACScalibur flow cytometer ( BD Biosciences ) , and analyzed using FlowJo ( v10 ) software . Bacteria were grown to an OD600 of 0 . 25 in EndoGRO-MV culture medium ( Millipore ) , the bacteria suspension was smeared on charged glass slides ( Fisher ) , and the slides were fixed with 4% paraformaldehyde for 30 min at room temperature . The slides were blocked with 3% BSA for 1 hour , then incubated with rabbit antibodies to BspC or IgG at a 1:50 dilution followed by donkey anti-rabbit conjugated to AlexaFluor488 ( Invitrogen ) . Bacteria were imaged using a BZ-X710 fluorescent microscope ( Keyence ) . Bacteria were grown to log phase and were then fixed for 10 min using a one-step method with 2 . 5% glutaraldehyde , 1% osmium tetraoxide , 0 . 1M sodium cacodylate . Bacteria were collected on 0 . 4 μM polycarbonate filters by passing the solution through a swinnex device outfitted on a 10 mL syringe . The filters were dehydrated through a series of increasing ethanol concentrations and then dried in a Tousimis SAMRI-790 critical point drying machine . The dried filters were mounted on SEM sample stubs with double-sided carbon tape , coated with 6nm platinum using a Quorom Q150ts high-resolution coater and imaged with a FEI FEG450 scanning electron microscope . Cells of the well-characterized human cerebral microvascular endothelial cell line ( hCMEC/D3 ) , referred to here as hCMEC were obtained from Millipore and were maintained in an EndoGRO-MV complete medium kit supplemented with 1 ng/ml fibroblast growth factor-2 ( FGF-2; Millipore ) [81–84] . Hela57A were provided by Marijke Keestra-Gounder at the University of Colorado , Anschutz Medical Campus and cultured in DMEM ( Corning Cellgro ) containing 10% fetal bovine serum ( Atlanta Biologicals ) . HEK293T cells were obtained from Origene and cultured in DMEM containing 10% fetal bovine serum and 2mM L-glutamine ( Thermo Fisher ) . The lentiviral expression plasmid pLenti-C-Myc-DDK harboring the human vimentin gene ( NM_003380 , pLenti-VIM ) was obtained from Origene . To generate lentiviruses , HEK293T cells were transfected with the pLenti-VIM plasmid in combinations with the packaging plasmid psPAX2 and the envelope plasmid pMD2 . G ( Addgene ) using TransIT_293 transfection reagent ( Mirus ) . After an 18 h incubation , the culture supernatant containing lentiviruses was harvested and filtered through a 0 . 45 μm syringe filter to remove cellular debris . The viral titer was 106 to 107 transduction units ( TU ) per mL . 105 fresh HEK293T cells were infected with lentiviruses at a MOI of 5 for 24 h in the presence of 10 μg/mL polybrene ( Sigma ) . The empty lentiviral expression plasmid pLenti-mock was used as a vector control . Assays to determine the total number of cell surface-adherent or intracellular bacteria were performed as describe previously [10] . Briefly , bacteria were grown to mid-log phase to infect cell monolayers ( 1 × 105 CFU , at a multiplicity of infection [MOI] of 1 ) . Total cell-associated GBS and L . lactis were recovered following a 30 min incubation , while intracellular GBS were recovered after 2 h infection and 2 h incubation with 100 μg gentamicin ( Sigma ) and 5 μg penicillin ( Sigma ) to kill all extracellular bacteria . Cells were detached with 0 . 1 ml of 0 . 25% trypsin-EDTA solution and lysed with addition of 0 . 4 ml of 0 . 025% Triton X-100 by vigorous pipetting . The lysates were then serially diluted and plated on THB agar to enumerate bacterial CFU . For antibody pre-treatment assays , hCMEC were incubated with 0 . 3 μg/ml antibodies for 30 min prior to infection with GBS . The mouse monoclonal antibody to vimentin , clone V9 ( Abcam ) , the rabbit polyclonal antibody to N-terminal vimentin ( Sigma ) , and the isotype controls ( VWR ) were used . Total cell-associated GBS were recovered following a 1h incubation . For luciferase assays , Hela57A cells were infected with 1 x 106 CFU ( MOI , 10 ) GBS for 90 min . Cells were then lysed and luciferase activity quantified using a luciferase assay system ( Promega ) according to manufacturer’s instructions . We utilized a mouse GBS infection model as described previously [10 , 26 , 27] . Briefly , 8-week old male CD-1 mice ( Charles River ) , 129S WT , or 129S-Vimtm1Cba/MesDmarkJ ( Vimentin KO ) ( Jackson Laboratory ) were injected intravenously with 1 × 109 CFU of wild-type GBS or the isogenic ΔbspC mutant for a high dose challenge , or 1 × 108 CFU for a low dose challenge . At the experimental endpoint mice were euthanized and blood , lung , and brain tissue were collected . The tissue was homogenized , and the brain homogenates and lung homogenates as well as blood were plated on THB agar for enumeration of bacterial CFU . Mouse brain tissue was frozen in OCT compound ( Sakura ) and sectioned using a CM1950 cryostat ( Leica ) . Sections were stained using hematoxylin and eosin ( Sigma ) and images were taken using a BZ-X710 microscope ( Keyence ) . At 48 h post-infection with 1 × 108 CFU of GBS , mice were euthanized then perfused to replace blood with PBS . The entire mouse brain was harvested from each animal and the tissue was processed with the Multi-Tissue Dissociation kit #1 following the Adult brain dissociation protocol ( Miltenyi Biotec ) . Cells were resuspended in MACS buffer ( Miltenyi Biotec ) and incubated with antibodies to Ly6C conjugated to BV421 , CD45 conjugated to PE , CD11b conjugated to FITC , and Ly6G conjugated to APC ( Invitrogen ) at 1:200 dilution , UltraLeaf anti-mouse CD16/CD32 Fc block ( Biolegend ) at 1:400 dilution , and fixable viability dye conjugated to eFLuor506 ( eBioscience ) at 1:1000 dilution for 1 h , then fixed ( eBioscience ) . Cells were counted using a Countess automated cell counter ( Invitrogen ) , read on a Fortessa X-20 flow cytometer ( BD Biosciences ) , and analyzed using FlowJo ( v10 ) software . Gates were drawn according to fluorescence minus one ( FMO ) controls . GBS were grown to mid-log phase and 1 × 106 CFU ( MOI , 10 ) were added to hCMEC monolayers and incubated at 37°C with 5% CO2 for 4 h . Cell supernatants were collected , the cells were then lysed , total RNA was extracted ( Machery-Nagel ) , and cDNA was synthesized ( Quanta Biosciences ) according to the manufacturers’ instructions . Primers and primer efficiencies for IL-8 , CXCL-1 , and GAPDH ( glyceraldehyde-3-phosphate dehydrogenase ) were utilized as previously described [85] . IL-8 and CXCL-1 from hCMEC supernatants , and KC and IL-1β from mouse brain homogenates were detected by enzyme-linked immunosorbent assay according to the manufacturer’s instructions ( R&D systems ) . hCMEC were grown to confluency on collagenized coverslips ( Fisher ) . Following a 1 h infection , cells were washed with PBS to remove non-adherent bacteria and fixed with 4% paraformaldehyde ( Sigma ) for 30 min . For Fig 4 , cells were incubated with 1% BSA in PBS with 0 . 01% Tween-20 ( Research Products International ) to block non-specific binding for 15 min , then incubated with a rabbit antibody to p65 ( Sigma ) at a 1:200 dilution overnight at 4°C . Coverslips were then washed with PBS and incubated with donkey anti-rabbit conjugated to Cy3 ( Jackson Immunoresearch ) at a 1:500 dilution for 1 h at room temperature . For Fig 6 , cells were incubated with 1% BSA in PBS for 15 min , then with antibodies to vimentin ( Abcam ) and GBS ( Genetex ) at a 1:200 dilution overnight at 4°C . Following washes with PBS and an incubation with donkey anti-mouse conjugated to Cy3 and donkey anti-rabbit conjugated to 488 secondary antibodies ( ThermoFisher ) at a 1:500 dilution for 1 h at room temperature , coverslips were washed with PBS and mounted onto glass microscopy slides ( Fisher ) with VECTASHIELD mounting medium containing DAPI ( Vector Labs ) . Cells were imaged using a BZ-X710 fluorescent microscope ( Keyence ) . Quantification of GBS and vimentin co-localization was performed by counting the number of GBS that co-localized with vimentin and dividing by the total number of GBS in each field . For Fig 7 , HEK293T cells were incubated with the antibody to vimentin followed by a FITC-conjugated secondary antibody . Cells were imaged using a Cytation 5 fluorescent microplate reader ( BioTek ) . Membrane proteins of hCMEC cells were enriched using a FOCUS membrane protein kit ( G Biosciences , St . Louis , MO ) , dissolved in rehydration buffer ( 7M urea , 2M thiolurea , 1% TBP , and 0 . 2% ampholytes 3–10 NL ) , and quantified using 2D Quant kit ( GE Healthcare , Piscataway , NJ ) . Proteins ( 100μg ) were loaded on 7-cm long immobilized pH gradient ( IPG ) strips with non-linear ( NL ) 3–10 pH gradient ( GE Healthcare ) . Isoelectric focusing was carried out in Multiphor II electrophoresis system ( GE Healthcare ) in three running phases ( phase 1: 250V/0 . 01h , phase 2: 3500V/1 . 5h , and phase 3: 3500V/ 4 . 5h ) . The second dimension SDS-PAGE was carried out using 12 . 5% acrylamide gels in duplicate . One gel was stained with Coomassie Blue G250 ( Bio-Rad , Hercules , CA ) for mass spectrometry analysis . The other gel was transferred to a PVDF membrane for far Western blot analysis . The PVDF membrane was denaturated and renaturated as described in [86] , followed by incubation in a blocking solution ( 5% skim milk in PBS ) for 1 h . Recombinant BspC was biotinylated using a EZ-Link Sulfo-NHS-Biotin kit ( ThermoFisher Scientific , Waltham , MA ) . The PVDF membrane was probed with the biotinylated BspC ( 100μg ) in a blocking solution overnight at 4°C . After washing three times with a washing buffer ( PBS , 0 . 05% Tween-20 ) , the PVDF membrane was incubated with an antibody conjugated to streptavidin-horse radish peroxidase ( HRP ) . Interacting proteins were detected by adding enhanced chemiluminescence ( ECL ) reagents ( ThermoFisher Scientific ) and visualized by x-ray film exposure . The protein spots from far Western blot were aligned to the corresponding protein spots in the Coomassie stained gel . The identified spots were excised and digested in gel with trypsin ( Worthington , Lakewood , NJ ) . Peptide mass spectra were collected on MALDI-TOF/TOF , ( ABI 4700 , AB Systems , Foster City , CA ) and protein identification was performed using the automated result dependent analysis ( RDA ) of ABI GPS Explorer softwareV3 . 5 . Spectra were analyzed by the Mascot search engine using the Swiss protein database . A bacterial adenylate cyclase two-hybrid assay was performed as in [32] and following manufacturer’s instructions ( Euromedex ) . Briefly , plasmids containing T25-Vimentin and BspC-T18 were transformed into E . coli lacking cyaA and E . coli were plated on LB plates containing X-gal ( Sigma ) . To measure β -galactosidase activity , Miller assays were performed according to standard protocols [87] . Briefly , E . coli were grown in 0 . 5mM IPTG ( Sigma ) , then permeabilized with 0 . 1% SDS ( Sigma ) and toluene ( Sigma ) . ONPG ( Research Products International ) was added and absorbance was measured at 600 , 550 , and 420nm . Three independent MST experiments were performed with His-tagged BspC labelled using the Monolith His-Tag Labeling Kit RED-tris-NTA 2nd Generation ( NanoTemper Technologies ) according to manufacturer’s instructions . The concentration of labelled BspC was kept constant at 10nM . Vimentin was purchased from Novus Biologicals and titrated in 1:1 dilutions to obtain a series of 16 titrations ranging in concentration from 20 μM to 0 μM . Measurements were performed in standard capillaries with a Monolith NT . 115 Pico system at 20% excitation power and 40% MST power ( NanoTemper Technologies ) . Following a 1 h infection with GBS , hCMEC were washed with PBS to remove non-adherent GBS . Cells were collected using a cell scraper ( VWR ) and resuspended in PBS containing 10% FBS and 1% sodium azide ( Sigma ) . Cells were incubated with primary antibodies to vimentin ( Abcam ) and GBS ( Genetex ) at 1:500 dilution for 1 h at 4°C followed by donkey anti-mouse conjugated to Cy3 and donkey anti-rabbit conjugated to 488 ( ThermoFisher ) secondary antibodies . Cells were then fixed ( eBioscience ) and analyzed using an ImageStream X imaging flow cytometer ( Amnis ) . GraphPad Prism version 7 . 0 was used for statistical analysis and statistical significance was accepted at P values of <0 . 05 . ( * , P < 0 . 05; ** , P < 0 . 005; *** , P < 0 . 0005; **** , P < 0 . 00005 ) . Specific tests are indicated in figure legends .
|
Group B Streptococcus ( GBS ) typically colonizes healthy adults but can cause severe disease in immune-compromised individuals , including newborns . Despite wide-spread intrapartum antibiotic prophylaxis given to pregnant women , GBS remains a leading cause of neonatal meningitis . To cause meningitis , GBS must interact with and penetrate the blood-brain barrier ( BBB ) , which separates bacteria and immune cells in the blood from the brain . In order to develop targeted therapies to treat GBS meningitis , it is important to understand the mechanisms of BBB crossing . Here , we describe the role of the GBS surface factor , BspC , in promoting meningitis and discover the host ligand for BspC , vimentin , which is an intermediate filament protein that is constitutively expressed by endothelial cells . We determined that BspC interacts with the C-terminal domain of cell-surface vimentin to promote bacterial attachment to brain endothelial cells and that purified BspC protein can induce immune signaling pathways . In a mouse model of hematogenous meningitis , we observed that a GBS mutant lacking BspC was less virulent compared to WT GBS and resulted in less inflammatory disease . We also observed that mice lacking vimentin were protected from GBS infection . These results reveal the importance of the BspC-vimentin interaction in the progression of GBS meningitis disease .
|
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] |
2019
|
The Group B Streptococcal surface antigen I/II protein, BspC, interacts with host vimentin to promote adherence to brain endothelium and inflammation during the pathogenesis of meningitis
|
For genome-wide association studies in family-based designs , we propose a powerful two-stage testing strategy that can be applied in situations in which parent-offspring trio data are available and all offspring are affected with the trait or disease under study . In the first step of the testing strategy , we construct estimators of genetic effect size in the completely ascertained sample of affected offspring and their parents that are statistically independent of the family-based association/transmission disequilibrium tests ( FBATs/TDTs ) that are calculated in the second step of the testing strategy . For each marker , the genetic effect is estimated ( without requiring an estimate of the SNP allele frequency ) and the conditional power of the corresponding FBAT/TDT is computed . Based on the power estimates , a weighted Bonferroni procedure assigns an individually adjusted significance level to each SNP . In the second stage , the SNPs are tested with the FBAT/TDT statistic at the individually adjusted significance levels . Using simulation studies for scenarios with up to 1 , 000 , 000 SNPs , varying allele frequencies and genetic effect sizes , the power of the strategy is compared with standard methodology ( e . g . , FBATs/TDTs with Bonferroni correction ) . In all considered situations , the proposed testing strategy demonstrates substantial power increases over the standard approach , even when the true genetic model is unknown and must be selected based on the conditional power estimates . The practical relevance of our methodology is illustrated by an application to a genome-wide association study for childhood asthma , in which we detect two markers meeting genome-wide significance that would not have been detected using standard methodology .
Recent advances in mapping array technology and the increasing content from SNP databases [1] , [2] have expanded the capacity for large-scale genotyping . With mapping arrays for more than one million SNPs now available [3] , [4] , [5] , [6] , genome-wide association studies carry the promise of identifying replicable associations between important genetic risk factors and complex diseases . One of the major hurdles that needs to be addressed in order to make genome-wide association studies successful is the multiple comparison problem . Hundreds of thousands of SNPs are genotyped and examined for potential associations with multiple phenotypes , resulting in possibly millions of statistical tests . The small number of SNPs that contain “true” signals must be identified among the thousands of false-positive results . The success of genome-wide association studies will depend upon whether it will be possible to overcome this obstacle and translate the increase in genotype information into the identification of novel disease loci , or whether the increased genetic information will be diluted by the multiple testing problem . A brute-force way to address the multiple comparison problem is to design studies with sample sizes large enough to test all genotyped SNPs with standard association tests and adjust for multiple comparison using the Bonferroni correction [7] . However , while sample sizes of several thousand subjects will certainly be feasible for common phenotypes ( e . g . , BMI , height ) , such a strategy carries the risk that the increase in sample size is accompanied by an increase in study heterogeneity , mitigating the positive effects of a larger sample size . Further , for many diseases , recruiting the theoretically required sample size may not be feasible , prohibited either by the costs for recruitment or phenotype assessment , or by the prevalence of the disease . An alternative approach is to develop novel statistical methodology to address the multiple comparison problem with realistic sample sizes . For the analysis of quantitative traits in family-based designs , Van Steen et al . [8] proposed a new class of two-stage testing strategies that uses the same data set twice , first for genomic screening and then for genetic association testing . The approach proved to be a very powerful way to address the multiple testing problem in genetic association studies [8] , [9] , [10] , [11] . Van Steen type testing strategies take advantage of a unique property of family-based data in that it can be partitioned into two statistically independent components . By exploiting the information about the genetic association that is not used in the second stage when the association tests are computed , the first stage prioritizes “promising” SNPs for the second stage . Van Steen type testing strategies have three key advantages: 1 . ) The method achieves statistical power levels which can be substantially higher than those of standard approaches [8] , [9] , and is thereby able to establish genome-wide significance within one study [8] , [9] , [10] , [11] . 2 . ) The Van Steen algorithm maintains the separation between the multiple testing problem and the replication process . Replication attempts in different studies are reserved for the generalization of the established associations and assessment of heterogeneity between study populations . 3 . ) Since genome-wide significance is established in the first data set , the number of SNPs that are pushed forward for replication testing in other populations is generally very small and does not require a large budget , which makes simultaneous replication attempts in multiple samples feasible . Although the approach has recently been significantly improved and now allows family studies to achieve power levels that are comparable to population-based studies with the same number of probands [9] , its applicability is limited . While extensions of the testing strategy are available for arbitrary family structures and for case/control designs [10] , [11] , the approach cannot be applied in situations in which there is no phenotypic variation in the phenotypes of the probands , i . e . , all probands are affected with the disease or trait of interest . This prevents the utilization of the approach in trio designs ( i . e . , affected probands and their parents ) . Since this original trio/TDT design is frequently used , this limitation of the testing strategy poses a major disadvantage for family-based designs . In this manuscript , we propose an extension of Van Steen type testing strategies to family-based designs in which all probands are affected . The strategy also uses the same data set for both stages , which we will refer to as the rank-weighting step and the testing step . In the first stage of the testing strategy , the genetic relative risk effect sizes are estimated for each SNP . We show that it is possible to derive four estimating equations that depend only on the observed parental mating types , but not on any unknown parameters . The estimating equations can be solved analytically , allowing for the construction of effect size estimators that do not depend on the marker allele frequency or offspring genotypes . This is in contrast to effect size estimators/association test statistics for study designs with only affected subjects in population-based studies [12] , [13] , [14] , where the allele frequency must be specified . Based on the genetic effect size estimates obtained from the estimating equations , we compute the conditional power of the FBAT/TDT for all SNPs . The relative rank of the SNPs by conditional power is then used in a weighted Bonferroni approach [9] to assign each SNP an individually adjusted significance level . The weights are constructed so that the overall type-1 error is maintained . In the second step of the testing strategy , the FBAT/TDT statistic is computed for each SNP and genome-wide significance is established based on its individually adjusted significance level . Using extensive simulation studies , the statistical power of the testing strategy is assessed for over a range of genetic effect sizes , different numbers of trios , when the mode of inheritance is known and unknown , and in the absence and presence of linkage disequilibrium ( LD ) . The practical relevance of the approach is illustrated by an application to a genome-wide association study of childhood asthma .
Van Steen testing strategies for genome-wide association studies partition the data set into two statistically independent , but overlapping parts [8] , [9] , [10] , [11] , [15] , [16] . In family-based designs , the first component contains information about the SNP-trait association at a population level , which is assessed based on the proband's phenotype , Y , and the parental genotypes , P1 , P2 [15] , [17] . In our application , we use the offspring phenotype and parental genotypes to construct effect size estimates of the genetic relative risk . The second component of the data characterizes the SNP-trait association at the family level , i . e . , the allele transmissions from the parents to their offspring [18] , [19] , [20] . Family-based association tests such as the TDT or FBAT are therefore conditional tests that treat the offspring genotype , X , as random , conditioning upon the offspring phenotype , Y , and the parental genotypes P1 , P2 . The evidence for SNP-trait association is evaluated by comparing the observed offspring genotype with the expected offspring genotype , which are computed by conditioning upon the parental genotypes , assuming Mendelian transmissions . Since the offspring genotype is the only random component of the FBAT/TDT statistic , the implication is that other information in the FBAT/TDT statistic ( i . e . , the offspring phenotype and parental genotypes ) may be used to assess the evidence for association without biasing the significance level of the FBAT/TDT statistic . Based on the two information sources about association in family-based designs , the density of the joint distribution for X , Y , and P1 , P2 can then be partitioned into two statistically independent components [21] , ( 1 ) Since the density for the first step of the testing strategy , the rank-weighting step , is given by p ( Y , P1 , P2 ) , and the density of the second step , the FBAT/TDT testing step , is p ( X|P1 , P2 , Y ) , likelihood decomposition ( Equation 1 ) implies that the two steps of the testing strategy are independent . The “evidence of association” ( i . e . , the genetic effect size estimate ) for each marker from the rank-weighting step can be utilized in the second stage without having to adjust the overall significance level for the estimation of the genetic effect size in the first stage . There are various ways in which the information from the rank-weighting step can inform the application of the FBAT/TDT statistic in the second step . The effect size estimate from the screening step can be used to select a small subset of “very promising” markers for FBAT/TDT testing [8] or to assign each marker with an individual significance level that reflects the rank of the marker's effect size estimate relative to the other markers [9] . Another possibility is to have the information from the screening step define the “tuning parameters” of the FBAT statistic [22] , [23] . We assume that trios are given ( i . e . , affected probands and parents ) , and that SNP data are analyzed . If the parental data are missing/unavailable , the parental genotypes can be replaced in all equations below by the sufficient statistic by Rabinowitz & Laird [18] , [19] . The sufficient statistic for each nuclear family is defined by all family configurations that lead to consistent inference about the missing parents , given the observed genotypes . When parental data are given , the parental genotypes represent the sufficient statistic . Like the parental genotypes , the sufficient statistic allows for the computation of the offspring genotype distribution within each family , independent of the unknown allele frequency . For a more detailed discussion , we refer to the original paper [18] . For each marker locus of interest , let xi be the coded genotype of the ith proband , counting the number of minor alleles for the SNP of interest . The variables pi1 and pi2 denote the parental genotypes for both parents at the locus . The phenotype of the ith proband is defined by yi . For trio samples in which all probands are affected , the phenotype is coded as “y = 1” . The FBAT statistic , , [19] , [20] is then given by: ( 2 ) and has a chi-square distribution with one degree of freedom . Assuming an additive coding function for the genotype , this FBAT statistic and the original TDT statistic [20] are equivalent . In order to develop a Van Steen type testing strategy [15] , [16] for the classical TDT design , the conditional power [22] , [24] of the FBAT/TDT statistic , , has to be computed in the first step of the testing strategy . This requires the specification of the conditional marker density under the alternative hypothesis: ( 3 ) where affected probands are coded as “yi = 1” . The parameter fx denotes the penetrance probability ( i . e . , fx = Pr ( yi = 1|x ) ) , and Ψx , the genotype relative risk ( i . e . , Ψx = fx/f0 ) . The probability Pr ( x|pi1 , pi2 ) is defined by Mendelian transmission and can be computed straightforwardly , conditional on parental genotypes , without any additional knowledge/assumptions . The penetrance probabilities are unknown and have to be estimated based on the information that is available in the rank-weighting step , i . e . , the offspring phenotype and the parental genotypes . In the original Van Steen approach [8] , the parental genotypes are used to compute the expected/predicted marker scores of the offspring . By regressing the offspring phenotype on its expected marker score , an estimate for the genetic effect size is obtained that allows us to specify the penetrance probability , Pr ( yi = 1|xi ) [15] , [16] . However , when there is no phenotypic variation in the data ( i . e . , all probands are affected ) , this approach is not applicable and an alternative approach has to be developed . In order to simplify the notation , our derivation will be based on the parameterization of the marker distribution ( Equation 3 ) in terms of the genotype relative risks , Ψx . Due to the lack of variation in the phenotype , the only variation that can be utilized for the estimation of the relative risk probabilities are the parental genotypes . In the trio design , there are six distinct parental mating types: ( p1 = 2 , p2 = 2 ) , ( p1 = 2 , p2 = 1 ) , ( p1 = 2 , p2 = 0 ) , ( p1 = 1 , p2 = 1 ) , ( p1 = 1 , p2 = 0 ) and ( p1 = 0 , p2 = 0 ) , where 0 , 1 , and 2 denote the number of copies of the minor allele for the marker of interest . The frequencies of the parental mating types in the ascertained sample ( yi = 1 ) can be computed using Bayes' rule , ( 4 ) where the parameter , p , denotes the minor allele frequency for the marker in the general population , and again , as above , the probabilities are defined by Mendelian transmissions . The probabilities Pr ( p1 = k , p1 = l ) are the paternal mating type frequencies in the general population , and k and l are given by one of the six distinct mating types defined above . Under the assumption of random mating and Hardy-Weinberg equilibrium at the marker locus in the general population , the probabilities Pr ( p1 = k , p1 = l ) will be defined by the actual mating type and the minor allele frequency , p . Based on these assumptions , the likelihood of the parental mating types in the ascertained sample is given by , where the probability of a mating type is denoted as and the observed number of mating types is . In order to obtain maximum likelihood estimates for the genotype relative risks Ψ1 and Ψ2 , one has to maximize the likelihood function l ( Ψ1 , Ψ2 , p ) over all unknown parameters , i . e . , the genotype relative risks , Ψ1 and Ψ2 , and the minor allele frequency of the marker , p . However , due to the structure of the likelihood function , the Fisher information matrix is ill conditioned [25] and a numerical solution of the likelihood maximization is non-trivial . This is particularly challenging in the context of genome-wide association studies in which the numerical implementation must be fast and reliable . In addition to the technical issues related to the likelihood maximization , the estimation of the allele frequency at the marker locus is also problematic in the presence of population admixture . To avoid issues related to the estimation of the allele frequency , we will construct estimators for the genotype relative risks , Ψ1 and Ψ2 , that are independent of the minor allele frequency , p , and have a closed analytical form , facilitating a numerically fast and robust implementation in genome-wide association studies . We consider the following four possible ratios of parental mating types: ( 5 ) Under the assumption of Hardy-Weinberg equilibrium in the general population , using ( Equation 4 ) , the minor allele frequency , p , drops out of the mating type ratios , and one can show that the ratios R1 , R2 , R3 , and R4 are given by: ( 6 ) It is important to note that the four ratios R1 , R2 , R3 , and R4 do not depend on the unknown minor allele frequency , p , and can be estimated based on the parental genotypes , e . g . , . It is also important to note that , if a likelihood approach for the parental mating types had been implemented , the minor allele frequency , p , would have to be estimated . If a genetic model is specified ( e . g . , under an additive mode of inheritance , Ψ1 = ( 1+Ψ2 ) /2 ) , each equation in ( Equation 6 ) will depend only on one unknown genotype relative risk parameter . Each equation can then be solved for the unknown parameter and four estimates for the genotype relative risk are obtained . Alternatively , an overall effect size estimate can be constructed by averaging over all four estimates for the genetic effect size . The selected estimate for the genotype relative risk can then be used to calculate the marker distribution under the alternative hypothesis ( Equation 3 ) , which is the final component needed in calculating the conditional power of the FBAT/TDT statistic . Using simulation studies , we will assess which of the four ratios ( or the average ) for the proposed testing strategy generally achieves the highest and most stable power estimates . Since the proposed estimators for the genotype relative risk only depend on the parental genotypes , they fulfill the decomposition condition ( Equation 1 ) and can be used in the rank-weighting step of the testing strategy without biasing the significance level of the FBAT/TDT statistic in the second stage . The independence of the mating type ratios from the allele frequency makes the approach particularly attractive in the presence of population admixture . While we have outlined the concept of genotype relative risk estimation in the context of ascertained family samples for the trio designs , the genetic effect size estimators can be constructed in the same way for more complex nuclear family structures . Using the algorithm by Rabinowitz & Laird [18] , all possible parental mating types can be derived for nuclear families with missing parental information and/or multiple offspring . The mating type probabilities can then be computed based on Bayes' rule , as for the trio design ( Equation 4 ) . By examining all possible mating type ratios , the ratios that depend only on the genotype relative risk , but not on the allele frequency , can be identified and used to construct direct estimators of the genetic effect size . While we are not able to provide a general rule of thumb on how to construct mating type ratios that do not depend on the allele frequency other than to evaluate all possible ratios , such ratios appear to exist for most nuclear family-types . Since the identification process of the suitable mating type ratios can be automated by using software packages such as Maple and Mathematica , the proposed concept of genotype relative risk estimation is not specific to the trio design and should be applicable to general nuclear family-types . It is important to note that the proposed genetic effect size estimators are derived under the assumption of Hardy-Weinberg equilibrium at the marker locus in the general population , but not in the ascertained sample . Since it is common practice to filter out SNPs that are strongly out of Hardy-Weinberg equilibrium when the genotype data are cleaned prior to analysis , only SNPs with mild to moderate violations of the Hardy-Weinberg assumption will reach the association analysis step . The effects of SNPs with Hardy-Weinberg violations on the proposed testing strategy are thereby limited . However , the genetic effect size estimation in the first step will be biased for such SNPs . In the presence of SNPs that are out of Hardy-Weinberg equilibrium and that are not associated with affection status , the proposed testing strategy is likely to have reduced power . If the Hardy-Weinberg assumption does not hold at the disease susceptibility locus ( DSL ) , the power of the proposed testing strategy can be either increased or decreased , depending on whether the signal that is caused by the true genetic effect at the DSL locus is amplified by the Hardy-Weinberg violation or not . Further , it is important to note that , while violations of the Hardy-Weinberg assumption will have an effect on the rank-weighting step , the validity of the FBAT/TDT-testing step and , consequently , the validity of the entire approach will not be affected by departures from Hardy-Weinberg . In the first phase of the testing strategy , the genetic effect size estimates for each marker are used to compute the conditional power at each locus , and all markers are ranked by power . A weighted Bonferroni approach [9] is implemented that assigns individual significance levels , denoted as αi , to each marker locus based on its conditional power ranking . Essentially , αi is the type 1 error apportioned to the ith test on the basis of its power ranking relative to all of the other tests . The individual significance levels are selected so that the overall significance level is maintained , e . g . , . Using the FBAT/TDT statistic , each marker is then tested in the second stage at the individual significance level αi , and its association with affection status is declared as genome-wide significant if its FBAT/TDT statistic p-value is less than the individual significance level αi . In order to determine the individual significance levels αi , we must select a weighting scheme to apply to the weighted Bonferroni method [9] . Essentially , the weighted Bonferroni method partitions the SNPs into bins and assigns each bin a weight , where the bin and weight sizes vary depending on the relative power ranking of the SNPs in the bin . Each SNP within a bin is assigned an equal weight , which represents a fraction ( or individual significance level , αi ) of the overall significance level , α . Many different weighting schemes to select bin/weight sizes may be applied , as long as α is maintained . We selected an exponential weighting scheme , which uses weights that decrease exponentially and bin sizes that increase exponentially as the power rankings decrease [9] . To define the exponential weighting scheme , let kj be the size of the jth partition , and let k and r be user-defined partitioning parameters with an integer value . Then the sizes of the subsequent partitions can be defined by k1 = k and kj = k*r ( j−1 ) . The exponential weight , wj , for the jth bin is given by , with . Finally , the individual significance level for the jth partition/bin is . With these parameter specifications , it is straightforward to see that , thus the overall alpha level is maintained . Further discussion of the weighted Bonferroni method and weighting schemes is given in Ionita-Laza et al . [9] . The optimal choices for the initial partition size k and the partitioning parameter r will be determined by simulation studies . Using simulation studies , we compare the proposed testing strategy to the standard approach , FBAT/TDT testing with Bonferroni corrected p-values . Both approaches are contrasted under various scenarios with differing trio sample sizes and minor allele frequencies . We simulate trio data under the assumption that all offspring are affected and the genotypes of both parents are known . The minor allele frequencies are drawn from β distributions that resemble the 550 K Illumina HumanHap array . The data were simulated under two separate scenarios . In the first scenario , independence among all markers ( i . e . , no linkage disequilibrium ( LD ) ) is assumed . In the second scenario , we simulated local LD between the SNPs . In order to obtain realistic local LD patterns , we utilized a 550 K scan in the CAMP study ( see Data Analysis section ) that consists of 400 trios . Based on the observed local LD patterns in CAMP , we simulated the correlated SNPs for the second scenario . Specifically , we applied a ‘moving window’ algorithm , where the observed correlation ( r2 ) between the SNP to be simulated and the SNP immediately preceding the SNP that is simulated ( in terms of physical location ) was used to recapitulate local LD patterns on a genome-wide scale . In each simulation , one locus/SNP is assumed to be the DSL , while the other SNPs that are not in LD with the DSL are considered null loci . For the null loci , under the independence scenario , the parental genotypes are generated by drawing from a Binomial distribution with the selected marker's minor allele frequency . When SNPs are correlated , the moving window approach described above is used to generate parental genotypes . Based on the parental genotypes , the offspring genotype is obtained by simulated Mendelian transmissions from the parents . At the DSL , the configuration of genotypes in the proband and parents is simulated based on their theoretical distribution under the specified alternative hypothesis , as outlined in Knapp [26] and Lange & Laird [22] , [24] . For the considered scenarios , we assessed the performance of the proposed approach when the genetic effect size is estimated either based on one of four mating type ratios ( R1–R4 , Equation 6 ) or by the average of the four estimates . In simulation studies comparing the performance of the estimators ( data not shown ) , we observed that the genotype relative risk estimator based on equation R4 consistently generated the highest power estimates ( for minor allele frequencies ( MAFs ) >0 . 1 ) , and was stable , even with modest effect sizes ( e . g . , OR = 1 . 25 ) and lower allele frequencies ( e . g . , MAF≤0 . 2 ) . Thus , all estimated power levels for the proposed method that are shown here are based on the genotype relative risk estimator for mating type ratio R4 . In the first set of simulations , we assume an additive mode of inheritance at the DSL . The genetic effect size is defined in terms of an odds ratio and ranges between 1 . 25 and 2 . 5 , depending on the number of trios . A disease prevalence ( K ) of 10% is selected throughout the simulations . The trio sample size varies between 500–2000 trios . To accurately depict the degree of LD between markers , 500 , 000 markers are simulated . Under the independence scenario , the power was assessed as the proportion of replicates where the FBAT test statistic p-value was less than the required weighted Bonferroni alpha level , based on its power ranking from the rank-weighting step . Under the LD scenario , the power was computed in two ways . First , we defined a positive result identically to the procedure used for the independence scenario ( i . e . , a significant result for the DSL only ) . Secondly , we more broadly defined a positive result to include a significant finding in the DSL or in any markers in strong LD ( r2>0 . 8 ) and within the same physical region , ( i . e . , within five SNPs ) with the DSL . For the standard Bonferroni correction , power was defined as the proportion of replicates with an FBAT statistic p-value<10−7 ( i . e . , 0 . 05/500 , 000 ) . The results of the first set of simulations are displayed in Table 1 . The number of trios is presented in column 1 and the odds ratio ( OR ) for the DSL is specified in column 2 . The minor allele frequency ( MAF ) of the DSL is displayed in Column 3 . Columns 4 , 6 , and 8 , denoted as “Weighted , ” present the power estimates using the weighted Bonferroni method by Ionita-Laza et al . [9] , with an exponential weighting scheme and partitioning parameters of K = 7 and r = 2 . The choice of K = 7 and r = 2 tended to have the highest power among a range of partitioning ( K = 3–10 , r = 2–5 ) parameters , although decreases in power were minimal within these ranges ( data not shown ) . Columns 5 , 7 , and 9 , denoted as “Standard , ” display the results for the standard approach in which all SNPs are equally weighted when applying the Bonferroni correction , and a significance level of 10−7 , ( i . e . , 0 . 05/500 , 000 ) is required for genome-wide significance . Columns 4–5 ( Independence scenario” ) reflect the scenario in which all markers are independent ( i . e . , adjacent r2 = 0 ) . Columns 6–9 ( “LD scenario” ) display the power estimates when LD is present among markers , where the power represents either detecting the DSL only ( Column 6–7 ) , or the DSL/markers in strong LD with the DSL ( Columns 8–9 ) . The power estimates are based on at least 1 , 000 replicates for each ( DSL ) minor allele frequency and odds ratio . For genome screens of 500 K SNPs , regardless of the sample size or degree of correlation among markers , the use of power-driven weights from the rank-weighting step shows a considerable improvement in power over the standard methodology . For the lowest power estimates ( <40% power for the standard Bonferroni ) , the power estimates for the weighted method are typically at least twofold greater than the standard approach . For low to moderate power estimates , ( 40–70% power for Bonferroni ) , the weighted method outperforms the standard correction by to 15–40% . For SNPs with greater than 70% power with the standard approach , the improvement ranges between 7 and 11% , unless the power estimates are near one . However , even in these scenarios , the power estimates for the weighted Bonferroni method are always higher , though the differences between the two methods are more modest . With respect to trio sample size , we note that even with smaller sample sizes ( e . g . , n = 500 ) , there is still power to detect a DSL ( or SNP in LD with the DSL ) , and the power gains over standard Bonferroni correction are maintained , although a more pronounced effect size is required ( OR = 2 . 25–2 . 5 ) to achieve adequate power . Based on the results of our simulation studies , we would not recommend genome-wide association studies of fewer than 300 trios unless extremely large effect sizes ( OR>3 ) were anticipated . To verify that the proposed testing strategy maintains the overall alpha level , the simulations were repeated under the null hypothesis of no linkage/no association , with a sample size of 500 trios . Based on over 10 , 000 replicates , the observed overall type 1 error rate was maintained at 4 . 66% . Finally , in examining the impact that LD has on power , when considering a positive finding to be the detection of the DSL only , the power of the approach was slightly reduced in comparison to the scenario in which the SNPs were independent . However , the proposed testing strategy still outperforms the standard approach by differences that are of practical relevance . When the definition of a positive finding is extended to those SNPs that are in LD with the DSL , the power estimates are higher than the independence scenario . This is a significant finding , given that some array platforms for genome-wide genotyping do not employ LD-tagging methods , and as chip density increases ( i . e . , one million SNP arrays ) , linkage disequilibrium will have a greater impact on the analysis of genome-wide association studies . Since in practice the underlying mode of inheritance is unknown , we ran a second set of simulations to reflect this reality and assess the impact on the power of the proposed method and the standard approach . In the data analysis step of the following simulation , the true genetic model was considered to be “unknown . ” We simulated three scenarios , where the true ( but unknown ) generating model was either additive , dominant , or recessive , and conducted separate FBAT analyses under all three genetic models . To evaluate the power for the weighted Bonferroni method [9] , we estimated the conditional power for each SNP under all three genetic models . For each SNP , the result for the genetic model with highest power was selected and the lower powered results ( without evaluating the FBAT statistic p-value ) were discarded . This resulted in 500 , 000 SNPs/power estimates across the three genetic models , that were ranked overall by power and evaluated for association using weighted Bonferroni significance levels . The weighted Bonferroni significance levels were computed in the same way as previously described . We then compared the power obtained from the weighted method to standard Bonferroni correction , which computed the FBAT statistic under all three genetic models at each SNP , thus requiring a correction for 1 . 5 million comparisons ( 500 , 000 markers * 3 genetic models ) and an FBAT p-value <3 . 3×10−8 for significance ( i . e . , 0 . 05/1 , 500 , 000 ) . For simplicity , we ran these simulations for 2000 trios . The results of the second set of simulations are displayed in Table 2 . The data are presented in an identical format to the simulations under the additive model ( including partitioning parameters of K = 7 and r = 2 ) , except that column 1 reflects the “true” underlying genetic model rather than the number of trios . For the additive model , in comparison to the simulations where the genetic model is known , the power estimates tend be slightly lower . In the independence scenario , for an odds ratio of 1 . 5 and MAF of 0 . 2 , when the genetic model is known , the weighted Bonferroni method has 91% power versus 85% for the standard , whereas , when the genetic model is unknown , the power estimates are 80% and 57% , respectively . However , our new method seems much more robust to analysis under multiple models in comparison to the standard correction . For an effect size of 1 . 5 , the power loss in the unknown model ranges from 7 to 15% , depending on MAF , while power loss under the standard method ranges from 15 to 63% . Similar observations are made for the power comparisons between the weighted and standard methods for the LD scenarios . The overall power is reduced relative to the situation where the generating genetic model is known , but the difference in power between the weighted and standard methods is more striking . In comparing the independence scenario to the LD scenarios , the patterns observed when the genetic model is known hold here as well: when LD is present and the DSL or SNPs in LD with the DSL are considered , the power is highest , followed by the independence scenario . The lowest overall power is noted when LD is present and only the DSL is examined for significant association . In summary , while the overall power drops , the benefits of our methodology versus the standard are more pronounced when the genetic model is unknown and multiple analyses are conducted . In comparing our method with weighted Bonferroni significance levels to the standard under dominant and recessive models , our procedure consistently demonstrates greater power , regardless of the degree of LD , effect size , or MAF . However , under a recessive model , a MAF of 0 . 3 or greater is required to achieve adequate power for the range of effect sizes that we examined ( OR = 2–2 . 5 ) . Overall , our new methodology has the greatest impact for the low to moderately powered markers . For SNPs with standard Bonferroni power estimates ranging between 40% and 70% , the new method generally boosts power by an absolute difference of 10–15% , potentially providing marginally powered SNPs with a better chance of detection . Our simulation studies illustrate that the application of the proposed testing strategy is not limited by the number of trios analyzed , the degree of correlation among SNPs , the genetic model , or the size of the genetic effect . When standard approaches fail to provide sufficient power , the proposed testing strategy maintains acceptable power levels for small to moderate effect sizes ( n = 2000 ) for the additive generating models , and moderate effect sizes under the dominant or recessive models or designs with fewer trios ( n = 500–1000 ) . As a general rule of thumb , our simulation experiments suggest that the testing strategy achieves optimal power levels for partitioning parameters of K = 7 and r = 2 for 500 , 000 markers , though power estimates were similar for K = 5–10 and r = 2–3 . A comparison of the achieved power levels for differing number of trios and various genetic models illustrates that the impact of the multiple testing problem on a genome-wide association study can be minimized by the use of the proposed testing strategy . Asthma is a complex respiratory disorder , likely due to both genetic and environmental influences that affect the developing respiratory system . Asthma has been shown to have substantial heritability [27] , [28] , [29] and a comprehensive review of the literature in 2003 reported more than 200 studies with an association between asthma and its related phenotypes [30] . Thus , we applied our methodology to a family-based genome-wide association study of asthma . The families were originally recruited through the Childhood Asthma Management Program ( CAMP ) [31] Genetics Ancillary Study . All of the families were ascertained through asthmatic probands between 5 and 12 years old with mild to moderate asthma . All of the probands are affected , making it impossible to apply methodologies that require phenotype variation . SNP genotyping was performed using Illumina HumanHap 550v3 arrays . Of 547 , 645 SNPs , 2 . 5% were removed during data cleaning due to genotype completion rates <95% , parent-offspring Mendelian errors , or because the assay sequence could not be aligned to one genomic locus , which resulted in 534 , 290 autosomal markers for analysis . Genotyping was conducted on 1215 subjects in 422 families . After removing 43 subjects with inadequate data , 1172 subjects comprising 403 families were analyzed . We applied the new power rank-weighting methodology , under an additive genetic model , to all 534 , 290 SNP , using equation R4 ( Equation 6 ) to estimate genetic effect sizes , which had consistently had the highest power in the simulation studies . The power rankings were used to individually weight the family-based association test ( also assuming an additive model ) for each marker , using the method of Ionita-Laza et al . [9] . Table 3 displays the results for the CAMP data analysis . Based on the results of the simulation studies , the partitioning parameters of K = 7 and r = 2 were used . From the analysis , two SNPs were identified as genome-wide significant with a global alpha level of 0 . 05 . These SNP were also the top two by power . Thus , the Top K Method by Van Steen et al . [8] , with a modest choice of ‘Top’ markers selected for analysis , would have also detected these SNPs . However , the weighted Bonferroni method by Ionita-Laza et al . [9] allows for the evaluation of all SNP . Most strikingly , neither of these SNPs would have been detected after standard Bonferroni [7] or FDR-type [32] correction . These significant markers reside on chromosomes 1 ( rs10863712 ) and 14 ( rs1294497 ) . In both markers , the minor allele is over-transmitted to the affected proband . These markers are currently under further study . These results provide proof of concept for our new method in that the top-ranked markers by power also showed evidence of association , strongly suggesting consistency of association in the independent population level and family level components of family-based data .
The testing strategy as well as the corresponding power and sample size calculations has been fully implemented in the software package PBAT , which is freely available at http://www . biostat . harvard . edu/̃clange/default . htm [36] , [37] .
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The current state of genotyping technology has enabled researchers to conduct genome-wide association studies of up to 1 , 000 , 000 SNPs , allowing for systematic scanning of the genome for variants that might influence the development and progression of complex diseases . One of the largest obstacles to the successful detection of such variants is the multiple comparisons/testing problem in the genetic association analysis . For family-based designs in which all offspring are affected with the disease/trait under study , we developed a methodology that addresses this problem by partitioning the family-based data into two statistically independent components . The first component is used to screen the data and determine the most promising SNPs . The second component is used to test the SNPs for association , where information from the screening is used to weight the SNPs during testing . This methodology is more powerful than standard procedures for multiple comparisons adjustment ( i . e . , Bonferroni correction ) . Additionally , as only one data set is required for screening and testing , our testing strategy is less susceptible to study heterogeneity . Finally , as many family-based studies collect data only from affected offspring , this method addresses a major limitation of previous methodologies for multiple comparisons in family-based designs , which require variation in the disease/trait among offspring .
|
[
"Abstract",
"Introduction",
"Methods",
"Discussion"
] |
[
"genetics",
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"genomics/disease",
"models",
"genetics",
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2008
|
Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected
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β-lactam antibiotics interfere with cross-linking of the bacterial cell wall , but the killing mechanism of this important class of antibiotics is not fully understood . Serendipitously we found that sub-lethal doses of β-lactams rescue growth and prevent spontaneous lysis of Staphylococcus aureus mutants lacking the widely conserved chaperone ClpX , and we reasoned that a better understanding of the clpX phenotypes could provide novel insights into the downstream effects of β-lactam binding to the PBP targets . Super-resolution imaging revealed that clpX cells display aberrant septum synthesis , and initiate daughter cell separation prior to septum completion at 30°C , but not at 37°C , demonstrating that ClpX becomes critical for coordinating the S . aureus cell cycle as the temperature decreases . FtsZ localization and dynamics were not affected in the absence of ClpX , suggesting that ClpX affects septum formation and autolytic activation downstream of Z-ring formation . Interestingly , oxacillin antagonized the septum progression defects of clpX cells and prevented lysis of prematurely splitting clpX cells . Strikingly , inhibitors of wall teichoic acid ( WTA ) biosynthesis that work synergistically with β-lactams to kill MRSA synthesis also rescued growth of the clpX mutant , as did genetic inactivation of the gene encoding the septal autolysin , Sle1 . Taken together , our data support a model in which Sle1 causes premature splitting and lysis of clpX daughter cells unless Sle1-dependent lysis is antagonized by β-lactams or by inhibiting an early step in WTA biosynthesis . The finding that β-lactams and inhibitors of WTA biosynthesis specifically prevent lysis of a mutant with dysregulated autolytic activity lends support to the idea that PBPs and WTA biosynthesis play an important role in coordinating cell division with autolytic splitting of daughter cells , and that β-lactams do not kill S . aureus simply by weakening the cell wall .
Staphylococcus aureus is a commensal bacterium capable of causing a variety of both localized and invasive infections . Due to its ability to acquire resistance to all relevant antibiotics S . aureus remains a major clinical challenge worldwide [1] . The most challenging antimicrobial resistance issue in S . aureus has been the dissemination of methicillin-resistant S . aureus ( MRSA ) strains that are resistant to almost all β-lactam antibiotics , one of the safest and most widely used classes of antibiotics ever developed [2] . Early work on the mechanism of action of β-lactams culminated in the discovery that penicillin inhibits crosslinking of peptidoglycan ( PG ) , the central component of bacterial cell walls [3] . The enzymes mediating cross-linking of peptidoglycan strands , the targets of penicillin , were therefore designated penicillin binding proteins ( PBPs ) . The realization that penicillin inhibits PG crosslinking led to the classical model in which penicillin-mediated cell lysis is believed to occur as a consequence of a mechanically weakened cell wall incapable of withstanding high intracellular turgor [3 , 4] . The killing effect of β-lactam antibiotics , however , has turned out to be more complex [5–9] , and may even vary between bacteria , as the organization of PG synthesis and the number of PBPs differ widely between bacterial species [10] . Spherical bacteria such as S . aureus have only one cell wall synthesis machine , and S . aureus encodes only four PBPs [11] . Notably , MRSA and other Staphylococci have obtained resistance to β-lactams by horizontal acquisition of the mecA gene encoding an alternative PBP ( PBP2a ) that is resistant to inhibition by most β-lactams [12 , 13] . PBP2a mediated resistance additionally depends on several intrinsic factors that can be targeted by specific compounds to re-sensitize MRSA to β-lactams [14–16] . As an example , inhibitors of wall teichoic acid ( WTA ) biosynthesis , work synergistically with β-lactams to kill MRSA both in vitro and in in vivo models of infection , thereby opening a novel paradigm for combination treatment of MRSA [16] . Indeed , a combination strategy pairing β-lactamase inhibitors with β-lactams has proven highly successful in restoring β-lactam efficacy against Gram-negative bacteria [17] . In all living cells molecular chaperones are essential for facilitating unfolding and interactions of proteins . The ClpX chaperone is a highly conserved ATP-dependent chaperone that , additionally to functioning as a classical chaperone , can associate with ClpP to form the ClpXP proteolytic complex [18] . S . aureus clpX mutant exhibits a mild growth defect at 37°C that is severely exacerbated at 30°C [19 , 20] . This cold-sensitive growth defect of the clpX mutant is independent of ClpP , and is alleviated by loss-of-function mutations in the ltaS gene [20 , 21] . ltaS encodes the LtaS synthetase that is required for synthesis of lipoteichoic acid ( LTA ) , an essential cell wall polymer of Gram-positive bacteria controlling cell division and autolytic activity [22] . Interestingly , inactivation of ClpX restored the septum placement defects of cells depleted for LTA , suggesting a link between ClpX and cell division in S . aureus [20] . Here we demonstrate that ClpX becomes critical for progression of S . aureus septum synthesis as the temperature decreases . In cells with stalling of septum synthesis , autolytic splitting of daughter cells is activated prior to septum completion resulting in cell lysis , unless β-lactam antibiotics are added to the growth medium . Strikingly , inhibitors of the first step in WTA biosynthesis , similarly to inactivation of the Sle1 autolysin specifically rescues growth of S . aureus clpX mutants , supporting a fundamental connection between the transpeptidase activity of PBPs , teichoic acids biosynthesis and activation of autolysins mediating septal splitting . In conclusion , this study identifies the ClpX chaperone as an important player in S . aureus cell division , and provides novel insight into the link between β-lactam antibiotics and cell division in this important pathogen .
Serendipitously , while determining the susceptibility of the S . aureus clpX mutant to oxacillin , we repeatedly observed zones of improved growth at a certain distance from the filter discs containing the antibiotic , a phenomenon that was not observed for wild-type strains ( marked by arrow in Fig 1A ) . This observation indicated that sub-lethal concentrations of oxacillin stimulate growth of the clpX mutant . Indeed , addition of sub-lethal concentrations of oxacillin rescued the severe growth defect normally seen for S . aureus clpX mutants at 30°C ( Fig 1B ) . To investigate if growth of S . aureus clpX mutants is generally improved by addition of β-lactam antibiotics , three S . aureus strains of clinical origin , representing both MRSA ( JE2 ) and methicillin-sensitive S . aureus ( SA564 and Newman ) , and the corresponding clpX deletion strains were grown in broth containing oxacillin , meropenem or cefuroxime ( representing three different chemical classes of β-lactams ) in various concentrations below and above the previously determined MIC values [23] . We found that the presence of β-lactam antibiotics increased the final yield and growth rate of the clpX mutants in all strain backgrounds ( Figs 1C and 1D and S1 ) . As shown previously [23] , inactivation of clpX increased the MIC values in the JE2 background ( S1 Fig ) , but not in the MSSA strain backgrounds . A wide range of β-lactam concentrations was tested , but we did not identify any concentration at which the growth rates of the wild-type strains were enhanced ( S1 Fig ) . For comparison , we also included clpP mutants , but observed no or only a minor stimulatory effect on the growth rate of the clpP mutants in the presence of β-lactams ( S1 Fig ) . We conclude that the ClpX dependent growth defect that is suppressed by β-lactams is caused by loss of ClpX chaperone activity , not loss of ClpXP protease activity . Given the unusual ability of β-lactams to stimulate growth of the clpX mutant , we reasoned that a better understanding of the clpX growth defect could provide novel insights into how β-lactam antibiotics interfere with growth of S . aureus . We first speculated that β-lactam antibiotics may rescue growth of the clpX mutant by restoring possible abnormalities in the PG composition of the cell wall . To test this hypothesis , peptidoglycan was purified from the cell wall of wild-type and the clpX cells grown at 30°C in the presence or absence of oxacillin , and muropeptides were separated and identified by HPLC . The muropeptide profiles of the wild-type strain and the clpX strain , however , turned out to be almost identical , with oxacillin inducing similar changes in the PG structure in both strains ( S2 Fig ) . We next assessed if PBPs amounts or binding activity was changed in cells lacking ClpX . To this end , Bocillin-FL labeling was used to detect PBPs in membrane fractions from SA564 wild-type and clpX cells grown at 37°C or 30°C ( +/- oxacillin ) . As the PBP4 signal was very weak in the PBP-profiles , the PBP4 levels were additionally determined by Western blot analysis . Interestingly , while no variation in PBP levels was detected between the SA564 wild-type and clpX cells grown at 37°C , the level of PBP2 appeared slightly increased in clpX cells as compared to wild-type cells when strains were grown at 30°C ( S2 Fig ) . The presence of sub-MIC oxacillin did , however , not impact PBP-levels . Therefore , β-lactams neither seem to rescue growth of clpX cells by correcting an abnormal level of cell wall cross linking , nor by adjusting the levels of PBPs . The temperature dependent expression of PBP2 observed in clpX cells , however , indicates that ClpX plays a role in processes related to cell wall synthesis at the lower temperature . To further investigate how β-lactams improve growth of the clpX cells , we studied growth of single cells of the S . aureus SA564 wild type and clpX mutant in the absence or presence of oxacillin at 30°C using automated phase contrast time-lapse microscopy . The time-lapse experiments revealed that in the absence of oxacillin only about half of the imaged clpX cells ( 15 of 33 cells ) were capable of initiating growth and forming micro-colonies that compared to wild-type colonies were of significantly reduced size with an average number of cells of only 47±59 as compared to 1736±384 in wild-type colonies ( P<0 . 0001 ) ( Fig 2A and S1 Movie ) . The remaining 18 clpX cells either did not initiate dividing or stopped dividing early on in the experiment ( S1 Movie; black arrows and in Fig 2A ) . Strikingly , in the clpX micro-colonies a large fraction ( 16 ± 6% ) of cells lysed spontaneously during the course of the experiment ( S1 Movie; white arrows and in Fig 2A ) . The cells in Fig 2 were grown at 30°C for 90 min prior to imaging , however , growth arrest and spontaneous lysis could be observed right after shifting clpX cells from 37°C to 30°C , demonstrating that a down-shift in temperature has an immediate impact on cells devoid of ClpX activity . Interestingly , oxacillin clearly stimulated growth of clpX cells , and when exposed to oxacillin all imaged clpX cells ( 26 of 26 imaged cells ) were capable of initiating growth and ended up forming micro-colonies with significantly higher cell numbers than in the absence of oxacillin ( 351±175 , P<0 . 0001; Fig 2B and S1 Movie ) . In comparisons , the final cell count reached in wild-type micro-colonies was slightly reduced in the presence of oxacillin ( Fig 2 and S1 Movie ) . Remarkably , oxacillin appears to greatly reduce the number of clpX cells undergoing spontaneous lysis ( from 16 ± 6% to 4 ± 2%; P<0 . 0001 ) , and clpX cells exposed to oxacillin at the start of imaging ( T = 0 ) , initiated growth almost as fast as clpX cells that were pre-exposed to oxacillin for 90 min prior to imaging ( T = -90 ) . Hence , oxacillin seems to be capable of stimulating growth of clpX cells almost immediately . This important finding rules out the contribution of genetic suppressors , and indicates that the binding of oxacillin to the trans-peptidase ( TP ) site of PBPs per se may be causing the stimulatory effect . To further investigate the clpX phenotypes , we studied the morphology of wild-type and clpX cells by transmission electron microscopy ( TEM ) and scanning electron microscopy ( SEM ) after growth at 30°C . In general , cells lacking ClpX were smaller than wild-type cells ( V = 0 . 42 ± 0 . 1 μm3 as compared to V = 0 . 7 ± 0 . 1 μm3 , P < 0 . 001 ) and have a thickened cell wall ( Fig 3A ) , consistent with previous results described for clpX cells growing at 37°C [23] . However , clpX cells growing at 30°C displayed a number of distinctive morphological changes that were not observed at 37°C . First , consistent with the spontaneous cell lysis observed in the time-lapse microscopy , approximately 10% of the clpX mutant cells grown at 30°C appeared as lysed ghost cells in the TEM images ( S3 Fig ) . Interestingly , these ghost cells had a characteristic appearance in which the cell wall was ripped apart at the tips of the ingrowing , still incomplete , septa ( see examples in Fig 3C ) , indicating that these cells underwent lysis while in the process of daughter-cell splitting . To divide , S . aureus builds a septal cross wall generating two hemispherical daughter cells connected through a narrow peripheral ring [24 , 25] . Resolution of this peripheral wall ring leads to rapid splitting of daughter cells , in a process designated as “popping” [25] . Popping has been described to take place only in cells with closed septa and , consistent with this notion , the peripheral wall at the site of septum always appeared intact in wild-type cells displaying incomplete septa ( marked with white arrow in Figs 3A and S3 ) , while invaginations/breakage in the peripheral wall at the site of septum were visible only in wild-type displaying a completed septum ( marked with black arrow in Figs 3A and S3 ) . In contrast , a substantial fraction of clpX cells with still incomplete septa displayed invaginations in the peripheral wall at the edge of the septum , or a complete splitting of the ingrowing septum , indicating that they have initiated daughter cell splitting from the cell periphery ( black stars in Figs 3D and 3E and S3 ) . clpX cells in the process of splitting despite displaying a non-closed septal cross-wall ( seen as a hole in Fig 3C , right panel ) , or , while still being connected by an undivided cytoplasm could also be observed in SEM-images ( Fig 3D , right panel ) . Taken together , these findings strongly suggest that in the absence of ClpX , the system controlling the onset of autolytic separation of daughter cells becomes dysregulated , and that premature splitting of clpX cells with incomplete septa results in cell lysis . TEM-images also showed that some clpX cells displaying premature split appeared elongated ( as also observed in the time-lapse experiment , Fig 2A ) , see examples in Fig 3D and 3F , or displayed asymmetrical ingrowth of septa , and in extreme cases extending inwards only from one side ( +/- premature split; Fig 3D and 3E ) . This contrasts with wild-type S . aureus cells whose septa always extended symmetrically inwards from the edge of the cell wall ( Figs 3A and S3 ) . Finally , in some clpX cells , unordered membranous material reminiscent of mesosome-like structures [26] were observed at the site of septum ingrowth ( Fig 3E and 3F ) . The latter phenotypes suggest that ClpX also contributes to coordinating septum formation in S . aureus . To accurately quantify morphological phenotypes and to assess the influence of clpX on S . aureus cell cycle progression , we performed Super-Resolution Structured Illumination Microscopy ( SR-SIM ) on cells stained with the membrane dye Nile red , and scored cells according to the stage of septum ingrowth as described by Monteiro et al . [24]; see Fig 4A for example images . To enumerate cells with incomplete septa that show signs of premature splitting , cells were additionally stained with fluorescently modified vancomycin ( Van-FL ) , which labels the entire cell wall ( cell periphery and septum ) , or with a green fluorescent derivative of wheat germ agglutinin WGA-488 that only labels the peripheral wall [24 , 27] . To estimate the number of lysed cells , DNA was stained with the blue dye Hoechst 3334 . In this analysis , no differences in the distribution of cells in the different phases were observed for wild-type and clpX cells grown at 37°C ( Fig 4A ) . At 30°C , however , significantly fewer clpX cells displayed a complete septum ( phase 3 ) ( 4% as opposed to 15% of wild-type cells; P < 0 . 001 ) . Moreover , while the fraction of cells that were in the process of building a septum ( phase 2 ) was similar in wild-type and clpX cells at both temperatures , a more detailed analysis of the phase 2 cells revealed striking differences ( Fig 4 ) : consistent with the TEM analysis , a substantial number of clpX cells with incomplete septa showed signs of premature daughter cell splitting ( 20% of phase 2 cells ) , or had asymmetrical septum ingrowth ( 7% of phase 2 cells ) , when cells were grown at 30°C . None of these phenotypes were observed in wild-type cells at any temperature . While asymmetrical septum ingrowth was not observed in clpX cells grown at 37°C , premature splitting cells could be observed , however , at a lower frequency ( Fig 4B ) . Furthermore , when subdividing phase 2 cells into two subclasses based on the extent of septum ingrowth , the proportion of clpX cells that just started septum ingrowth ( defined as cells with less than 15% septum ingrowth; see examples in Fig 4B ) was significantly higher ( P < 0 . 001 ) at 30°C compared to 37°C , and when compared to the wild-type . For wild-type cells , an equal fraction of cells displayed early septum ingrowth at 30°C and 37°C . Finally , SR-SIM confirmed that the fraction of lysed clpX cells increased significantly when the temperature was decreased ( 2% at 37°C , and 16% at 30°C , P < 0 . 001 ) . In comparison , the proportion of lysed wild-type cells was estimated to be below 2% at both temperatures . In conclusion , the proportion of clpX mutant cells displaying a complete septum or late septum ingrowth was significantly reduced at 30°C , while the proportion of clpX cells displaying early septum ingrowth and aberrant septum was significantly increased at 30°C . Thus , the microscopy analyses suggest that ClpX chaperone activity becomes critical for the ability of S . aureus to complete the division septum as the temperature decreases . To further examine how β-lactams improve growth of the clpX mutant , we performed SR-SIM analysis on oxacillin treated wild-type and clpX mutant cells grown at 30°C , as described above ( Fig 4 ) . Interestingly , sub-lethal concentrations of oxacillin significantly increased the fraction of phase 3 cells ( closed septum ) : from 15 to 31% in the wild-type ( P < 0 . 001 ) , and from 4 to 14% in the clpX mutant ( P < 0 . 001 ) . Moreover , oxacillin significantly decreased the fraction of clpX cells ( phase 2 ) that had initiated cell separation prior to septum completion from 20% to 2% ( P < 0 . 001 ) , and in line with this observation , almost no lysed clpX mutant cells were observed ( Fig 4B ) . Hence , oxacillin increases the fraction of cells with complete division septa in both the wild-type and the clpX backgrounds , and prevents premature splitting of clpX cells with incomplete division septa . In contrast , asymmetrical ingrowth of septa is still readily observed in oxacillin treated clpX mutant cells ( Fig 4A and 4B ) . These conclusions were supported when the oxacillin treated SA564 wild-type and clpX cells were analyzed by TEM; additionally the TEM images indicated that oxacillin prevents formation of mesosome-like structures in clpX cells ( S4 Fig ) . Oxacillin treatment , however , conferred a number of well described morphological changes that were shared by wild-type and clpX cells including blurring of the electron-dense septal mid-zone , a more fuzzy surface , and thickening of septa . Finally , many daughter cells that have initiated inward splitting from the cell periphery remain incompletely separated at mid-cell ( S4 Fig ) [7 , 27 , 28] . Hence , both the SR-SIM and the TEM images support that oxacillin , even in concentrations well below the MIC value , prolongs phase 3 and delays splitting of the septum in both wt and clpX cells . To directly assess the impact of ClpX and oxacillin on progression of septal PG synthesis , we used fluorescent D-amino acids ( FDAAs ) to visualize regions of new PG insertion [24 , 29 , 30] . PG synthesis was followed at 30°C and 37°C by sequentially labeling cells with FDAAs of different colors , thereby creating a virtual time-lapse image of PG synthesis [24 , 29 , 30] . Cells were first pulse-labeled for 10 min with green nitrobenzofurazan-amino-D-alanine ( NADA ) , followed by a 10-min pulse with the blue hydroxycoumarin-amino-D-alanine ( HADA ) . Labeled cells were imaged by SR-SIM , and progression of PG synthesis was scored in 300 randomly picked wild-type and clpX mutant cells grown in the absence or presence of oxacillin ( Fig 5; in order to improve the contrast NADA is displayed in magenta , while HADA is displayed in cyan ) . In the absence of oxacillin , PG synthesis proceeded from phase 1 ( no septa , PG synthesis takes place in the lateral wall ) to phase 2 ( septal PG synthesis progresses inwards ) , and finally phase 3 ( closed septum , PG synthesis occurs in both septum and the lateral wall ) in > 95% of wild-type cells , as described in [24 , 25] ( see Fig 5A ) . When the clpX mutant was grown at 37°C , PG synthesis followed the wild-type paradigm ( S5 Fig ) . In contrast , when the clpX mutant was grown at 30°C , the septal PG synthesis progressed abnormally in a substantial fraction of phase 2 cells , as 22 ± 3% of the clpX cells that had initiated septum formation in the first period of labeling ( NADA ) did not continue septum synthesis in the second period of labeling ( HADA ) . Instead , the HADA signal co-localized with the NADA signal in the early septum ingrowth , and additionally , a peripheral HADA signal was visible ( marked with white arrows in Fig 5A ) . Because other clpX cells displaying NADA labeling in an early septal ingrowth were indeed capable of septum progression and septum closure ( green arrows in Fig 5A ) , the septal PG synthesis rate does not seem to be generally reduced in the clpX mutant . Instead , the co-localization of the NADA and HADA in an early septum ingrowth may reflect stalling of inward septum progression in a subpopulation of clpX cells . Interestingly , in the presence of a sub-lethal concentration of oxacillin the fraction of clpX cells displaying co-localization of NADA and HADA at the early-septum ingrowth was reduced to 6 ± 2% ( Fig 5B ) . FDAAs only incorporate into newly synthesized PG and therefore premature splitting initiating from the peripheral wall cannot be detected with this approach [30] . However , splitting of newly synthesized , still incomplete , septum was observed ( red arrows in Fig 5A ) , and while this phenotype was not observed in wild-type cells , this phenotype was displayed in about 20 ± 2% of the clpX cells ( phase 2 cells ) grown in the absence of oxacillin . In the presence of oxacillin , only 8 ± 2% of clpX cells showed splitting of newly synthesized still incomplete septa ( see example in Fig 5B ) . In wild-type cells grown in the presence of oxacillin , NADA- and HADA signals more often co-localized in the entire septal plane ( examples depicted in Fig 5B ) , supporting that wild-type cells grown with oxacillin spend longer time in phase 3 . We conclude that at temperatures below the optimum , the ClpX chaperone activity becomes important for S . aureus septal PG synthesis to proceed beyond the point of septum initiation , and that oxacillin antagonizes the septum progression defects conferred by inactivation of ClpX . The results presented so far suggest that oxacillin improves growth of an S . aureus clpX mutant by allowing inward progression of the division septum and inhibiting premature splitting and lysis of daughter cells . To investigate septal PG synthesis in cells with premature splitting , we randomly picked 50 clpX cells grown at 30°C that had initiated septum formation during incubation with NADA , and that displayed the characteristic morphology of premature splitting , and assessed where HADA was incorporated in these cells . Interestingly , only very few clpX cells displaying premature septum split continued synthesizing septum ( Fig 5C-i ) ; instead HADA was incorporated at the cell periphery ( Fig 5C-ii ) . In a few cells no HADA signal was detected at all ( Fig 5C-iii ) . Hence , septal PG synthesis seems to stop and instead become dispersed to the peripheral wall in clpX cells displaying splitting of a yet incomplete septum . Remarkably , in oxacillin treated cells , septum synthesis progressed normally in most cells with premature split ( 40 ± 1 of 50 cells , P < 0 . 001 , Fig 5C ) . Taken together , this analysis demonstrates that oxacillin antagonizes the arrest of septum synthesis observed in clpX cells with premature septal split . ClpX from diverse bacteria interacts directly with FtsZ suggesting that the ClpX chaperone has a conserved role in assisting assembly/disassembly of the FtsZ polymer [31–34] . We therefore reasoned that ClpX may regulate septum progression by interfering with FtsZ . To study localization and constriction of the FtsZ-ring , a plasmid expressing eYFP-tagged derivative of FtsZ from an IPTG-inducible promoter [35] was introduced into the SA564 clpX mutant . However , although we succeeded in introducing the FtsZ::eYFP plasmid into the SA564 clpX mutant in several occasions , the fluorescent signal was lost upon further cultivation of the strain , suggesting that the expression of FtsZ::eYFP becomes toxic to SA564 devoid of ClpX even at 37°C . In contrast , the plasmid could be stably maintained in the 8325–4 background , and FtsZ localization and dynamics were instead performed in this strain . In both wild-type and clpX mutant cells , the Z-ring changed predictably throughout the cell cycle ( S2 Movie and Fig 6A ) : in newly divided cells , the Z ring has the same diameter as the cell until the ring starts to constrict and eventually closes ( as described in [36] ) . Following closure , FtsZ undergoes a period of highly dynamic re-distribution , before the Z-ring cycle starts over again in newly divided cells . Hence , FtsZ dynamics appear not to be affected by lack of ClpX activity . Next , we imaged the relative localization of FtsZ and PG synthesis by sequentially labeling PG synthesis with FDAAs as described above , except that tetramethylrhodamine 3-amino–d-alanine ( TADA , red signal but displayed in magenta ) was used instead of NADA to avoid overlap with the yellow eYFP signal . In both wild-type and clpX cells , the eYFP signal localized ahead of septal PG synthesis in all phase 2 cells ( Fig 6B and overview in S6 Fig ) . Specifically , FtsZ also localized ahead of the FDAA signal in clpX cells having HADA and TADA signal co-localizing in an early septum in growth ( Fig 6B ) . Strikingly , the FtsZ signal maintained its septal localization in clpX cells with premature split and arrest of septal PG-synthesis ( see example in Fig 6B ) . As also shown above , PG incorporation in such cells takes place in the peripheral wall . Hence , our data supports the idea that FtsZ dynamics is not impeded in cells lacking ClpX . Next , we asked if the ability to rescue growth of a S . aureus clpX cells is specific for the β-lactam class of antibiotics , and whether it depends on inhibition of specific PBPs ( S7 Fig ) . The compounds assessed were either antibiotics with completely different targets , compounds inhibiting various steps in the cell envelope synthesis pathway , or β-lactams that inhibit the four S . aureus PBPs with different specificities [37–40] . Intriguingly , tunicamycin and tarocin A1 , two well characterized inhibitors of the first step in the WTA biosynthesis pathway that work synergistically with β-lactams to kill MRSA [14 , 16] , were the only non β-lactam compounds that stimulated growth of the clpX mutant ( Figs 7A and 7B and S7 ) . In contrast , targocil that inhibits a late step in WTA biosynthesis , and does not restore sensitivity of MRSA to β-lactams [41] , did not improve growth of the clpX mutant ( Figs 7A and 7B and S7 ) . Similarly , late stage inhibitors of PG synthesis , such as vancomycin and lysostaphin that interfere with PG-crosslinking ( vancomycin through binding to the d-Ala-d-Ala dipeptide PG-stem unit , and lysostaphin , which breaks already formed cross-bridges ) , did not stimulate growth of the clpX mutant ( S7 Fig ) . Taken together , these findings demonstrate that neither inhibition of WTA synthesis nor reducing PG cross-linking per se will alleviate the growth defect of the clpX mutant . Testing β-lactams with varying PBP specificities showed that β-lactams specifically inhibiting PBP1 ( meropenem , imipenem , and cloxacillin ) , or PBP3 ( cefaclor ) stimulated growth of the clpX mutant most efficiently ( Figs 7A and S7 ) . Therefore , the specific binding of β-lactams to the trans-peptidase ( TP ) domain of PBP1 and PBP3 seems to be crucial for the ability of β-lactams to antagonize the severe growth defect imposed by the lack of ClpX at 30°C . The findings that tunicamycin , tarocin A1 , and β-lactam antibiotics specifically rescue growth of the clpX mutant point to the existence of a functional link between the early steps of WTA biosynthesis and the TP domain of PBPs that is critical for alleviating the clpX-phenotype . LTA synthesis seems to play a part in the same process , as loss-of-function mutations in ltaS also rescue growth of the clpX mutant [20] . Of special interest to the present study , LTA and ClpX have opposite roles in determining the level of the two major autolysins involved in daughter cell splitting , namely Sle1 and Atl [20] . One possible scenario is therefore that the elevated levels of Atl and Sle1 autolysins are causing premature splitting and lysis of clpX cells unless localization or activation of these autolysins is prevented . This model would be consistent with earlier reports demonstrating that WTA and LTA promote septal localization of autolysins [14 , 20 , 42 , 43] , and with our finding that oxacillin delays splitting of cells with completed septa . In support that autolysins contribute to the growth defect of the clpX mutant at 30°C , we found that inactivation of sle1 , and to a minor extent inactivation of atl , enabled the clpX strain to form visible colonies at 30°C ( Fig 7C ) . Thus , one simple scenario would be that β-lactam antibiotics and TarO inhibitors rescue growth of the clpX mutant by antagonizing mainly Sle1-mediated lysis .
Because mis-coordination in activation of autolytic enzymes may have fatal consequences , regulatory checkpoints that coordinate the autolytic system with septum completion likely exist , however , little is known about these mechanisms . Here , we show that the widely conserved ClpX chaperone plays a temperature dependent role in staphylococcal cell division resulting in severe morphological changes at 30°C but not at 37°C . In wild-type S . aureus cells , splitting of daughter cells is not initiated prior to septum closure . In contrast , a substantial fraction of clpX cells displaying incomplete septa had initiated splitting of daughter cells indicating that the system responsible for coordinating autolytic splitting with septum completion has become dysregulated . In clpX cells displaying the premature splitting phenotype , septal PG synthesis did not progress inwards , demonstrating that clpX cells with premature split are unable to finalize the septum . The detrimental character of this defect likely prevents cells from undergoing further divisions , explaining why a large proportion of clpX cells are non-dividing and end up lysing . In support hereof , TEM pictures show that most clpX ghost cells were in the process of splitting despite having an incomplete septum . This is likely due to turgor pressure forces breaking the tip of the ingrowing septum where the cell wall is thin and mechanically weak [44] . Hence , we assume that premature splitting is the underlying cause for the high rate of spontaneous lysis observed among clpX cells . Importantly , cells devoid of ClpX contain elevated levels of the two major autolysins associated with separation of S . aureus daughter cells , Sle1 and Atl [20 , 21 , 45–47] . Therefore , premature splitting of clpX cells could simply be a consequence of excess autolysins , and consistent with this assumption inactivation of sle1 and to a minor extent atl improved growth of the clpX mutant at 30°C . However , whilst SleI certainly contributes to the premature splitting and spontaneous lysis of clpX cells , additional factors are likely in play , as premature splitting and lysis of clpX cells is more frequent at 30°C than at 37°C , despite the finding that autolysin levels are elevated at both temperatures [20 , 21] . As a halt in inward progression of septum synthesis was observed in clpX cells only at the lower temperature , we speculate that this stalling of septum synthesis put the cells at risk for premature activation of autolysins , as depicted in the working model ( Fig 8 ) . In this model , S . aureus depends on ClpX chaperone activity for transforming an early stage divisome complex into a late stage divisome complex at 30°C , but not at 37°C . At both temperatures , the high levels of autolysins will make the clpX cells more prone to initiate daughter cell separation before septum completion . However , stalling of the divisome exacerbates the risk of premature split at 30°C . Consistent with this model , premature split could be observed in clpX cells grown at 37°C , however , at this temperature septal progression seems to proceed fast enough to enable completion of the septum , as outlined in Fig 8 . FtsZ localization and dynamics were not affected in the absence of ClpX , suggesting that ClpX affects septum formation downstream of Z-ring formation . Importantly , cytokinesis in Bacillus subtilis and S . aureus is proposed to occur in two-steps: an initial FtsZ dependent slow step that may drive the initial membrane invagination , and a second faster step driven by PG synthesis and recruitment of late division proteins such as PBPs [36 , 48] . Hence , we speculate that ClpX promotes septum progression at 30°C by directly , or indirectly , assisting assembly of this late divisome complex . Technically this will , however , be challenging to prove , as molecular chaperones like ClpX associate only transiently with folding intermediates of substrate proteins . Remarkably , the growth and lysis defect imposed by the clpX deletion was alleviated by sub-lethal concentrations of β-lactam antibiotics . This intriguing finding is to our knowledge the first example of β-lactam antibiotics being able to promote growth and preventing spontaneous lysis of a bacterial mutant . The presented data show that oxacillin simultaneously rescues septum synthesis , and prevents premature splitting , mesosome formation , and spontaneous lysis of the clpX mutant , lending support to a linkage between these phenotypes . The ability of sub-lethal concentrations of β-lactam antibiotics to suppress spontaneous lysis of clpX mutant cells was surprising , as loss of wall integrity accompanied by cell lysis is believed to contribute to the lethal activity of β-lactam antibiotics [5 , 9 , 49] . Here , we observed that oxacillin treatment of both S . aureus wild-type and clpX mutant cells increased the fraction of cells displaying a complete division septum , supporting previous findings that β-lactams delay autolytic splitting of daughter cells [7 , 28] . Moreover , the sequential PG staining experiments showed that late septal FDAA signals often overlap in wild-type cells grown in the presence of oxacillin , indicating that β-lactams prolong PG synthesis in the completed septum . Consistent with these findings , β-lactam treated S . aureus cells display characteristic thickened septum in TEM images [7 , 28] . Taken together , these findings indicate that the irreversible binding of β-lactams ( mimicking substrate binding ) to the TP domain of PBPs impedes activation of septal autolysins and abrogates the normal release of PBPs from the septal PG synthesis complex upon completion of the division septum . Hence , we speculate that the unoccupied TP domain upon completion of PG crosslinking plays a role in signaling that PG synthesis is complete , and that it is time to activate septal autolysins , and to release PBPs from the septal site . This hypothesis would be consistent with previous findings indicating that i ) the transpeptidation substrates recruit PBP2 to the division site , and that ii ) the TP site of PBP1 takes part in a checkpoint-type mechanism ensuring that autolytic splitting of daughter cells can only take place upon completion of septum synthesis [50 , 51] . Hence , oxacillin may rescue septum synthesis in clpX cells with premature split by stabilizing the late septal PG synthesis complex thereby reducing the risk of lysis ( Fig 8 ) . Previously , we showed that the fast-growing suppressor mutants arising when clpX cells are grown at 30°C have lost the ability to synthesize LTA [20] . Interestingly , we here show that inhibitors of the first step of WTA synthesis are the only other compounds that similarly to β-lactams rescue growth of the clpX mutant . LTA and WTA are both described to be critical for maintaining normal levels of peptidoglycan hydrolase activity [14 , 42 , 43] , and consistent with these findings the elevated levels of surface-anchored Atl and Sle1 in clpX cells are reverted to wild-type levels by inactivation of LtaS [20] . We , hence , speculate that inhibition of teichoic acid synthesis stimulates growth of the clpX mutant by antagonizing premature autolytic splitting of daughter cells ( Fig 8 ) . To follow up on the finding that TarO inhibitors specifically rescue growth of clpX mutants , we asked if genetic inactivation of tarO would also rescue growth of the clpX mutants , but did not succeed in deleting tarO in SA564 and JE2 clpX strains . This finding supports that TarO inhibitors do not simply rescue growth of clpX mutants by reducing WTA synthesis . Instead we speculate that the binding of tunicamycin or tarocin A1 to the TarO enzyme may , similarly to the binding of oxacillin to PBPs , induce a conformational change that is responsible for the stimulatory effect . However , more experimental data is required to clarify the underlying mechanism . In conclusion , we have shown that S . aureus cell division is temperature sensitive , and that the ClpX chaperone serves an important function in coordinating initiation of daughter cell separation with septum completion at 30°C . When ClpX is absent , cell division frequently has a fatal outcome because septal PG synthesis stalls and cell separation is initiated prior to completion of the septum . Interestingly , these defects were prevented by binding of β-lactam antibiotics to the PBP transpeptidase activity domain , indicating that this final stage in PG biosynthesis plays a role in coordinating septum synthesis and activation of autolytic splitting of daughter cells . Our work therefore supports the idea that in this clinically important bacterium , the effect of β-lactam antibiotics is tightly linked to coordination of cell division .
Strains used in this study are listed in S1 Table . S . aureus strains were grown in tryptic soy broth media ( TSB; Oxoid ) under vigorous agitation at 200 rpm at 37°C . In most experiments , 20 ml of medium was inoculated in 200-ml flasks to allow efficient aeration of the medium . For solid medium , 1 . 5% agar was added to make TSA plates . Erythromycin ( 7 . 5 μg ml-1 ) was added as required . Upon receipt of the low-passage isolate SA564 , the strain was cultured once and stored frozen at -80°C . In all experiments , we used bacterial strains freshly streaked from the frozen stocks on TSA plates with antibiotics added as required and incubated overnight at 37°C . The growth was followed by measuring the optical densities at 600 nm . The starting OD was always below 0 . 05 . When inoculating S . aureus clpX deletion strains , care was taken to avoid visibly larger colonies containing potential suppressor mutants [20] . To minimize the risk of selecting for fast-growing suppressor mutants in broth cultures of clpX mutant cells grown at 30°C , strains were first grown at 37°C for four generations ( OD600 ~0 . 1–0 . 2 ) before shifting to 30°C . S . aureus JE2-derived strains were obtained from the Network of Antimicrobial Resistance in Staphylococcus aureus ( NARSA ) program ( supported under NIAID/NIH contract HHSN272200700055C ) . All exponential growth rates were determined by growing the relevant strains in a Bioscreen C instrument: For growth in the BioscreenC instrument , overnight cultures were diluted in 300 μl TSB ( with or without antibiotics as indicated ) to an OD600 of approx . 0 . 001 , Plates were incubated at 30°C or 37°C and OD600 was measured every 5 min with 20 seconds of shaking before each measurement . The growth rates were automatically calculated as described before [20] . In short , OD600 values were log-transformed and linear regressions were determined for each data point in the OD600 interval from 0 . 02 to 0 . 12 based on a window containing 15 data points . The exponential growth rate was identified as the maximal slope of the linear regressions . The standard error of the mean was calculated using values from three biological replicates . Statistical significance was calculated using Student’s t-test . For end-point ODs , overnight cultures were diluted 1:200 in TSB and grown to exponential phase ( OD600 0 . 1 ) and then diluted 1:10 , 000 in 200 μl TSB ( with or without antibiotics as indicated ) in a 96-well microtiter plate , and incubated 24 h at 30°C with shaking . The final yield was determined by measuring the OD600 and by determining cfu ml-1 by plate counting . S . aureus strains were inoculated on TSA plates and incubated at 37°C overnight . The next day , a bacterial suspension was adjusted to a 0 . 5 McFarland ( Sensititre® nephelometer and the Sensititre® McFarland Standard ) and streaked on MHA . The plates were allowed to dry prior to the addition of 1 μg oxacillin discs ( Oxoid ) and incubated at 37°C for 48 hours . Cultures of SA564 wild-type and SA564ΔclpX were grown in TSB at 37˚C for four generations ( OD600 = 0 . 1 ) before shifting cultures to 30˚C and continuing growth in the absence or presence of 0 . 01 μg ml-1 oxacillin ( T = -90 ) for 90 minutes prior to imaging ( reaching OD600 of 0 . 5 ± 0 . 1 ) . Cells were subsequently washed in fresh TSB before spotting on TSB-polyacrylamide ( 10% ) slides supplemented with 0 . 008 μg ml-1 oxacillin when appropriate . Acrylamide pads were placed inside a Gene frame ( Thermo Fisher Scientific ) and sealed with a coverslip as described before [52] . Phase contrast image acquisition was performed using a DV Elite microscope ( GE healthcare ) with a sCMOS ( PCO ) camera with a 100x oil-immersion objective . Images were acquired with 200 ms exposure time every 6 minutes for at least 6 h at 30°C using Softworx ( Applied Precision ) software . Images were analyzed using Fiji ( http://fiji . sc ) . Each experiment was performed at least in triplicate . 25 micro colonies were imaged for SA564; 27 micro colonies for SA564 + oxacillin; 33 micro colonies for SA564 clpX; 24 micro colonies for SA564 clpX + oxacillin ( T = -90 ) and 26 micro colonies for SA564 clpX + oxacillin with no preexposure ( T = 0 ) . The frequency of clpX cells undergoing spontaneous lysis was determined by following the fate of all single cells in observable in the 26 and 33 imaged clpX micro colonies ( grown +/- oxacillin , respectively ) throughout the course of the experiment . To analyze FtsZ localization and dynamics , S . aureus wild-type ( 8325-4/pCQ11ftsZ::eYFP ) and clpX mutant ( 8325–4ΔclpX/pCQ11ftsZ::eYFP ) were grown overnight in TSB medium at 37°C and cultures were diluted 100 times in fresh TSB medium and grown until an OD600 of 0 . 1 . Cells were washed once in fresh TSB medium and spotted onto a TSB-polyacrylamide ( 10% ) slide incubated with TSB medium supplemented when appropriate with 100 μM IPTG . Acrylamide pads were placed inside a Gene frame ( Thermo Fisher Scientific ) and sealed with a cover glass as described before [52] . Time-lapse images of FtsZ-eYFP were acquired using a Leica DMi8 microscope with a sCMOS DFC9000 ( Leica ) camera with a 100x oil-immersion objective and a Spectra X ( Lumencor ) illumination module . Fluorescent images were acquired every 4 min with 400 ms exposure using a YFP filter cube ( Chroma , excitation 492–514 nm , dichroic 520 nm , emission 520–550 nm ) . Images were processed using LAS X ( Leica ) and signal was deconvolved using Huygens ( SVI ) software . S . aureus strains were grown in TSB at 37° until an OD600 of 0 . 1 . At this point the cultures were split in two and growth was continued at 30°C in the presence or absence of oxacillin ( 0 . 02 ug/Ml ) until the OD600 reached 0 . 9 . Muropeptides were obtained from purified peptidoglycan digested with the muramidase mutanolysin M1 ( Sigma ) , an n-acetylmuramidase that cuts glycan strands between the n-acetylmuramic and n-acetylglucosamine residues of both O-acetylated and unmodified peptidoglycan , as previously described in [53] . The resulting muropeptides were reduced with sodium borohydride ( Sigma ) and analyzed by reversed-phase HPLC using a HypersilODS column ( Thermo Fisher Scientific , Waltham , MA ) . Muropeptide species were eluted in 0 . 1 M sodium phosphate , pH 2 . 0 , with a gradient of 5–30% methanol for 155 min and detected at 206 nm . The eluted muropeptides were detected by determination of their UV absorption at 206 nm , using the software LC SOLUTION ( Shimadzu , Kyoto , Japan ) . Peaks corresponding to monomers , dimers , trimers to higher oligomers were assigned according to previous nomenclature [54] . PBP levels were analyzed as described previously [55] . In short , membrane proteins were purified from late-exponential cultures ( OD600 of 1 ) of SA564 wild-type and the corresponding clpX mutant grown at 30°C or 37°C in the presence or absence of oxacillin at 0 . 05 ug/mL . Cells were resuspended in 50 mM Tris , 150 mM NaCl , 5 mM MgCl2 buffer , pH 7 . 5 supplemented with phenylmethylsulfonyl fluoride ( 0 . 5 mM ) , b-mercaptoethanol ( 10 mM ) , Lysostaphin ( 100 mg ml-1 ) , DNase ( 20 mg/ml , and RNase ( 10 mg ml-1 ) . The cell suspension was incubated at 37°C for 30 min followed by sonication for 5 cycles of 1 min with 2 min intervals on ice between each cycle . The membranes were harvested by ultracentrifugation at 110 , 000 X g for 40 min at 4°C and solubilized in 2% Triton X-100 . 100 ug purified membrane was labeled with Bocillin-FL ( 100 uM ) for 10 minutes at 30°C . The reaction was stopped by adding 5X volume of sample buffer . PBPs were separated on a 7 . 5% SDS gel and visualized using fluorography . PBP4 levels were additionally determined by Western blot analysis using antibodies specific for S . aureus PBP4 as described in [21] . Densitometry analysis for three biological replicates was performed using the Fiji “Gel Analysis tool” , where the gel background was removed individually for each band . SR-SIM was performed with an Elyra PS . 1 microscope ( Zeiss ) using a Plan-Apochromat 63x/1 . 4 oil DIC M27 objective and a Pco . edge 5 . 5 camera . Images were acquired with five grid rotations and reconstructed using ZEN software ( black edition , 2012 , version 8 . 1 . 0 . 484 ) based on a structured illumination algorithm , using synthetic , channel specific optical transfer functions and noise filter settings ranging from -6 to -8 . Laser specifications can be seen in S2 Table . SR-SIM was performed at CFIM . The volume of 100 phase 1 cells was determined ( three biological replicates ) as described in [24] . Briefly , an ellipse was fitted to the border limits of the membrane and measurements of the minor and major axis were acquired . The shape of the cells was assumed to be that of a prolate spheroid and the volume was estimated by the equation V = 4/3πab2; a and b correspond to the major and minor axes , respectively . Ellipse fitting and measurements were performed using ImageJ . To address progression of the cell cycle , exponential cultures of S . aureus were incubated for 5 min at room temperature with the membrane dye Nile Red , the cell wall dye WGA-488 or Van-Fl and the DNA dye Hoechst 3334 ( S3 Table ) . Samples were placed on an agarose pad ( 1 . 2% in PBS ) and visualized by SR-SIM as described above . 300 cells were scored according to the stage of septum ingrowth: no septum ( phase 1 ) , incomplete septum ( phase 2 ) , or non-separated cells with complete septum ( phase 3 ) . Dead cells were scored based on Hoechst staining: lysed cells , as cells where DNA had leaked out of the cell and anucleated cells as cells devoid of Hoechst staining . The analysis was performed on two biological replicates . Additionally , 200 cells were scored according to the state of septum ingrowth by measuring the length of the ingrowing septum relative to the cell diameter using Fiji . Cells with less than 15% septum ingrowth were scored as “early” , while cells with more than 15% septum ingrowth were scored as “late” . Additionally , the fractions of cells displaying asymmetrical septum ingrowth , or showing signs of premature splitting was ( based on staining with Van-FL ) were scored . This analysis was performed on two biological replicates . To evaluate localization of PG synthesis , exponential cultures of S . aureus ( SA564 or 8325–4 ) were pulse labeled with FDAAs; cells were initially incubated 10 minutes with NADA , washed in PBS and resuspended in TSB . The cells were then incubated 10 minutes with HADA , washed with PBS , placed on an agarose pad and visualized by SR-SIM . This experiment was conducted in three biological replicates including a staining in reverse order and one using the red TADA as a replacement for NADA . Analysis on the progression of PG synthesis was performed on 300 cells for each biological replicate with similar results . To investigate the progression of septal PG synthesis in clpX mutant cells displaying premature split , HADA incorporation was assessed in 50 cells ( in each of three biological replicates ) that had initiated septum formation during the initial labeling and displayed the characteristic morphology of premature splitting . In order to assess FtsZ relative to the active PG synthesis , S . aureus ( 8325–4 ) wild-type and clpX mutant transformed with pCQ11 expressing an eYFP-tagged derivative of FtsZ from an IPTG-inducible promoter were analyzed using sequentially labeling with FDAAs as described above ( incubation with TADA for 10 minutes followed by HADA for 10 minutes ) . Cells were grown at 30°C in the presence of 50 μM IPTG ( at higher IPTG concentrations cell division defects were observed in the wild-type strain ) . In order to assess if genetic inactivation of tarO rescues growth of S . aureus clpX mutants we attempted to delete the tarO from the chromosome as described in [56] . In brief , the pMAD pΔtagO plasmid was electroporated into SA564clpX and JE2clpX strains at 34°C instead of 30°C to reduce the risk of selecting for spontaneous suppressor mutants in the clpX strains [20] . To achieve integration into the chromosome by homologous recombination , cultures were grown at 42°C ( non-permissive for plasmid replication ) for 8 h before serially diluting and plating on TSA plates containing 5 mg ml-1 erythromycin . Plasmid integration into the chromosomal tarO locus was confirmed using primer sets P5: 5’—CTC CGT AAC AAA TTG AGG ATA ACA—3’and P4: 5’- TAG TCG TCC TCC TAA AAT ATA CTC– 3’ or P3: 5’—CCT AAG CCT GTT AAG TAA TCA TAT -3’ and P6: 5’—GAT CGA AGT TAG GCT GGT AAG A- 3’ . A single colony was subsequently inoculated into 5 ml of TSB , and the culture was grown at the permissive temperature ( 34°C ) in the absence of antibiotic selection to stimulate plasmid excision . At this stage , colony PCR , using primers P3: 5’—CCT AAG CCT GTT AAG TAA TCA TAT -3’ and P4 was performed to identify colonies that carried the chromosomal tarO deletion . In these cells , tarO is present on the pMAD plasmid and in order to lose the plasmid , cells were grown at the non-permissive temperature ( 37°C or 40°C as wild-type tarO mutants cannot grow at 42°C ) . We were , however , unable to achieve plasmid loss this way . Instead , we tried to select for tarO mutants by adding 1 μg ml-1 targocil ( toxic to cells with an intact copy of tarO ) to the growth medium , but all attempts to create clpX , tarO double mutants were unsuccessful [57] . Statistical analysis was done using R statistical software . Student’s t-test was used to assess significant differences in growth in the absence or presence of a tested antibiotic . The Chi-squared test of independence was used to determine if there was a significant relationship between the proportion of cells assigned to each of the three phases or relevant phenotypes under the tested condition ( number of cells in the relevant phase or phenotype/the total number of cells ) . A value P < 0 . 05 was considered significant .
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The bacterium Staphylococcus aureus is a major cause of human disease , and the rapid spread of S . aureus strains that are resistant to almost all β-lactam antibiotics has made treatment increasingly difficult . β-lactams interfere with cross-linking of the bacterial cell wall but the killing mechanism of this important class of antibiotics is not fully understood . Here we provide novel insight into this topic by examining a defined S . aureus mutant that has the unusual property of growing markedly better in the presence of β-lactams . Without β-lactams this mutant dies spontaneously at a high frequency due to premature separation of daughter cells during cell division . Cell death of the mutant can , however , be prevented either by exposure to β-lactam antibiotics or by inhibiting synthesis of wall teichoic acid , a major component of the cell wall in Gram-positive bacteria with a conserved role in activation of autolytic splitting of daughter cells . The finding that β-lactam antibiotics can prevent lysis of a mutant with deregulated activity of autolytic enzymes involved in daughter cell splitting , emphasizes the idea that β-lactams interfere with the coordination between cell division and daughter cell splitting , and do not kill S . aureus simply by weakening the cell wall .
|
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"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
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"antimicrobials",
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"methicillin-resistant",
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] |
2019
|
The ClpX chaperone controls autolytic splitting of Staphylococcus aureus daughter cells, but is bypassed by β-lactam antibiotics or inhibitors of WTA biosynthesis
|
Insulators are DNA elements that divide chromosomes into independent transcriptional domains . The Drosophila genome contains hundreds of binding sites for the Suppressor of Hairy-wing [Su ( Hw ) ] insulator protein , corresponding to locations of the retroviral gypsy insulator and non-gypsy binding regions ( BRs ) . The first non-gypsy BR identified , 1A-2 , resides in cytological region 1A . Using a quantitative transgene system , we show that 1A-2 is a composite insulator containing enhancer blocking and facilitator elements . We discovered that 1A-2 separates the yellow ( y ) gene from a previously unannotated , non-coding RNA gene , named yar for y-achaete ( ac ) intergenic RNA . The role of 1A-2 was elucidated using homologous recombination to excise these sequences from the natural location , representing the first deletion of any Su ( Hw ) BR in the genome . Loss of 1A-2 reduced yar RNA accumulation , without affecting mRNA levels from the neighboring y and ac genes . These data indicate that within the 1A region , 1A-2 acts an activator of yar transcription . Taken together , these studies reveal that the properties of 1A-2 are context-dependent , as this element has both insulator and enhancer activities . These findings imply that the function of non-gypsy Su ( Hw ) BRs depends on the genomic environment , predicting that Su ( Hw ) BRs represent a diverse collection of genomic regulatory elements .
In eukaryotic genomes , neighboring genes often display distinct spatial and temporal patterns of transcription , even though intergenic distances are within the range of enhancer and silencer action . These observations suggest that constraints exist that limit promiscuous interactions between long distance regulatory elements and non-target promoters . Chromatin insulators represent one class of genomic elements that restrict enhancer and silencer action [1]–[5] . Insulators have been identified based on two functional properties . First , insulators prevent enhancer and silencer modulation of a promoter in a position-dependent manner , such that an enhancer or silencer is blocked only when the insulator is located between these elements and a promoter . Second , insulators protect gene expression from positive and negative chromosomal position effects associated with ectopic placement of genes within genomes , an activity referred to as barrier function . Sequences with one or both of these properties have been identified in most eukaryotic genomes and have been implicated in the regulation of diverse cellular processes , ranging from centromere function in yeast to imprinting in mammals [6] , [7] . These observations imply that insulators are fundamental components of eukaryotic genomes . One of the best-characterized insulators resides in the 5′ untranslated region of the Drosophila gypsy retrovirus . This versatile gypsy insulator blocks over twenty enhancers active in different tissues and developmental stages , prevents repressive effects caused by Polycomb group complexes and heterochromatin and protects an origin of DNA replication from chromosomal position effects [2] , [5] . The gypsy insulator consists of a cluster of twelve repeats that are bound by the zinc finger Suppressor of Hairy-wing [Su ( Hw ) ] protein [8] . At least three additional proteins are associated with the gypsy insulator , including Modifier of ( mdg4 ) 67 . 2 ( Mod67 . 2 ) , Centrosomal Protein of 190 kD ( CP190 ) and Enhancer of y2 [E ( y ) 2] . In general , Mod67 . 2 and CP190 are required for enhancer and silencer blocking by the gypsy insulator , while E ( y ) 2 has been shown to be required only for barrier function [9]–[13] . The Su ( Hw ) protein associates with hundreds of non-gypsy regions in the Drosophila genome that have a largely unknown function . The extensive co-localization of the four gypsy insulator proteins at non-gypsy regions has led to the proposal that these represent chromatin insulators . Yet , non-gypsy Su ( Hw ) binding regions are different in sequence and organization from the gypsy insulator , with the majority of BRs containing single Su ( Hw ) binding sites ( BSs ) [14]–[18] . This observation is striking , as at least four tightly spaced Su ( Hw ) sites from the gypsy insulator were required for robust enhancer blocking [19]–[21] . Direct tests of the non-gypsy BRs in transgene assays show that most , but not all , interfere with enhancer-activated transcription [15]–[18] . These findings imply that non-gypsy regions contain additional elements that assist the insulator function of Su ( Hw ) . The first non-gypsy Su ( Hw ) BR identified , named 1A-2 , is a cluster of two Su ( Hw ) BSs located in cytological region 1A ( Figure 1 ) . Here we investigated the properties of 1A-2 , using two strategies . First , we employed a quantitative transgene system to define the 1A-2 sequences required for enhancer blocking . Second , we performed homologous recombination to establish lines carrying a deletion of 1A-2 at the natural genomic location , representing the first deletion of a non-gypsy Su ( Hw ) BR in the Drosophila genome . Effects of the loss of these sequences on gene expression in the 1A region were determined , leading to the discovery that 1A-2 contributes to transcriptional activation of a novel , non-coding RNA gene . Taken together , our studies demonstrate that 1A-2 has both activator and insulators properties , depending on the context tested . These findings imply that properties of non-gypsy Su ( Hw ) BRs are influenced by the genomic environment , predicting that Su ( Hw ) BRs represent a diverse collection of elements with distinct regulatory functions .
The Su ( Hw ) BR 1A-2 is a 520 bp element that contains two Su ( Hw ) BSs [18] and a CP190 BS [9] . Previous studies using qualitative transgene assays demonstrated that 1A-2 blocked enhancer-activated transcription in a position-dependent manner , a key feature of insulator activity [17] , [18] . We employed the quantitative Fat Body Enhancer ( FBE ) 1-yolk protein ( yp ) 2 -LacZ transgene to define DNA sequences required for 1A-2 enhancer blocking ( Figure 1 ) , a system previously used to characterize properties of the gypsy insulator [20] , [22] . A reporter transgene was constructed wherein full length 1A-2 ( 520 ) was inserted between FBE1 and the yp2 promoter . Multiple P[F-1A-2 ( 520 ) -yp2] transgenic lines with single insertions were established . Quantitative β-galactosidase activity assays were completed to define the level of yp2 promoter activity . Protein extracts were isolated from adult females representing several independent lines , and multiple assays were undertaken to establish an average activity unit ( aau ) for each transgene ( Figure 1 ) . We found that transgenic P[F-1A-2 ( 520 ) -yp2] females had low levels of yp2 expression ( aau 0 . 86 ) , similar to levels in P[F-gyp-yp2] females ( aau 0 . 75 ) and significantly lower than levels found in the control P[FBE1-yp2] females ( aau 5 . 97 ) . We conclude that 1A-2 blocks FBE1 , extending the enhancer blocking effects of 1A-2 to a new enhancer-promoter pair . The minimal sequences required for 1A-2 insulator function were determined by generation of transgenic lines carrying transposons with insertion of subregions of 1A-2 between FBE1 and yp2-LacZ ( Figure 2 ) . P[F-1A-2 ( 157 ) -yp2] females showed a strong enhancer block ( aau 0 . 62 ) . As this subregion lacks the CP190 BS [9] , these findings indicate that direct CP190 binding is not required for insulator function . 1A-2 ( 157 ) was further divided into two parts , one containing the two Su ( Hw ) BSs , 1A-2 ( 79 ) , and one containing the remaining sequences , 1A-2 ( 78 ) . Transgenic P[F-1A-2 ( 79 ) -yp2] females showed a two-fold weaker enhancer block than 1A-2 ( 157 ) ( aau 1 . 29 , P = 0 . 02 ) , whereas P[F-1A-2 ( 78 ) -yp2] females showed high yp2 activity levels , close to those obtained for the control P[F-yp2] females ( aau 5 . 9 versus 5 . 97 ) . These data suggest that 1A-2 ( 78 ) contributes to the blocking effectiveness of the 1A-2 Su ( Hw ) BSs , but cannot itself block enhancer-promoter interactions . We considered two possibilities to account for the contributions made by 1A-2 ( 78 ) . First , these sequences might contain a binding site ( s ) for a second insulator protein that cooperates with the Su ( Hw ) BSs for insulator function . Second , 1A-2 ( 78 ) might improve the activity of the Su ( Hw ) BSs , perhaps by increasing in vivo association . We reasoned that if 1A-2 ( 78 ) contained a binding site for a novel insulator protein , then insulator effects might require a reiterated element , as observed previously when individual binding sites for other insulator proteins were tested [23] , [24] . To this end , we generated P[F-1A-2 ( 78×4 ) -yp2] that carried four copies of 1A-2 ( 78 ) inserted between FBE1 and the yp2 promoter . Surprisingly , these transgenic females had higher yp2 activity than the control P[F-yp2] females ( aau 18 . 78 versus 5 . 97 aau , P = 6 . 3×10−8 ) . Transgenic P[F-1A-2 ( 78×4 ) -yp2] males showed no yp2 activity ( data not shown ) . Based on the retained transcriptional specificity of the P[F-1A-2 ( 78×4 ) -yp2] transgene , we conclude that 1A-2 ( 78 ) is not a general transcriptional enhancer but improves the activity of FBE1 . These data imply that 1A-2 ( 78 ) may possess a general activity that facilitates factor association . To test this postulate , we determined whether 1A-2 ( 78 ) restored enhancer blocking to a synthetic Su ( Hw ) BR containing three reiterated gypsy BSs ( 3R:3 ) that was previously shown to be inactive in this transgene system [20] . Supporting a facilitator function of 1A-2 ( 78 ) we found that transgenic P[F- 3R:3-1A-2 ( 78 ) -yp2] females had low yp2 activity ( aau 0 . 22 ) . These studies show that in the presence of 1A-2 ( 78 ) , 3R:3 became a strong insulator . As previous findings suggest that the effectiveness of enhancer blocking by the Su ( Hw ) protein is limited by the in vivo accessibility of Su ( Hw ) , we conclude 1A-2 ( 78 ) is a facilitator that may improve transcription factor binding to chromosomes . As a first step in defining the role of 1A-2 within the y-ac region , we evaluated whether the existing annotation reflected the transcriptional potential of this region . These analyses were motivated by the recent studies showing widespread transcription in intergenic regions of the Drosophila genome [25] . A search of the NCBI databases uncovered a small , novel , processed EST of ∼400 nt that was transcribed from the y-ac intergenic sequences . Sequences corresponding to this EST are located ∼1 . 4 kb downstream of the y termination signal and transcribed in the same direction as the y and ac genes . Northern analyses of embryonic polyA+ RNA using a radiolabeled probe representing the intergenic EST identified a family of RNAs , with the most abundant species sized at ∼1 . 6 kb ( Figure 3 ) . Accumulation of these RNAs began ∼7 hours after the start of embryogenesis , in agreement with the expression profile obtained using tiling array studies of embryonic RNAs [25] . These data suggest that the y-ac intergenic region contains a previously uncharacterized gene , which we call yar , for y-ac intergenic RNA . Activation of genes in the 1A locus is temporally in an order following chromosomal position , such that ac , then yar and then y is transcribed . The structure of the yar RNAs was defined using rapid amplification of cDNA ends ( RACE , Figure 4 ) . Sequence analysis of the 5′ RACE products revealed three discrete transcription start sites within an ∼200 bp region , with the most distal RNA starting ∼1 . 2 kb downstream of the y gene . Each putative start site showed weak homology to Drosophila transcriptional control elements [26] , with two having a partial match to the TATA consensus sequence located 17 to 35 bp upstream of the start site . Sequence analysis of the 3′ RACE products identified multiple splice variants , each ending in a common exon that contained an unconventional polyadenylation signal sequence AAATACA , previously estimated to be present in ∼3% of Drosophila genes [27] , that was located 12 bp upstream of the string of As in the RACE products . Predicted translation of the yar RNAs indicated that no transcript would encode a protein of more than 75 amino acids , implying that yar is a non-coding RNA gene . Ends out gene targeting was used to delete 1A-2 from the y-ac region ( Figures 4 , 5 ) . Gene targeting is a two step processes that requires establishment of transgenic flies that carry a transposon with the replacement gene , followed by the introduction of endonucleases to stimulate homologous recombination between the replacement gene and its endogenous homologue . To delete 1A-2 , we constructed P[yΔ1A-2 target] . This transposon carried a modified y gene , wherein 1A-2 was replaced by the hypomorphic whs gene that was flanked by loxP sites ( Figure 5 ) . Transgenic lines were established in a y1 w1118 background , where the endogenous y gene carried a mutation of the translation start codon , and the endogenous w gene carried a deletion of the promoter . P[yΔ1A-2 target] flies had orange eyes and dark pigmentation of all cuticle structures except the wing , as the y gene lacked the wing enhancer . To stimulate recombination , transgenic y1 w1118; P[yΔ1A-2 target] males were crossed to females carrying the heat shock ( hs ) -FLP recombinase and the hs-I-SceI endonuclease transgenes and progeny of this cross were heat shocked to produce the endonucleases . Over 100 resulting females were crossed to y1 w1118 males and homologous recombinants were identified among the offspring of this cross in two ways . First , flies were screened for dark wings , as recombination at the endogenous y1 gene would reconstitute a wild type y transcription unit with all enhancers , whereas progeny with ectopic insertions of the replacement y gene would produce flies with lightly colored wings due to the absent wing enhancer . Second , we conducted genetic analyses to determine whether the w+ phenotype was linked to the X chromosome . Five putative homologous recombination lines were established based on dark wing pigmentation . Further genetic analyses showed that in one line , XGL339-23-38 , the w marker mapped to the X chromosome , suggesting a correct targeting event . Southern analyses confirmed the structure of the y gene in these flies ( Figure S1 ) . This targeted allele was named , yΔ1A-2w . We reasoned that if 1A-2 was an insulator in the y-ac locus , then deletion of 1A-2 would release constraints on the y and ac enhancers , causing changes in gene expression that would alter cuticle pigmentation and bristle number in yΔ1A-2w relative to wild type flies [28] , [29] . However , we found that adult phenotypes of yΔ1A-2w flies were indistinguishable from wild type flies . In yΔ1A-2w , the whs gene replaced 1A-2 . To rule out the possibility that this gene served as a surrogate insulator by carrying a promoter that captured the y and ac enhancers , yΔ1A-2w flies were crossed to flies carrying a source of Cre recombinase to remove the whs gene . Southern and PCR analyses confirmed the structure of y gene in yΔ1A-2 flies ( Figure S1 ) . Again , the cuticle and bristle phenotypes of the yΔ1A-2 flies were indistinguishable from wild type . Taken together , these data imply that 1A-2 is not an insulator at the endogenous genomic location . Within the y-ac intergenic region , we identified a second cluster of Su ( Hw ) binding sites , which we called 1A-2′ . These sites differ from the Su ( Hw ) consensus sequence at multiple highly conserved positions ( Figure 4 ) . Electrophoretic mobility shift assays demonstrated that 1A-2′ had ∼3-fold lower affinity for Su ( Hw ) than 1A-2 ( data not shown ) . Even so , we considered it possible that weaker 1A-2′ Su ( Hw ) BR might provide a redundant function with 1A-2 to define regulatory interactions in the y-ac region . For this reason , we generated a second targeting vector , P[yΔ1A-2/Δ1A-2′ target] , wherein the whs gene replaced an ∼1 . 0 kb deletion that encompassed both 1A-2 and 1A-2′ . Following the procedure described above , six putative homologous recombinant lines were identified based on dark wing pigmentation . Further genetic analyses showed that one of these lines , XGL426-41-4 , had marker linkage to the X chromosome . This allele was named yΔ1A-2/Δ1A-2′w . Flies from this line were used to obtain a derivative line lacking the whs gene , producing yΔ1A-2/Δ1A-2′ . Southern and PCR analyses confirmed the structure of the y gene resulting from these targeting events ( Figure S1 ) . Comparison of adult phenotypes in yΔ1A-2/Δ1A-2′ and wild type flies showed that the cuticle color and bristle number were indistinguishable , suggesting that 1A-2′ did not compensate for 1A-2 .
We used the quantitative FBE1-yp2-LacZ reporter system to define the sequence requirements for enhancer blocking by 1A-2 ( 520 ) . Prior application of this system demonstrated that at least four gypsy Su ( Hw ) sites were needed for robust blocking [20] . Here , we show that 1A-2 ( 157 ) provided as strong an enhancer block as the gypsy insulator ( Figures 1 , 2 ) . A fragment containing only the Su ( Hw ) BRs [1A-2 ( 79 ) ] reconstituted a weaker enhancer block than 1A-2 ( 157 ) , but had a greater blocking capacity than the synthetic insulators made from reiterated copies of BS3 of the gypsy insulator [20] . While we do not know the reason for the more robust blocking , we note that these regions differ in sequence and distance of separation from Su ( Hw ) sites ( Figure 4 ) . Blocking effectiveness does not appear to be due to differences in DNA recognition , as the in vitro binding constants for Su ( Hw ) for the 1A-2 and gypsy BSs are similar [16] . Our experiments revealed that 1A-2 contains a second regulatory element located in 1A-2 ( 78 ) . When these sequences were positioned next to the inactive , synthetic Su ( Hw ) BR ( 3R:3 ) , a functional insulator was reconstituted ( Figure 2B ) . These data are consistent with previous findings that Su ( Hw ) chromosome association is limited [32] . Taken together , we propose that 1A-2 is a composite insulator that contains an enhancer blocking and a facilitator function that may improve Su ( Hw ) chromosome association . Further , we predict that in vivo effectiveness of enhancer blocking by the Su ( Hw ) protein is related to the accessibility of Su ( Hw ) BSs . If single or small clusters of Su ( Hw ) BSs are located in genomic regions of open chromatin , then these regions will demonstrate enhancer blocking , as defined in transgene assays . This proposal implies that genomic context greatly influences the properties of non-gypsy Su ( Hw ) BRs . 1A-2 is located between the independently regulated y and ac genes . Chromatin immunoprecipitation studies demonstrated that 1A-2 is associated with Su ( Hw ) , Mod67 . 2 and E ( y ) 2 in vivo [12] , [16] , [18] , suggesting that this element binds a complex competent for establishing a genomic insulator . Based on these properties , we postulated that 1A-2 was responsible for the regulatory independence of the y and ac genes in the 1A locus [16] . As a first step in testing this proposal , we investigated transcription in the y-ac region to evaluate the current accuracy of the genomic annotation of this region . These studies identified a previously unannotated gene , yar , located ∼1 . 2 kb downstream of the y gene and ∼3 . 0 kb upstream of ac . Multiple , differentially spliced , polyA+ RNAs are encoded by yar , with the largest translation product predicted to be 75 amino acids , indicating that this is a non-coding RNA gene . Emerging data suggest that non-coding RNAs are abundant in eukaryotes and have a wide repertoire of biological functions , ranging from structural components in protein complexes to regulatory molecules involved in transcription and translation [33]–[35] . It is unknown whether yar has a function . As flies carrying a large genomic deletion that removes sequences upstream of y and extends downstream of ac ( y− ac− ) are viable and fertile , yar is a non-essential gene . Having re-defined the transcriptional profile in the 1A locus , we tested the function of 1A-2 and a second , weaker Su ( Hw ) BR , 1A-2′ , on gene regulation , using gene targeting to delete these elements . Our studies represent the first deletional analysis of any non-gypsy Su ( Hw ) BR in the Drosophila genome . Two targeted deletion lines , yΔ1A-2 and yΔ1A-2/Δ1A-2′ were established ( Figure 4 ) . Levels of y , ac , sc and yar RNA accumulation during development were studied using quantitative PCR . We find that loss of 1A-2 and 1A2′ has no effect on the timing and level of y , ac or sc RNAs relative to the wild type control ( Figure S3 ) , but strongly reduced yar RNA ( Figure 6 ) . These data suggest that the effects of loss of 1A-2 are limited to local changes of gene expression , implying that these sequences are not a chromatin insulator at the endogenous location . Instead , our data indicate that 1A-2 may be an activator of yar expression , consistent with other studies that have suggested a role for Su ( Hw ) in gene activation [36]–[38] . These data , coupled with genetic studies on the effects of the loss of Su ( Hw ) on expression of genes adjacent to Su ( Hw ) BRs [16] , demonstrate that Su ( Hw ) BRs have diverse functions in the genome . The complexity of the transcriptional effects associated with Su ( Hw ) BRs is reminiscent of regions in mammalian genomes that bind the versatile regulatory protein CTCF . High throughput genomic analyses have identified hundreds of CTCF binding sites within the mouse and human genomes [7] , [39]–[41] . Although many of these sequences possess enhancer blocking activity [39] , [42] , [43] , CTCF has been implicated in transcriptional activation [44]–[46] , repression [47]–[50] , and chromosome pairing [44] , [51] , [52] . These observations suggest that , similar to the non-gypsy Su ( Hw ) BRs , genomic context will have an important influence on the properties of CTCF BSs within a given region . The mechanism ( s ) used to maintain transcriptional autonomy in the 1A locus are unclear . The discovery of yar provides an alternative explanation to the need for a chromatin insulator . Based on the developmental timing displayed by the 1A genes , we postulate that activation of yar transcription may cause inactivation of ac through transcriptional interference . Similarly , activation of y may repress yar transcription . Although yΔ1A-2 and yΔ1A-2/Δ1A-2′ flies show reduced yar expression , transcription is not abolished , suggesting that the remaining yar activity may be sufficient to turn off ac . Alternatively , other mechanisms can be considered that might influence enhancer preference , including selectivity of enhancers for certain classes of promoters [53] , [54] , the presence of promoter targeting sequences that direct enhancer action [55] , [56] , or promoter tethering elements that capture enhancers [57] . Further experiments to define the properties of DNA elements within the 1A locus will resolve how transcriptional independence is achieved .
Flies were raised at 25°C , 70% humidity on standard corn meal/agar medium . Description of the alleles used can be found at http://flybase . bio . indiana . edu . The FBE1-yp2 -LacZ fusion gene [20] carried a BglII site , positioned at −335 relative to the transcription start site ( TSS ) that was used for insertion of tested 1A-2 fragments . Resulting transgenes were inserted into a P element transformation vector , generating P[F-1A-2 ( 520 ) -yp2] with the full length 1A-2 , P[F-1A-2 ( 157 ) -yp2] with a 157 bp region of 1A-2 , P[F-1A-2 ( 79 ) -yp2] with two 1A-2 Su ( Hw ) binding sites , P[F-1A-2 ( 78 ) -yp2] with the 78 bp 3′ region , P[F-1A-2 ( 78×4 ) -yp2] with four tandem repeats of the 1A-2 78 bp element and P[F-3R:3 ( 78 ) -yp2] with a hybrid insertion between a cluster of three tandem repeats of the gypsy Su ( Hw ) binding sites [nucleotides 732–759 [58]] , as described in [20] and the 78 bp element . P transposons were injected into the host y1w67c23 strain or w1118 ( Genetic Services , Inc , Cambridge , MA ) . Transgenic lines were analyzed by Southern and PCR analyses to determine the number and integrity of the transposons . Lines with single transposon insertions were used in subsequent analyses . The yp2 promoter activity was assessed using quantitative β-galactosidase assays , performed essentially as previously described [20] . Each transgenic line was assayed using extracts isolated from three different matings . Each extract was assayed in duplicate , and the error between these samples was less than 10% . Average promoter activity and standard deviation were determined using the statistical analysis feature of the Microsoft Excel program . Two targeting transposons were constructed for gene targeting , using pW25 [59]–[61] . This vector has multi-cloning site , NotI-SphI-Acc65I-Stop-lox-whs-lox-Stop-AscI-BsiWI . The lox sites are in direct orientation , permitting removal of the whs transformation marker by Cre recombinase . P[yΔ1A-2 target] ( XGL339 ) was used to target an ∼0 . 43 kb deletion encompassing 1A-2 alone , whereas P[yΔ1A-2/Δ1A-2′ target] ( XGL426 ) was used to target an ∼1 . 03 kb deletion that included 1A-2 and 1A-2′ . These targeting transposons were generated in a two-step procedure . First , a 6 . 6 kb yellow fragment ( −1842 to +4796 relative to the yTSS ) was PCR amplified , using primers carrying the BsiWI and AscI sites and cloned into pW25 to make XGL235 . This fragment contains the yellow transcription unit and the body enhancer , but lacks the wing enhancer . Second , PCR primers containing NotI sites generated a 3 kb fragment ( y+5234 to y+8184 relative to the yTSS ) to make P[yΔ1A-2 target] or a 3 . 5 kb fragment ( y+5826 to y+9318 relative to the yTSS ) to make P[yΔ1A-2/Δ1A-2′ target] . In all cases , PCR fragments were sequenced to confirm appropriate amplification . For targeting , we generated transgenic lines in a y1 w1118 mutant background . Gene targeting followed the procedure outlined in [59] . A combination of Southern and PCR analyses identified correctly targeted events . To remove the whs gene , red-eyed males carrying a targeted deletion event were crossed to females carrying Cre recombinase , as described in [62] . The white-eyed flies were collected and used to establish homozygous stocks . Deletion events were confirmed by PCR amplification and sequence analyses . The structures of the yar RNAs were determined using RACE of total RNA isolated from 6–12 hour CS embryos . In the 3′-RACE experiments , 5 µg of RNA were reverse transcribed using the adaptor oligo-dT primer ( 3′-RACE kit , Invitrogen ) , and cDNA was amplified using a yar specific primer ( 1 µM ) and the abridged universal primer ( 80 nM , Invitrogen ) . Several products were identified by agarose gel electrophoresis , gel purified and cloned into the TOPO vector ( Invitrogen ) . Sequencing and BLAST search identified three yar splice variants that shared a common distal exon and poly-A signal . In the 5′-RACE experiments , 5 µg of RNA were reverse transcribed with a yar specific primer ( 100 nM ) , purified over a S . N . A . P column ( Invitrogen ) to remove unincorporated nucleotides and primers , and C-tailed at 4° for 2 hours , using terminal deoxynucleotidyl transferase . Tailed cDNAs were amplified with nested yar specific primers ( 400 nM ) and an abridged anchor primer ( 400 nM , Invitrogen ) . PCR products were directly cloned into the TOPO vector . Forty-eight clones were analyzed by restriction digestion , revealing nine classes of insert . At least one representative of each class was sequenced . BLAST analyses of these data identified ten alternative splice variants and three alternative start sites . Both the 3′-RACE and 5′-RACE were performed on two independent RNA isolations . Gene-specific primer sequences are available upon request . RNA was isolated from staged embryos collected from cages of wild type ( CS ) flies , using the NaDodSO4/phenol technique [63] . Five µg of oligo-dT selected polyA+ RNA was used in northern analyses and hybridized with radiolabeled fragments corresponding to y ( a ClaI-BglII fragment , representing +2466 to +4815 relative to the yTSS ) , yar ( EST DN154052 , 418 bp ) and ac ( a PCR fragment representing +115 to +531 relative to the acTSS ) . Hybridization with sequences corresponding to the ribosomal gene , RpL32 , served as a loading control . For real-time PCR experiments , RNA was isolated from embryos and pupae from three lines: CS , yΔ1A-2 line XGL339-23-38 , yΔ1A-2/Δ1A-2′ line XGL426-41-4 . RNA isolation and real-time PCR analyses were performed as described in [16] . PCR primers amplified 100–200 bp fragments . y primers flanked the intron . yar primers were in the invariant fourth exon , to ensure quantification of all transcripts . Primer sequences are available upon request . Duplicate or triplicate reactions were performed and averaged , with the difference among the replicates no greater than 0 . 5 cycle threshold ( CT ) . At least three independent experiments were performed for each primer set from two independent RNA samples . The expression level of each gene was determined using Ras64B as an internal control ( ΔCT ) . The fold change in expression of each gene relative to the wild type ( CS ) value was determined with the ΔΔCT method .
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Insulators are conserved genomic elements that define domains of independent transcription . One class of insulators in the Drosophila genome are defined by the binding of the Su ( Hw ) protein , with the gypsy insulator representing the classic Su ( Hw ) -dependent insulator . Su ( Hw ) associates with hundreds of non-gypsy regions distributed throughout the genome that differ in sequence and organization from the gypsy insulator . To gain insights into the role of Su ( Hw ) in genome organization , we defined the properties of the first non-gypsy Su ( Hw ) binding region identified , 1A-2 . Our studies reveal differences in 1A-2 activity , depending on the context tested . We show that 1A-2 is an insulator in enhancer blocking studies but functions as a transcriptional activator within the natural genomic location . Our findings are reminiscent of properties of binding regions that associate with the vertebrate CTCF protein , which have defined insulator , activator , and repressor functions . Finally , our studies indicate that a noncoding RNA gene may contribute to independent transcriptional regulation in the genome .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"molecular",
"biology/transcription",
"initiation",
"and",
"activation",
"genetics",
"and",
"genomics/gene",
"expression",
"genetics",
"and",
"genomics/functional",
"genomics",
"genetics",
"and",
"genomics/nuclear",
"structure",
"and",
"function",
"molecular",
"biology/chromosome",
"structure",
"genetics",
"and",
"genomics/gene",
"function",
"biochemistry/transcription",
"and",
"translation",
"molecular",
"biology",
"genetics",
"and",
"genomics"
] |
2008
|
Context Differences Reveal Insulator and Activator Functions of a Su(Hw) Binding Region
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Binary cell fate decisions allow the production of distinct sister neurons from an intermediate precursor . Neurons are further diversified based on the birth order of intermediate precursors . Here we examined the interplay between binary cell fate and birth-order-dependent temporal fate in the Drosophila lateral antennal lobe ( lAL ) neuronal lineage . Single-cell mapping of the lAL lineage by twin-spot mosaic analysis with repressible cell markers ( ts-MARCM ) revealed that projection neurons ( PNs ) and local interneurons ( LNs ) are made in pairs through binary fate decisions . Forty-five types of PNs innervating distinct brain regions arise in a stereotyped sequence; however , the PNs with similar morphologies are not necessarily born in a contiguous window . The LNs are morphologically less diverse than the PNs , and the sequential morphogenetic changes in the two pairs occur independently . Sanpodo-dependent Notch activity promotes and patterns the LN fates . By contrast , Notch diversifies PN temporal fates in a Sanpodo-dispensable manner . These pleiotropic Notch actions underlie the differential temporal fate specification of twin neurons produced by common precursors within a lineage , possibly by modulating postmitotic neurons' responses to Notch-independent transcriptional cascades .
The computing power of a brain is rooted in its complex neural network , composed of numerous types of neurons . Understanding how diverse neurons are specified is fundamental for elucidating how such an intricate organ develops and evolves from simple to higher organisms . Drosophila melanogaster has a relatively tractable neural development , study of which has revealed multiple mechanisms that act in sequence to diversify neuron fates [1] . To determine the interplay among serial fating mechanisms is critical for unraveling how the large repertoire of neural fates can be reliably established to make a functional brain . Neurons in the Drosophila central nervous system ( CNS ) arise from a stereotyped set of neural progenitors called neuroblasts ( NBs ) [2] , [3] . Each NB generates a lineage of neurons through multiple rounds of self-renewing asymmetric cell divisions . In most divisions , one NB deposits a ganglion mother cell ( GMC ) that divides once to produce two neurons [4] , [5] . Three known mechanisms underlie neuronal diversification through the protracted process of neurogenesis . ( 1 ) The acquisition of lineage identity by each NB occurs during early spatial patterning and governs the neural types it produces [6] . ( 2 ) The specification of temporal identity within a given lineage underlies the orderly derivation of distinct neurons from a common progenitor [7] , [8] . ( 3 ) The binary cell fate decision distinguishes fate between sister neurons made by a single GMC [9]–[14] . Although much has been learned about each of the neuronal diversification processes , scientists have just begun to elucidate how these serial fating mechanisms are integrated to determine a neuron's terminal fate . A combinatorial expression of various transcription factors may confer lineage identity based on where the NBs originate in early embryos [6] , [15]–[21] . By contrast , a generic temporal fating mechanism has been shown to govern birth order/time-dependent neuron fate specification in diverse neuronal lineages [7] , [8] . It involves a series of transcription factors that express in sequence in the NBs . Each of these transcription factors dictates the temporal identity of the neurons born during the time of its expression [22] . However , distinct lineages show different lineage-characteristic temporal identity profiles , arguing for a role of lineage identity in patterning the expression of temporal factors . In fact , recent studies on the Drosophila embryonic NB lineage 5–6 have demonstrated that lineage determinants and temporal fating factors do not simply work additively to specify a final neuron fate . Instead , lineage identity genes may refine neuronal temporal fates by subdividing the temporal window defined by a single temporal identity factor into multiple subdomains with distinct transcriptional outputs [23] . As to the binary cell fate decision in postmitotic neurons , it remains unclear how the transition of the temporal code of the NB and GMC precursors is differentially read out based on Notch activity . Do sister neurons made by the same set of GMCs in a given lineage alter temporal identity simultaneously ? If not , what mechanisms underlie the differential patterning of temporal cell fates between the Notch-on neurons and their Notch-off sibs ? Notch/Numb has been shown to specify A/B binary cell fates of twin neurons derived from a GMC [13] , [14] . Such binary fate decision underlies the initial production of two distinct sets of progeny in most , if not all , Drosophila neuronal lineages . However , many CNS lineages exist as a lone hemilineage because one entire hemilineage has undergone premature cell death [24]–[26] . For instance , two of the three antennal lobe ( AL ) lineages , which make projection neurons ( PNs ) connecting the AL to the lateral horn ( LH ) , yield only one viable neuron from each GMC . Notably , Notch-off specifies the PN fates and Notch-on promotes apoptosis in the anterodorsal PN ( adPN ) lineage but vice versa in the ventral PN ( vPN ) lineage [24] . Mapping ( delineating the serially derived neurons based on the GMC birth order ) the adPN lineage has revealed 40 types of AL PNs that arise in an invariant sequence from the progenitor of the lineage [27] . Unfortunately , it is not possible to discern birth time/order-dependent fate changes among their apoptotic sibs , preventing comparative analysis of temporal fate transitions between sister hemilineages . By contrast , the lAL lineage produces PNs as well as AL local interneurons ( LNs ) , which can be interconverted by manipulating Notch activities [24] , [28] . Identifying each PN and LN and determining their twin relationship in the lAL lineage should allow a close examination of neuron fate specification based on the interplay between temporal identity and binary fate decision . Here we determined the twin neurons made by each GMC of the larval lAL lineage , using twin-spot mosaic analysis with repressible cell markers ( ts-MARCM ) that permits labeling of sister clones ( e . g . , twin neurons ) derived from a common precursor ( e . g . , a GMC ) in distinct colors [26] . We demonstrated that the lAL lineage consists of two distinct hemilineages that yield a PN and LN pair from each GMC at early times and a single PN at the end of the lineage . Stereotyped PN and LN twin clones were consistently observed at specific time points . Notably , PNs exhibit higher morphological diversity and thus alter temporal fates that govern morphogenesis in a faster tempo than their LN sibs . Additional lines of evidence indicate that the PN and LN offspring of the lAL lineage are differentially patterned with respect to their temporal identity . Interestingly , knocking out Sanpodo ( Spdo ) , a positive regulator of Notch , from the lAL NB led to duplication of the entire complement of PNs at the expense of less dynamic LNs . This implies that twin neurons are born with equivalent temporal codes , which may specify different temporal fates depending on Notch activities . We further uncovered a spdo-independent role of Notch in specifying a set of temporal fates in the PN hemilineage . Despite the complex binary and temporal fate transformations , Notch mutant clones maintained the normal dynamic expressions of Chronologically inappropriate morphogenesis ( Chinmo ) [29] , [30] and Broad complex ( Br-C ) [31] during larval development . Although Notch did not regulate chinmo expression , loss of Chinmo affected PN and LN temporal fates in hemilineage-dependent manners , arguing that Notch acts downstream of temporal fating factors to modulate neuronal temporal fates . Taken together , we established the Drosophila lAL lineage as a model system for studying the origin-dependent neuron fate specification and demonstrated that Notch not only underlies binary cell fate decision but also determines temporal fates in both Notch-high and Notch-low sister neurons .
The lateral antennal lobe ( lAL ) lineage yields about 200 neurons during larval neurogenesis [32] . Labeling the lAL progeny by conventional mosaic analysis with a repressible cell marker ( MARCM ) [33] using a pan-neural nSyb-GAL4 revealed neuronal cell bodies packed along the lateral border of the AL . They elaborate densely in the antennal lobe ( AL ) and the neighboring antennal mechanosensory and motor center ( AMMC ) ( Figure 1A ) and further innervate the inferior ventrolateral protocerebrum ( IVLP ) , lateral horn ( LH ) , superior medial protocerebrum ( SMP ) , and some other brain regions ( Figure 1A ) . It is not possible to determine the detailed “projectome” among the targets without single-neuron labeling . To reveal single-cell morphology and simultaneously determine the neuron birth order , we “sequenced” the larval lAL lineage using ts-MARCM [26] with nSyb-GAL4 . We determined ganglion mother cell ( GMC ) progeny born in 2-h windows throughout larval development ( see Materials and Methods ) . We identified lAL GMC clones based on cell body positions and neurite trajectory patterns that match the lAL NB clones generated at various time points ( unpublished data ) . Except near the lineage end ( see below ) , both daughter neurons derived from each lAL GMC survived into the adult stage . Notably , one projection neuron ( PN ) consistently paired with one local interneuron ( LN ) . They exist as twin clones when differentially labeled by ts-MARCM ( Figure 1B ) . This confirms the previous hypothesis that the lAL lineage is composed of one PN hemilineage and one LN hemilineage [24] , [28] , [32] . Moreover , we obtained neuron pairs with distinct characteristic morphologies following clone induction at different developmental times , indicating that the birth order of GMCs has governed neuronal diversification in the protracted lAL lineage ( Figure 1B; see below ) . The lAL PNs identified by ts-MARCM can be categorized into five classes based on their morphology: monoglomerular PN ( mPN ) , unilateral PN ( unPN ) , bilateral PN ( biPN ) , AMMC PN , and suboesophageal ganglion ( SOG ) PN ( Figure 2 ) . mPNs connect a single AL glomerulus to the mushroom body ( MB ) calyx and LH through the inner antennocerebral tract ( iACT; Figure 1A ) [34] , [35] . The mPNs target the VA4 , VC2 , VC1 , DM1 , DM2 , VA5 , VA7m , DA1 , DL3 , VM1 , DA2 , or DM5 AL glomerulus ( Figure 2 ) and have been determined previously based on the GAL4-GH146 marker [36] , [37] . The lack of additional mPNs using the more broadly expressed nSyb marker suggests this set was already complete . Unlike mPNs , unPNs and biPNs connect the AL ( s ) to various brain regions not yet implicated in olfaction , which include the posteriorlateral protocerebrum ( PLP ) , inferior ventrolateral protocerebrum ( IVLP ) , and superior medial protocerebrum ( SMP ) . unPNs restrict their proximal elaborations to the ipsilateral AL , whereas biPNs show bilateral AL elaborations . Eight types of unPNs and six types of biPNs can be further distinguished based on ( 1 ) AL innervation patterns , ( 2 ) neurite trajectories , and ( 3 ) distal targets ( Figure 2; see Table S1 for details ) . In addition to the AL PNs , we obtained 16 types of AMMC neurons and three types of SOG neurons that may account for the AMMC and SOG elaborations seen in the lAL NB clones ( Figure 2 , compared to Figure 1A ) . Most of the AMMC neurons acquire some bilateral elaborations across the brain midline . AMMC-1 to -11 connect the ipsilateral AMMC to the ipsilateral as well as contralateral IVLPs or posterior ventrolateral protocerebrum ( PVLP ) ( AMMC-1 to -8 ) , or only to the contralateral IVLP/PVLP ( AMMC-9 to -11 ) . AMMC-12 and -13 elaborate exclusively within the AMMC and wire the paired AMMC structures together . AMMC-14 to -16 show dendrite-like processes in the IVLP and axon-like projections in the AMMC , but AMMC-14 only targets the ipsilateral AMMC whereas AMMC-15 and -16 innervate both ipsilateral and contralateral AMMCs . Finally , the three types of SOG PNs show unique characteristic patterns of proximal elaboration in the SOG and further target distinct brain regions , including the PLP ( SOG-1 ) , the contralateral and ipsilateral clamp surrounding the MB peduncles ( SOG-2 ) , and the ipsilateral clamp and inferior bridge ( IB ) ( SOG-3 ) . Some proximal neurites of SOG-3 further innervate the vest , which is posterior to the AL . Please refer to Table S1 for more detailed description of these stereotyped AMMC and SOG neurons . In sum , the lAL NB yields not only AL PNs but also AMMC and SOG neurons , which may contribute to distinct neural circuits ( see Discussion ) . Does the GMC birth order guide the derivation of these multiclass neurons one group by another along the Notch-off hemilineage of the complex lAL pedigree [24] , [28] ? The twin single-cell clones collected for this study were induced in discrete 2-h windows to sample neurons born at different times from larval hatching to puparium formation . Notably , distinct lAL PNs were preferentially hit at different developmental times . To deduce their possible birth order , we attempted to arrange the identified lAL PN types chronologically based on when their precursors are susceptible to mitotic recombination . We first determined the primary window ( s ) of susceptibility for each lAL PN type ( shaded boxes in Figure 3A; boxes that account for less than 10% or less of the hits at the respective timing of clone induction are not shaded , except for rarely hit neuron types , including AMMC-9 , and AMMC-15 ) . All but two of the 45 identifiable PN types show a single narrow window of susceptibility that staggers in partially overlapping manners along the ∼120 h of larval development . A tentative PN birth order can then be deduced based on the starts and/or ends of the susceptible windows as well as their prime times of appearance ( Figure 3A ) . We also determined the sequence of birth for the mPNs through analysis of GAL4-GH146-labeled NB clones ( Figure 3B–M″ ) . We witnessed a sequential loss of the 12 glomerular targets from the NB clones of reducing sizes . As to their paired GMC clones , we observed the serial appearance of the VA4 , VC2 , VC1 , DM1 , DM2 , VA5 , and VA7m mPNs as they sequentially disappeared from the NB clones of reducing sizes ( Figure 3B–H″ ) . Then some DA1 mPNs were hit before the birth of DL3 mPNs , and additional DA1 mPNs arose later with the NB clones lacking DL3 mPNs ( Figure 3I–K″ ) . The remaining VM1 , DA2 , and DM5 mPNs then followed in the same sequence as they disappeared from the NB clones ( Figure 3L–M″ ) . In addition , certain NB clones apparently paired with GH146-negative progeny and existed alone when labeled with GAL4-GH146 ( unpublished data ) . Ignoring those gaps , we derived the following birth sequence for the 12 types of lAL mPNs: VA4-VC2-VC1-DM1-DM2-VA5-VA7m-DA1-DL3-DA1-VM1-DA2-DM4 . The same birth order was obtained from the analysis of nSyb-GAL4-labeled single-cell clones ( Figure 3A ) . Notably , mapping the lAL lineage using a ubiquitous driver , like nSyb-GAL4 , and through analysis of numerous serially derived single-cell clones ( Figure 3A ) , further allowed us to ( 1 ) fill the gaps occupied by GH146-negative PNs , ( 2 ) resolve the mixing of DA1/DL3 mPNs , and ( 3 ) uncover the paired LNs ( see below ) . The complete birth order of larval-derived lAL PNs unveils several interesting points . First , distinct PNs are born in an invariant sequence . Second , different PN classes are born in an intercalated sequence with analogous PN types arising in separate windows . For example , the 12 mPN types derive in nine blocks that span nearly two-thirds of the larval development . During the same period of time , 14 other PN types , including 10 types of AMMC neurons , are made . Six additional AMMC types plus three types of atypical AL PNs are derived afterwards . In contrast with the late AMMC siblings , the majority of atypical AL PNs and all the SOG neurons are born prior to the mPN-producing windows . Third , the apparently arbitrary birth order is further complicated by the recurrent production of DA1 and DL3 mPNs . They are first born from 46 to 58 h after larval hatching and are also generated roughly 12 h later ( Figure 3A ) . DA1 mPNs precedes DL3 mPNs during their initial contiguous production . By contrast , DL3 mPNs arise before DA1 mPNs in their second round of birth that is further separated by the production of two types of AMMC neurons . The early-born DA1/DL3 and later-derived DA1/DL3 mPNs are morphologically indistinguishable and are both positive for GAL4-GH146 . Nonetheless , the DA1/DL3 mPNs born at different times pair with distinct LNs , and the early-born DA1 mPNs can be further divided into two groups based on their paired LNs ( Figure 3A; see below ) . Taken together , the lAL NB makes distinct PNs of diverse classes in a fixed arbitrary sequence . Neurons acquire specific fates based on their birth order , but the actual sequence of production reveals no obvious logic behind their stereotyped temporal deployment . Analogous neurons can arise at different times across the protracted lineage . Moreover , identical neurons can be born consistently in two waves . To uncover the genes that determine specific neuron classes versus the fates within a class will be critical for elucidating the molecular mechanisms underlying such orderly , but not class-by-class , production of distinct neuronal siblings . Besides PNs , the lAL lineage yields LNs . For most of the lineage , PNs and LNs were made in pairs , as the mitotic recombination during GMC divisions consistently led to the labeling of one PN paired with one LN by ts-MARCM ( Figure 4 ) . However , the final nine PN types were not paired with another neuron or a NB clone ( Figure 4 ) . This indicates that either the paired cell died or could not be labeled with nSyb-GAL4 . Notably , the longer PN hemilineage exhibits higher morphological diversity than its LN sister hemilineage . First , unlike PNs that innervate brain regions involved in multiple sensory modalities , their paired LNs exclusively innervate the ALs and should be selectively involved in olfaction . Second , many distinct PNs were paired with indistinguishable LNs . Nonetheless , the LNs can be grouped into four classes based on the extent of their AL elaborations . The pan-AL LNs densely innervate all the glomeruli in the AL; the lavish LNs occupy most , but not all , AL glomeruli; the patchy LNs invade many glomeruli in spotty patterns; the sparse LNs , by contrast , arborize locally within a few glomeruli ( Figure 5A–D ) . Notably , except for the DA1 and DL3 mPNs , PNs of a given type consistently pair with a particular class of LNs . The DA1 mPNs may be born with lavish , patchy , or sparse LNs , and the DL3 mPNs can pair with patchy or sparse LNs . By contrast , the remaining 43 PN types show strict sisterhood with one of the four LN classes . Taking both PN and LN diversities into consideration , we have in total recovered 48 distinct PN/LN pairs ( Figure 4 ) that arise sequentially from the lAL lineage as implicated from the invariant birth order of the PNs ( Figure 3A ) . For those five PN/LN pairs ( referred to as DA1/lavish , DA1/patchy , DA1/sparse , DL3/patchy , and DL3/sparse , respectively ) whose distinction depends on the LN diversity , we refined the PN grouping and determined the subgroups' windows of production . We found that DA1/lavish , DA1/patchy , and DL3/patchy are born earlier in a contiguous sequence and that DL3/sparse and DA1/sparse are born later in separate windows ( Figure 3A ) . When these 48 recognizable PN/LN pairs were chronologically arranged based on the derived birth order ( Figure 4 ) , we noticed that , unlike PNs , the AL LNs of different classes have arisen in a more logical sequence with most pan-AL LNs ( Figure 4A–D , F , G ) born before the lavish LNs ( Figure 4E , H–Y , AC–AD ) , which largely precede the patchy LNs ( Figure 4Z–AB ) and ultimately transit to the sparse LNs ( Figure 4AE–AM ) . The pan-AL LNs paired with distinct PNs are morphologically indistinguishable from one another . They show analogous electrophysiological profiles [38] , further indicating the homogeneity of the pan-AL class of LNs . How about the other three classes of LNs ? Notably , the lavish or sparse LNs that associate with a particular PN type ( thus born in a specific developmental time window ) tend to avoid or innervate a characteristic set of AL glomeruli . To examine the LN diversity in further detail , we computed the average AL elaboration pattern of the LNs for each of the 48 sequentially derived PN/LN pairs . We manually annotated individual LNs' glomerular innervation patterns and then calculated the percentage of LNs , for a given PN/LN-pair type , whose neurites could be found within a particular glomerulus ( Figure 5E ) . A uniform full pattern of elaboration was ascertained in the pan-AL LNs paired with distinct PNs ( Figure 5 ) . By contrast , the patchy LNs innervate various glomeruli stochastically and may jointly tile the entire AL , as they collectively show a low-penetrant targeting to nearly all the AL glomeruli within any of the three PN/LN groups that carry patchy LNs ( Figure 5 ) . Unlike the pan-AL and patchy LNs , the lavish as well as sparse LNs exhibit discriminative patterns of elaboration depending on the identity of the associated PNs . The lavish LNs selectively avoid certain glomeruli , while the sparse LNs preferentially innervate specific glomeruli ( Figure 5 ) . The stereotyped patterns of AL glomerular innervation observed in the LNs , paired with distinct PNs and born at specific developmental times , argue for the presence of distinct types of lavish and sparse LNs . This is distinct from the lack of discernible cellular diversity among the pan-AL or patchy LNs . Using the glomerular innervation frequencies to represent the LNs associated with a particular PN type and arranging them chronologically based on the deduced PN birth order revealed that the PN and LN hemilineages alter temporal identity independently . The PN hemilineage is longer and yields many more morphologically distinct neurons than the LN hemilineage . In addition , contrasting with PNs that arise in a rather complex sequence , the four LN classes are produced roughly in the order of pan-AL→lavish→patchy→sparse ( Figures 4 and 5E ) . During the production of the relatively homogeneous pools of pan-AL or patchy LNs , we witnessed multiple unilateral temporal fate changes in the PN hemilineage ( Figure 5E ) . As to the lavish and sparse LNs that exhibit morphological subtypes , we found that LNs showing indistinguishable AL elaboration patterns are born in contiguous blocks that yield distinct PNs ( Figure 5E ) . These observations collectively indicate that LNs alter temporal identity ( that controls morphogenesis ) at a slower tempo than PNs do , although they are derived from the same GMCs . Despite the presence of fewer LN fate transitions , the lavish-to-patchy LN fate switch consistently occurs without a concomitant PN fate change . It subdivides the window of DA1 mPN neurogenesis into two blocks that differ only on the LN side ( Figures 3A , 4Y–Z , and 5E ) . Taken together , PNs and LNs undergo independent temporal identity changes . The independent PN/LN temporal fate specification is further evidenced by two unilateral PN fate duplications . The DA1 and DL3 mPNs were initially made at 46 to 58 h after larval hatching ( ALH ) paired with lavish or patch LNs . After that , the lAL NB switched to produce AMMC PNs paired with various LNs . Notably , around 70 to 84 h ALH , the lAL lineage yielded additional DL3 and DA1 mPNs in reverse birth-order and associated with sparse LNs ( Figures 3A and 4Y , Z , AF , AI ) . These phenomena collectively suggest that neuronal terminal fates are determined in hemilineage-specific manners . It is hard to image how the temporal fates of twin neurons can be differentially patterned , given that neuronal temporal identities are presumably conferred in the precursors by a set of sequentially and transiently expressed transcription factors [8] , [22] . However , we have learned that the PN versus LN binary cell fates are determined through differential Notch signaling due to asymmetric segregation of Numb [24] , [28] . We wondered if Notch merely specifies PN/LN binary fates or it also governs the differential patterning of PN and LN temporal fates . LNs were grossly transformed into PNs in the lAL NB clones that lacked Sanpodo ( Spdo ) ( see below ) , a positive regulator of Notch [12] , [39] , [40] . Analyzing the temporal fates for those PNs transformed from LNs due to loss of Notch should help elucidate the role ( s ) of Notch in specifying PN versus LN temporal fates . We examined the PN composition of the PN-only spdo mutant lAL NB clones . We selectively marked the 12 types of mPNs , born in multiple clusters from 18 to 96 h ALH , with GAL4-GH146 . We further checked distinct populations of AMMC neurons using GAL4-GR20C03 and GAL4-GR72G12 . We found that the spdo mutant lAL NB clones , labeled with any of the three GAL4 drivers , show wild-type morphologies but carry two times more cell bodies ( Figure 6 ) . These observations indicate a perfect duplication of the PN hemilineage in the spdo mutant clones and suggest that the transformed PN hemilineage undergoes the same temporal identity changes as the native PN hemilineage does . Such results argue that the differential Notch signaling not only promotes the LN or PN fate but also governs the differential manifestation of temporal identity changes in the LN versus PN hemilineage . In contrast with the faithful duplication of diverse PNs in the spdo mutant clones , the lAL NB clones homozygous for mutations in notch or its co-activator Su ( H ) exhibited abnormal PN compositions . Labeling entire clones with nSyb-GAL4 revealed missing of the AMMC neurite tracks specifically in the notch or Su ( H ) mutant NB clones ( Figure 7C , D , compared to Figure 7A , B ) . There was no evidence for cell loss , given that we consistently counted around 200 cell bodies regardless of the clone genotype . To exclude changes in the pattern of lAL neurogenesis , we further determined the rate of proliferation at 30 h ALH when the lAL NB mainly produces mPNs and at 70 h ALH when the AMMC neurons are made . The sizes of wild-type and Su ( H ) clones were comparable . Moreover , they carried analogous numbers of mitotic cells ( Table S2 ) as revealed with the mitosis marker phospho-histone H3 ( PH3 ) [41] . So the PN-only notch and Su ( H ) mutant clones have made GMCs that yield viable neurons in correct numbers and at right timings , making us wonder if the prospective AMMC neurons have adopted other PN fates and acquired non-AMMC neurite trajectories . Given the prominence of AL neuronal elaborations in those clones lacking AMMC trajectories , we examined if the notch and Su ( H ) mutant NB clones carry many more AL PNs at the expense of AMMC neurons . We found that notch mutant lAL NB clones contain about five times more GH146-positive AL neurons than wild-type controls ( Figure 7E , compared to Figure 6A ) . A three times increase in the numbers of the later-born DA1 , DL3 , VM1 , DA2 , and DM5 mPNs , visualized with GAL4-GR83D12 , was also observed in Su ( H ) mutant clones ( Figure 7F ) . Note the exclusive dense innervation of the DA1 , DL3 , VM1 , DA2 , and DM5 glomeruli by the much enlarged Su ( H ) mutant clones ( Figure 7F ) , indicating an excessive production of normal-looking AL PNs by the lAL NB deficit in notch or Su ( H ) . These observations suggest that the prospective AMMC neurons of notch/Su ( H ) mutant clones might have aberrantly adopted the AL PN fates characteristic of siblings born at different times , reminiscent of some temporal cell fate transformation . The majority of AMMC neurons are born after 60 h ALH ( Figure 7G ) . If the prospective AMMC neurons had been transformed into AL PNs , one would expect that the supernumerary AL PNs were largely added during the second half of the lAL lineage . To verify this viewpoint , we examined when the GH146-positive mPNs were made in excess by the notch mutant lAL NB . We fed the larvae harboring GAL4-GH146-labeled wild-type or notch clones with EdU , a thymidine analog that labels proliferating cells , for 1 d at 0–24 , 24–48 , or 48–72 h ALH ( Figure 7G ) . The pulse labeling of EdU first confirmed that the GH146-positive mPNs were mostly generated between 24 and 72 h ALH ( Figure 7H ) . It further revealed that the majority of the excessive GH146-positive neurons in the notch mutant lAL NB clones were born after 48 h ALH when the prospective AMMC neurons were supposed to arise . Compared to wild-type controls , notch mutant clones yielded two times more GH146-positive neurons at 24–48 h ALH and up to four times more at 48–72 h ALH ( Figure 7H ) . This increase was not due to an acceleration of NB proliferation , because the total numbers of the EdU-positive cells on the lateral side of the AL remained comparable to those of the wild-type controls ( Figure 7I–L ) . And the 4-fold increase at 48–72 h ALH cannot be fully accounted for by the LN-to-PN fate changes . It argues instead that , on top of the binary cell fate transformation , most , if not all , of the PNs yielded during that period , including those that normally adopt the AMMC neuronal fates , have uniformly developed into GH146-positive mPNs . In sum , Notch signaling underlies the specification of AMMC versus AL neurons in the Notch-low PN hemilineage . Interestingly , the positive regulator of Notch , Spdo , is essential for the binary cell fate decision between LNs and PNs but dispensable for the temporal fate specification of the AMMC versus AL PN fates . Notch might regulate neuronal temporal cell fates through refining temporal codes or modulating postmitotic neurons' responses to Notch-independent transcriptional cascades . Chinmo and Br-C are dynamically expressed during larval neurogenesis [30] , [31] . We wondered if such dynamic gene expressions exist in the developing lAL lineage and whether these temporal signatures vary depending on Notch activities . Consistent with previous reports [31] , we could reliably detect a sequential birth-order-dependent expression of Chinmo and Br-C in the neuronal offspring of most , if not all , larval brain NBs . Chinmo preceded Br-C in the partially overlapping temporal gene expression , such that Chinmo ( + ) /Br-C ( − ) neurons consistently reside deeper in the cell body layer than their Chinmo ( − ) /Br-C ( + ) siblings ( Figure 8A , B ) . We quantified the lAL offspring positive for Chinmo and/or Br-C at 70 h ALH when many AMMC precursors should already exist . We obtained comparable numbers of Chinmo ( + ) /Br-C ( − ) , Chinmo ( + ) /Br-C ( + ) , and Chinmo ( − ) /Br-C ( + ) neurons in the lAL NB clones regardless of the genotype of spdo or Su ( H ) ( Figure 8C ) . We conclude that the Chinmo→Br-C temporal expression takes place analogously in both PN and LN hemilineages and independently of Notch activities . We further examined the involvement of Chinmo in specifying neuronal temporal fates of PNs versus LNs . Using GAL4-GH146 to monitor the orderly production of the 12 types of mPNs with ts-MARCM , we demonstrated the requirement of Chinmo for proper specification of the VC2 , VC1 , DM1 , and DM2 temporal fates ( Figure 9A ) . All of them have aberrantly adopted the VA5 temporal fate following loss of Chinmo from respective GMCs , as evidenced by their targeting of the VA5 glomerulus and the branching of axons reminiscent of the wild-type VA5 mPNs ( Figure 9B–G for VC2; unpublished data for VC1 , DM1 , and DM2 ) . We then examined Chinmo's requirement for their twin LNs . We created mutant LNs paired with wild-type PNs as isolated two-cell clones . Based on AL elaboration patterns , the chinmo mutant LN of the VC2 mPNs ( LN2 ) has adopted the fate of LN3 ( the twin LN of the VC1 mPN ) rather than the fate of LN6 ( the twin LN of the VA5 mPN ) ( Figure 9A ) . Compared to the wild-type LN2 innervating near all AL glomeruli ( Figure 9H ) , the prospective LN2 homozygous for chinmo acquired a much more restricted pattern of neurite elaboration and resembled the next-born LN3 ( Figure 9I , J ) . The transformed LN2 appears distinct from LN6 that normally pairs with the VA5 mPN ( Figure 9K ) , although the chinmo−/− VC2 mPN has consistently adopted the VA5 mPN fate ( Figure 9A–G ) . We did not observe chinmo-related temporal identity phenotypes for other LNs examined so far . Taken together , we identified chinmo as a temporal fating factor in the lAL lineage . Notably , the Notch-independent dynamic expression of Chinmo governs LN and PN temporal fates in hemilineage-specific ( i . e . , Notch-dependent ) manners , arguing that Notch acts in parallel with or downstream of temporal fating factors to determine terminal temporal fates ( Figure 9L ) .
Detailed analysis of the lateral antennal lobe ( lAL ) lineage attests to the stereotypy of clonal development in the Drosophila central brain , discloses novel types of antennal lobe ( AL ) neurons as well as neurons that innervate other brain regions , and exemplifies how diverse neurons of different classes can derive from a common progenitor . The lAL neuroblast ( NB ) gives rise to a rather heterogeneous population of neurons , which is achieved through the derivation of two distinct hemilineages that yield projection neurons ( PNs ) and local interneurons ( LNs ) , respectively . The LN hemilineage produces LNs exclusively for the AL , while the PN hemilineage generates not only AL PNs but also PNs of the antennal mechanosensory and motor center ( AMMC ) and suboesophageal ganglion ( SOG ) . Furthermore , the paired hemilineages yield diverse PNs and LNs concurrently but in distinct temporal patterns . Various neurons of different LN classes are made one class after another . By contrast , distinct PNs arise in a complex intercalated sequence . Given that most Drosophila neuronal lineages ( possibly all except the MB lineages ) consist of two distinct hemilineages or exist as a lone hemilineage [25] , [26] , neural development and neuronal diversification appear to be orchestrated along hemilineages instead . This suggests that understanding hemilineage identity will clarify a central organizational theme in Drosophila brain development . Interestingly , Notch governs hemilineage identity and further patterns the hemilineage-characteristic temporal fate changes . By lineage mapping using ts-MARCM and through analysis of sanpodo ( spdo ) mutant clones , we confirm that the lAL lineage is made up of a Notch-high LN hemilineage and a Notch-low PN hemilineage . Despite their derivation from common GMCs , PNs and LNs undergo temporal fate changes independently . The lAL PNs exhibit higher cellular diversity and thus alter their temporal fates more frequently than their LN sibs do . However , there are also developmental periods when one LN interclass fate switch consistently occurs during the continuous production of a particular PN type . Notably , knocking down spdo through the lAL lineage development has resulted in duplication of the entire PN hemilineage . This indicates that the prospective LNs have been transformed into PNs with correct PN temporal fates . It argues that twin neurons are born with identical temporal fating factors and that the Spdo-dependent Notch activity has not only promoted the LN fate but also governed the birth time/order-dependent neuronal diversification in the LN hemilineage . And Notch mediates cell fate decision between LNs and PNs as well as within the Notch-low PN hemilineage where Notch acts in a Spdo-dispensable manner to promote the AMMC PN fates as opposed to the AL PN fates ( Figure 9L ) . In the PN-only Notch or Su ( H ) , but not spdo , mutant lAL NB clones , the prospective AMMC neurons aberrantly adopted various AL PN fates . Diverse AMMC neurons and distinct AL PNs normally arise in alternative blocks . Regardless of the AMMC-to-AL fate transformation , the overall temporal patterning appeared intact in the AMMC-lacking PN hemilineages as evidenced by comparable increases in the AL PNs of various types ( Figure 7 ) . These observations suggest that Notch is not involved in the regulation of GMC temporal identity but rather diversifies PN temporal fates after birth of postmitotic neurons . At this stage , we are still naïve about the nature of such Spdo-independent Notch signaling or the sources of the dynamics that underlie the alternation of AMMC and AL PN fates . Two mechanisms could underlie the Notch-dependent temporal fate specification of both PNs and LNs ( Figure 9L′ , L″ ) . First , Notch High or Low may differentially modulate the refinement of temporal fating factors in the newborn neurons . Lineage identity genes have been shown to participate in subpatterning of temporal cell fates in the NB 5–6 lineage [23] . It is possible that terminal identity genes are established in postmitotic neurons through a combined action of lineage determinants , GMCs' temporal identity factors and Notch signaling ( Figure 9L′ ) . Second , Notch targets may modulate neuronal responses to common temporal codes . Notably , the birth-order-dependent expressions of Chinmo and Br-C in the lAL offspring were well maintained even when loss of Notch signaling had elicited complex binary and temporal fate transformations . And the Notch-independent dynamic expression of Chinmo governed both PN and LN temporal fates but in hemilineage-specific manners . These observations imply that Notch acts downstream of temporal fating factors to regulate neuronal temporal fates potentially through some epigenetic mechanisms ( Figure 9L″ ) . As to the neuronal details and their possible functions , the lAL lineage yields diverse classes of AL LNs and PNs , many distinct AMMC neurons , and a small number of SOG PNs , which may contribute to the processing of various sensory inputs . Beside the 12 types of well-characterized monoglomerular PNs ( mPNs ) that connect a single glomerulus of the AL to mushroom body ( MB ) calyx and lateral horn ( LH ) [34] , [35] , we identified eight types of unilateral PN ( unPN ) and six types of bilateral PN ( biPN ) . The unPNs have proximal elaboration in the ipsilateral AL and biPNs have that in both ipsilateral and contralateral AL . Interestingly , unPNs and biPNs often connect AL to brain regions that have not been shown to be involved in olfaction , such as posteriorlateral protocerebrum ( PLP ) , superior medial protocerebrum ( SMP ) , inferior ventrolateral protocerebrum ( IVLP ) , and crepine ( CRE ) ( Figure S1 ) . In addition to these putative olfactory neurons , there are 16 types of AMMC PNs and three types of SOG PNs in the lAL lineage . The SOG PNs have proximal innervation in suboesophageal ganglion ( SOG ) , the primary target for the gustatory receptor neurons [42] , and therefore are candidate downstream neurons in the gustatory processing neural circuit . The AMMC PNs have primary innervations in the antennal mechanosensory and motor center ( AMMC ) , which have been shown to be important for hearing and gravity-sensing [43] . The AMMC PNs therefore might be part of the auditory/gravity-sensing circuit [43] , [44] . Notably , like many AL PNs , most AMMC PNs have axon-like projection into IVLP ( Figure S1 ) . Such convergence makes IVLP a potential integration site for various inputs . The production of diverse PNs from a single progenitor further suggests a possible evolution of distinct networks from a common ancestral circuit . In sum , the lAL NB makes multiple classes of diverse neurons in a complex yet stereotyped pattern , manifested as a series of LN/PN pairs and orchestrated through distinct Notch activities . The Spdo-dependent Notch action that occurs in the Numb-negative offspring has not only conferred the LN fate but also patterned the LN temporal identities . A novel Spdo-independent Notch action is further utilized to increase the PN temporal fates by promoting AMMC neuronal fates in otherwise AL PNs . Both Notch-mediated temporal fate regulations are apparently executed after proper deployment of temporal fating factors . Taken together , Notch plays integral roles in the derivation of final neuronal temporal cell fates .
The fly strains used in this study include ( 1 ) GAL4-GH146 [45]; ( 2 ) asense-GAL4; ( 3 ) FRT19A , notch[55e11] , UAS-mCD8::GFP; ( 4 ) FRT40A , UAS-mCD8::GFP , UAS-rCD2i , Chinmo[1] , GAL4-GH146/CyO; ( 5 ) hs-FLP[1];FRT40A , UAS-rCD2::RFP , UAS-GFPi; ( 6 ) FRT40A , UAS-mCD8::GFP , UAS-rCD2i;nSyb-GAL4 ( 2-1 ) ; ( 7 ) FRT82B , spdo[27]/TM6B; ( 8 ) 40A , Su ( H ) [delta 47]/CyO [46] , [47]; ( 9 ) FRT19A , hs-FLP[122] , tubp-GAL80;GAL4-GH146; ( 10 ) FRT19A , hs-FLP[1];nSyb-GAL4; ( 11 ) hs-FLP[1];GAL4-GH146;FRT82B , tubp-GAL80; ( 12 ) hs-FLP[1];FRT82B , UAS-rCD2::RFP-UAS-GFPi; and ( 13 ) FRT82B , spdo[27] , UAS-mCD8::GFP-UAS-rCD2i . Larvae 0–2 h old with proper genotype were collected and put into vials ( 80 larvae/vial ) containing standard fly food . The larvae were raised at 25°C until desired stages . To induce clones , the larvae were heat-shocked at 37°C for 15–40 min . After heat shock , the larvae were put back to 25°C until dissection at desired stages . Only male flies were dissected for the detailed lineage analysis of the lAL neurons . Because background olfactory receptor neuron ( ORN ) clones often interfered with the lAL clones in the antennal lobe , we removed antennae 1 d after adult eclosion and waited for 3 d for the ORN axons to degenerate before brain dissection . For the ts-MARCM clones in Figures 1B , 2 , and 4 , the clones of interest inevitably coexist with various background clones due to the use of the pan-neuronal driver nSyb-GAL4 . In such cases , confocal images of the brains containing clones of the same neuron type were carefully compared stack by stack to determine the background clones . The brain with the least background was chosen and the background clones were manually masked to reveal the clone of interest . Larvae 0–2 h old with the genotype of FRT19A , notch[1] , UAS-mCD8::GFP/hs-FLP[122] , FRT19A , tubp-GAL80;GAL4-GH146 , UAS-mCD8::GFP/CyO or FRT19A , UAS-mCD8::GFP/hs-FLP[122] , FRT19A , tubp-GAL80;GAL4-GH146 , UAS-mCD8::GFP/CyO were heat-shocked at 37°C for 1 h to induce MARCM clones . To feed the larvae EdU at 0–24 h ALH , the larvae were transferred into vials ( 100 larvae/vial ) containing standard fly food with 100 µg/ml EdU ( Invitrogen ) for 24 h at 25°C , and then transferred into vials ( 100 larvae/vial ) with standard fly food only until adult eclosion . To feed the larvae EdU at 24–48 h or 48–72 h ALH , the larvae , after heat-shock , were transferred into vials ( 100 larvae/vial ) containing standard fly food for 24 h or 48 h at 25°C . The larvae were then transferred into vials ( 100 larvae/vial ) containing standard fly food with 100 µg/ml EdU for 24 h at 25°C . After the EdU feeding , the larvae were transferred back to the vials with standard fly food and raised at 25°C until adult eclosion . The adult brains were dissected in 1× Phosphate buffered saline ( PBS ) and stained for EdU using Click-iT EdU Alexa Fluor 555 Imaging Kit ( Invitrogen ) . After the EdU staining , the brains were washed three times by 1× PBS with 0 . 75% Triton X-100 ( 0 . 75% PBT; Fisher Scientific ) for 15 min each . The brains were then incubated with rabbit anti-GFP Ab ( 1∶1 , 000; invitrogen ) and mouse nc82 mAb ( 1∶50; DSHB ) at 4°C overnight . Next day , the brains were washed with 0 . 75% PBT three times for 15 min each and incubated with Alexa 488-conjugated goat anti-rabbit ( 1∶200; invitrogen ) and Cy5-conjugated goat anti-mouse secondary antibodies ( 1∶400; Jackson ImmunoResearch ) at 4°C overnight . Next day , the brains were washed with 0 . 75% PBT three times for 15 min each before mounted using SlowFade gold anti-fade reagent ( Invitrogen ) . Fly brains were dissected in 1× PBS , fixed in 1× PBS with 4% formaldehyde ( Fisher Scientific ) at room temperature for 20 min , washed by 1× PBS with 0 . 75% Triton X-100 ( 0 . 75% PBT; Fisher Scientific ) three times for 15 min each , and incubated in 1× PBS with 0 . 5% goat normal serum ( Jackson ImmunoResearch ) for 30 min before incubation with primary antibodies at 4°C overnight . Next day , the brains were washed in 0 . 75% PBT three times for 15 min each before incubated with secondary antibodies at 4°C overnight . Next day , the brains were washed with 0 . 75% PBT for 15 min for three times and mounted using SlowFade gold anti-fade reagent ( Invitrogen ) . The immunofluorescent signals were collected by Zeiss LSM confocal microscope and processed using Fiji and Adobe Photoshop . Primary antibodies used in this study include rat anti-mCD8 mAb ( 1∶100; Caltag ) , mouse nc82 mAb ( 1∶100; DSHB ) , rabbit anti-Dsred ( 1∶500; Clontech ) , mouse anti-Br-C ( core ) ( 1∶100; DSHB ) , rabbit anti-Chinmo ( 1∶1 , 000 ) [30] , rabbit anti-PH3 ( 1∶250; Upstate ) , and rabbit anti-GFP Ab ( 1∶1 , 000; invitrogen ) . The secondary antibodies were Alexa 488-conjugated goat anti-rabbit or goat anti-rat ( 1∶200; invitrogen ) , Cy3-conjugated goat anti-rabbit ( 1∶400; Jackson ImmunoResearch ) , and Cy5-conjugated goat anti-mouse ( 1∶400; Jackson ImmunoResearch ) .
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The Drosophila brain develops from a limited number of neural stem cells that produce a series of ganglion mother cells ( GMCs ) that divide once to produce a pair of neurons in a defined order , termed a neuronal lineage . Here , we provide a detailed lineage map for the neurons derived from the Drosophila lateral antennal lobe ( lAL ) neuroblast . The lAL lineage consists of two distinct hemilineages , generated through differential Notch signaling in the two GMC daughters , to produce one projection neuron ( PN ) paired with a local interneuron ( LN ) . Both hemilineages yield distinct cell types in the same sequence , although the temporal identity ( birth-order-dependent fate ) changes are regulated independently between projection neurons and local interneurons , such that a series of analogous local interneurons may co-derive with different projection neurons and vice versa . We also find that Notch signaling can transform a class of nonantennal lobe projection neurons into antennal lobe projection neurons . These findings suggest that Notch signaling not only modulates temporal fate but itself plays a role in the distinction of antennal lobe versus nonantennal lobe neurons .
|
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"developmental",
"biology",
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2012
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Lineage Analysis of Drosophila Lateral Antennal Lobe Neurons Reveals Notch-Dependent Binary Temporal Fate Decisions
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The domestic dog is a robust model for studying the genetics of complex disease susceptibility . The strategies used to develop and propagate modern breeds have resulted in an elevated risk for specific diseases in particular breeds . One example is that of Standard Poodles ( STPOs ) , who have increased risk for squamous cell carcinoma of the digit ( SCCD ) , a locally aggressive cancer that causes lytic bone lesions , sometimes with multiple toe recurrence . However , only STPOs of dark coat color are at high risk; light colored STPOs are almost entirely unaffected , suggesting that interactions between multiple pathways are necessary for oncogenesis . We performed a genome-wide association study ( GWAS ) on STPOs , comparing 31 SCCD cases to 34 unrelated black STPO controls . The peak SNP on canine chromosome 15 was statistically significant at the genome-wide level ( Praw = 1 . 60×10−7; Pgenome = 0 . 0066 ) . Additional mapping resolved the region to the KIT Ligand ( KITLG ) locus . Comparison of STPO cases to other at-risk breeds narrowed the locus to a 144 . 9-Kb region . Haplotype mapping among 84 STPO cases identified a minimal region of 28 . 3 Kb . A copy number variant ( CNV ) containing predicted enhancer elements was found to be strongly associated with SCCD in STPOs ( P = 1 . 72×10−8 ) . Light colored STPOs carry the CNV risk alleles at the same frequency as black STPOs , but are not susceptible to SCCD . A GWAS comparing 24 black and 24 light colored STPOs highlighted only the MC1R locus as significantly different between the two datasets , suggesting that a compensatory mutation within the MC1R locus likely protects light colored STPOs from disease . Our findings highlight a role for KITLG in SCCD susceptibility , as well as demonstrate that interactions between the KITLG and MC1R loci are potentially required for SCCD oncogenesis . These findings highlight how studies of breed-limited diseases are useful for disentangling multigene disorders .
Each of the approximately 300 domestic dog breeds recognized world-wide has undergone strong phenotypic selection for specific behavioral and morphologic traits . One consequence of the breeding programs used to propagate lineages with such strong phenotypic homogeneity is the increased incidence of diseases , including cancer . Indeed , cancer is the leading cause of disease-associated death in dogs [1] , [2] , with 23% of all dogs and 45% of dogs older than 10 years dying of cancer . Multiple breeds are at an elevated risk for specific cancers , indicating a likely genetic predisposition ( reviewed in [3] , [4] , [5] ) . Dogs are diagnosed with nearly all of the same cancers as humans [6] , and the underlying pathology and treatment response are typically the same as for humans [7] , suggesting that canine cancer genetic studies are a useful way to advance our understanding of human disease [3] , [8] , [9] . Typically , for any given cancer , the number of deleterious alleles segregating in a single dog breed is likely to be limited , as dog fanciers employ closed breeding programs to develop breeds with specific phenotypic traits [5] , [10] , [11] . As a result , cancer gene mapping in dogs presents a mechanism to circumvent the small families , outbred population structure and locus heterogeneity that continually plague human cancer gene mapping [3] , [4] . Applying the canine model to cancer gene mapping is particularly useful when multiple closely related breeds are at an increased risk for the same form of the disease [12] , [13] , [14] , [15] , as this often indicates that the breeds in question may share a common founder mutation . This is particularly applicable to the problem of cancer , where results from genome-wide association studies ( GWAS ) in humans indicate that noncoding variants are expected to contribute significantly to disease susceptibility [16] . Squamous cell carcinoma of the digit ( SCCD ) is the most frequently occurring cutaneous squamous cell carcinoma ( SCC ) in dogs , making up 60% of all SCCs of the skin [17] , [18] . It is the most common malignant nail bed tumor , comprising 44 . 4% of reported cases [19] , [20] , [21] , [22] . SCCD is a locally aggressive cancer that causes bone lysis in approximately 80% of cases [19] , [20] , [21] . Tumors can develop in multiple digits , typically in breeds at the highest genetic risk [17] , [21] , [22] , [23] . The disease is considerably more aggressive than other cutaneous SCCs , with 19 . 2% of reported cases progressing to metastatic disease [19] , [20] , [21] , [22] , [24] . Multiple breeds have increased or decreased risk of SCCD compared to mixed breed dogs [24] , [25] . The five breeds with the highest risk of SCCD include Giant Schnauzers ( Odds Ratio ( OR ) = 22 . 7 , 95% Confidence Interval ( C . I . ) = 16 . 0–32 . 3 ) , Gordon Setter ( OR = 11 . 1 , 95% C . I . = 7 . 5–16 . 3 ) , Briard ( OR = 10 . 4 , 95% C . I . 5 . 5–19 . 8 ) , Kerry Blue Terrier ( OR = 7 . 7 , 95% C . I . = 4 . 8–12 . 2 ) and Standard Poodles ( OR = 5 . 9 , 95% C . I . 4 . 8–7 . 2 ) [25] . By comparison , three breeds with reduced risk are the Beagle ( OR = 0 . 1 , 95% C . I . = 0 . 03–0 . 30 ) , Collie ( OR = 0 . 16 , 95% C . I . = 0 . 04–0 . 65 ) and Boxer ( OR = 0 . 23 , 95% C . I . = 0 . 13–0 . 43 ) [25] . In this study , we evaluated three increased risk breeds , Standard Poodles ( STPOs ) , Giant Schnauzers and Briards ( Figure 1 ) . Phylogenetically , all three breeds belong to the modern group of dogs developed mostly in Europe , but are not closely related as none of them appear together within a single cluster or group [13] , [26] . One of the most interesting aspects of SCCD is its profoundly strong association with dark coat colors in a subset of breeds [19] , [20] , [21] , [22] . The most striking example is that of the very popular STPO where black dogs are at high risk for SCCD , but light colored dogs , including white and cream are , to our knowledge , unaffected . The association of the disease with particular STPO coat colors suggests that studies of SCCD might be informative for both identifying a cancer susceptibility allele as well as for elucidating additional complex gene or pathway interactions involved in the susceptibility process .
We conducted a GWAS for SCCD in STPOs using DNA from 31 cases and 34 controls ( Figure 2 ) . All cases had biopsy confirmation of SCCD and dark coats ( 30 black and one “blue” , which is a dilution of black ) . All controls had black coats , were over the age of eight and were unrelated to one another at the grandparent level . Analysis of 36 , 897 SNPs revealed a single statistically significant association on canine chromosome 15 ( CFA15 ) . The six most strongly associated SNPs ( Praw = 6 . 51×10−5 to 1 . 60×10−7 ) were contiguous on CFA15 and the peak SNP , CFA15:32 , 383 , 555 ( in the CanFam2 assembly ) , was statistically significant at the genome-wide level ( Pgenome = 0 . 0066 , based on 100 , 000 permutations ) . The risk-associated allele was present in 90 . 3% cases at the peak SNP , and 51 . 6% of cases were homozygous for the risk-associated allele ( Table 1 ) . By comparison , none of the controls were homozygous for the risk-associated allele , and 50% were heterozygous ( Table 1 ) . In order to refine the initial association peak further , both recombination mapping and an additional association analysis were performed . Both analyses utilized data from the resequencing of 525 amplicons in 38 cases and 30 controls . The cases represented the original 31 STPO cases plus seven additional cases that were enrolled following completion of the initial GWAS . The controls were the same as those in the initial GWAS , minus four with insufficient DNA for follow-up analyses . All 38 cases and 30 controls were resequenced around the peak SNP . Given that several cases did not carry the risk-associated allele at CFA15:32 , 383 , 555 , we sought to capture variants in as many cases and controls as possible to assemble an optimally detailed haplotype structure across the region . The 525 amplicons were spaced , on average , every one Kb within a 1 . 2 Mb region surrounding CFA15:32 , 383 , 555 ( CFA15:31 , 900 , 000–33 , 100 , 000 ) in order to ensure that the boundaries of the recombination intervals and limits of the significant association signal were identified . The amplicons were also designed to resequence the exons of the six genes in the region . Following the resequencing , 862 variants , including SNPs and indels , were identified , for a median spacing of 370 bp . A total of 658 of 862 variants had a minor allele frequency >10% , generating a median spacing of 368 bp . The recombination mapping highlighted regions where individual cases no longer shared at least one copy of the STPO risk-associated haplotype . For the one recombinant interval , the borders are defined by the position for which there is one individual case that no longer shares the putative risk associated haplotype . One individual may define the centromeric side of the region of interest and a different individual the telomeric border . The more conservative and standard approach is to define the borders of the region by the position where three individuals per border no longer share the region of interest . While this generally creates a larger region to analyze , it provides greater assurance that the region contains the mutation of interest since using one individual can create false positives if , for instance , that individual was misdiagnosed or represents a phenocopy . We utilized all 862 variants to determine the one and three recombination intervals . Since the analysis focused on finding where cases stop sharing the risk-associated alleles or haplotypes , only the 35 cases that shared at least one copy of the risk-associated allele at the peak SNP were included in the analysis . We evaluated one variant at a time and a recombination event was identified if a case no longer shared at least one copy of the STPO case major allele for a particular variant , and if this case continued to no longer share at least one copy of the STPO case major allele or haplotype for ≥one Kb . Centromeric to the peak SNP , the first recombination event was at 32 , 347 , 048 bp in one case and evidence for the third recombination event occurred at 32 , 088 , 047 bp in two additional cases ( Figure 3 ) . The first and third recombination events telomeric to the peak SNP were at 32 , 873 , 675 bp in one case and 32 , 901 , 086 bp in two additional cases , respectively . Thus , from this analysis , we defined the one recombination interval as the 526 . 6 Kb locus from CFA15:32 , 347 , 048–32 , 873 , 675 and the three recombination interval as the 813 . 0 Kb locus from CFA15:32 , 088 , 047–32 , 901 , 086 ( Figure 3 ) . An additional association analysis was performed to highlight the region of strongest association to the disease . We compared data from all 38 cases to that obtained from the 30 controls . Figure 3 shows the association results for the 658 variants with minor allele frequencies >10% . All but three of the 220 variants that associated strongly with SCCD ( P values<1 . 0×10−7 ) were within a single 520 . 1 Kb locus that spanned CFA15:32 , 312 , 908–32 , 832 , 982 ( Figure 3 ) , which corresponded closely to the 526 . 6 Kb one recombination interval . This region was observed to contain an excellent candidate oncogene , KITLG , whose exons are located entirely within the locus of association . With such an obvious candidate gene at the SCCD locus , we intensified our efforts to obtain better coverage of the KITLG region . We eventually resequenced 100% of the exons , 89 . 7% of the introns , and 79 . 3% of the 10 Kb region upstream of the first exon ( Figure S1A ) . We examined the data for a causal variant , defined as a variant which was present in all STPO cases and for which the risk allele frequency differed significantly between cases and controls . However , none of the variants identified in the region met these criteria . In addition , no new variant demonstrated a stronger association with the disease than those we had previously identified ( Figure 3 ) . Since the STPO one and three recombination intervals are large , spanning 526 . 6 Kb and 813 . 0 Kb , respectively , we conducted an interbreed haplotype analysis to reduce the region of interest . We compared data from the 38 STPO cases with data from affected dogs of two other at-risk breeds: Giant Schnauzers ( n = 28 ) and Briards ( n = 11 ) . All together , 536 variants with a median spacing of 472 bp were available for the STPO and Giant Schnauzer analysis , 821 variants with a median spacing 375 bp were evaluated for the STPO and Briard case comparison . Utilizing these variants , we scanned the STPO three recombination interval for the largest region where all Giant Schnauzer or Briard cases had at least one copy of the same haplotype as the majority of STPO cases . The Giant Schnauzers had only one region greater than 50 Kb where all cases carried the same haplotype as the majority of STPO cases . This region was 75 . 1 Kb in length , from CFA15:32 , 832 , 982–32 , 908 , 071 , and the shared haplotype was present in 34 of 38 STPO cases . There were , however , four discordant SNPs in the adjacent region in either the Giant Schnauzer and/or STPO cases ( CFA15:32 , 724 , 674 , CFA15:32 , 749 , 603 , CFA15:32 , 795 , 285 and CFA15:32 , 832 , 982 ) that likely arose on the risk haplotype after the causal variant . Acting conservatively we excluded these four SNPs from consideration , thus expanding the provisional region of interest , which we defined as that shared between the Giant Schnauzer and STPO cases , from 75 . 1 Kb to 207 . 8 Kb ( CFA15:32 , 700 , 300–32 , 908 , 071; Figure 4 ) . The results of the interbreed haplotype analysis in the Briard cases were very similar to that of the Giant Schnauzer , although the Briards reduced the region of interest still further . Briards had only one region greater than 40 Kb for which all cases shared a haplotype with the majority of STPO cases , and it was the same as the initial Giant Schnauzer region ( 75 . 1 Kb from CFA15:32 , 832 , 982–32 , 908 , 071 ) . The Briard cases were homozygous for the major STPO case haplotype , with the homozygosity extending to create a shared haplotype of 144 . 9 Kb between the Briard and STPO cases ( CFA15:32 , 763 , 151–32 , 908 , 071; Figure 4 ) , after discarding two of the discordant SNPs , described above , that also disrupted the Giant Schnauzer haplotype ( CFA15:32 , 795 , 285 and CFA15:32 , 832 , 982 ) . In summary , the largest overlapping region between STPO , Giant Schnauzer and Briard cases was the 144 . 9 Kb region that extends from CFA15:32 , 763 , 151 to 32 , 908 , 071 . We investigated the 144 . 9 Kb overlapping region in STPO cases and controls , and determined the linkage disequilibrium ( LD ) patterns of 186 STPO variants within the region using Haploview [27] . Two major LD patterns were present ( Figure 4 ) . The first had only one predicted LD block , which we termed block A . The second was comprised of three LD blocks , termed B , C and D , which were not very polymorphic in STPOs . The haplotype within block A segregated disproportionately with disease in the 38 STPO cases compared to the 30 controls ( P = 1 . 67×10−8 ) , and initially appeared promising as the location of the causal variant . The four SNPs that tag block A were therefore genotyped in all STPO , Giant Schnauzer and Briard cases and controls , including 46 additional STPO cases ( 84 total STPO cases ) . The number of dogs with zero , one or two chromosomes containing the risk-associated haplotype are indicated in Table 2 . Importantly , not all STPO cases carried the block A risk-associated haplotype . Six of 84 did not , indicating that while variant ( s ) within block A were likely closely linked to the causal variant , they did not fully explain the disease in STPOs . We noted , however , that the block A risk-associated haplotype was homozygous in all 28 Giant Schnauzer cases and nearly all of the unrelated Giant Schnauzer controls ( 12 out of 13; 96 . 2% ) , indicating that Giant Schnauzers are nearly fixed for this haplotype . Since the block A risk-associated haplotype was found to be closely linked to the causal variant in STPOs , the high frequency of the block A risk-associated haplotype in Giant Schnauzers hints at why they are at the highest risk for the disease ( OR , 22 . 7; CI , 16–32 . 3 ) [25] . By comparison , 72 . 2% of Briard controls carried the STPO block A risk-associated haplotype , which was between the haplotype frequency in STPO ( 26 . 5% ) and Giant Schnauzer ( 96 . 2% ) controls , and was consistent with the disease risk observed in Briards ( OR , 10 . 4; CI , 5 . 5–19 . 8 ) [25] . Since the variants identified thus far did not explain the disease in all STPO cases , we completed the resequencing of the 144 . 9 Kb region using tiled primers ( Figure S1B ) . In the end , 142 , 938 bp or 98 . 6% of the region was completely resequenced in STPO cases and controls . The remaining 1 , 982 bp represented regions that were difficult to sequence using Sanger sequencing , including long stretches of homopolymers and other repeats . In the 144 . 9 Kb region , 36 additional variants that segregate with the disease were identified for a total of 114 disease-associated variants . However , no causal variant candidates that met our specified criteria of occurring in all STPO cases and being significantly associated with disease were identified . We next performed haplotype mapping with tagging variants across the entire 144 . 9 Kb region in all 84 STPO cases ( Figure 5 ) to identify regions to prioritize in a search for large insertions , deletions or copy number variants ( CNVs ) . The majority of STPO cases ( n = 64 ) shared at least one copy of the same haplotype within LD blocks A , B , C and D . The remaining 20 STPO cases shared at least one copy of the major STPO case haplotype in only two or three of the LD blocks , as indicated by the blue bars in Figure 5 . Specifically , eight cases shared in LD blocks A and B , six cases shared in LD blocks A , B and C , and another six cases shared in LD blocks B , C and D . Thus , the only LD block where all STPO cases shared at least one copy of the same STPO case haplotype is LD block B . Data from the 38 STPO cases which were resequenced across the 144 . 9 Kb haplotype indicated the same result . As such , we investigated the 28 . 3 Kb between the end of LD block A and the beginning of LD block C further . The canine reference sequence [15] for the 28 . 3 Kb sub-region contains a tandem copy of a 5 . 7 Kb element in the Boxer ( Figure 5 ) , which is only found once in all other placental mammalian species for which there is finished genome sequence ( n = 20; http://genome . ucsc . edu ) . Interestingly , the 5 . 7 Kb element is , in fact , between the end of block A and the beginning of block B making it immediately adjacent to the block A disease-associated haplotype , which we observed was in strong , but not perfect , LD with the putative causal variant . To test if this was the disease variant , we performed Southern blots using DNA from STPO cases and controls where we identified variation in the copy number of the 5 . 7 kb unit ranging from one to five copies ( Figure S2 ) . After comparing STPO cases and controls , our data indicated that the expanded 5 . 7 Kb element is an excellent SCCD causal variant candidate . All cases with Southern blot data ( n = 47 ) had at least one allele with ≥4 copies of the 5 . 7 Kb element ( Table 3 ) , which we termed the risk alleles and , as such , the expanded CNV was strongly associated with disease in STPO cases ( P = 1 . 72×10−8 ) . Specifically , 15 cases were heterozygous and 32 were homozygous for ≥4 copies . By comparison , in a set of 45 unrelated black STPO controls , 13 had no alleles with ≥4 copies , 24 were heterozygous and eight were homozygous for the risk alleles ( Table 3 ) . Importantly , six out of 84 cases did not carry the block A risk-associated haplotype . Of these six , we were able to obtain CNV genotype data on four . All four cases had at least one copy of the CNV risk allele with three being heterozygous and one homozygous . We reevaluated the 144 . 9 Kb resequencing data and confirmed that no other SNP or small insertion/deletion had the same segregation pattern as the CNV risk and non-risk alleles . Thus , our data indicated that the CNV is the best SCCD causal variant candidate as the expanded 5 . 7 Kb element explained the disease in the STPO better than any of the other risk-associated variants identified . Evidence that the expanded CNV is the putative SCCD causal variant was also consistent with data obtained from the other increased risk breeds . All nine genotyped Giant Schnauzer cases were homozygous for four copies of the 5 . 7 Kb element . In the Briard , three out of the four genotyped cases were homozygous for the CNV risk alleles . Specifically , two Briard cases were homozygous for four copies , one was a four/five heterozygote and one was homozygous for two copies . Therefore , overall only one case out of 60 ( 47 STPOs , nine Giant Schnauzers and four Briards ) lacked the putative causal variant . We also genotyped the CNV in 36 dogs from six breeds at reduced risk for SCCD ( n = 3 to 8 dogs per breed ) . The six breeds selected , which varied in terms of size and morphologic features , were the Basset Hound ( n = 8; OR 0 . 27; CI 0 . 10–0 . 73 ) , Boston Terrier ( n = 3; OR 0 . 25; CI 0 . 06–1 . 01 ) , Boxer ( n = 6; OR 0 . 23; CI 0 . 13–0 . 43 ) , Shetland Sheepdog ( n = 8; OR 0 . 18; CI 0 . 07–0 . 42 ) , Collie ( n = 7; OR 0 . 16; CI 0 . 04–0 . 65 ) , and Beagle ( n = 4; OR 0 . 10; CI 0 . 03–0 . 30 ) [25] . Alleles containing either one or three copies of the CNV were the most common in this population ( 52 . 8% and 41 . 7% ) . The two copy allele was infrequent ( 4 . 2% ) . As expected , the four copy allele was rare ( 1 . 4% ) found in only one dog and none of the dogs carried the five copy allele . Thus , the CNV risk alleles are rare in the aggregate reduced risk breeds tested especially when compared to the set of 45 black STPO controls ( P = 3 . 77×10−10 ) . As the four copy allele was discovered in one of three unrelated Boston Terriers , it would be interesting to determine the population frequency of the four copy allele specifically in this reduced risk breed . However , no additional unrelated Boston Terriers were available in our collection at this time . Although we note that a much larger collection would be needed to determine the prevalence of the CNV risk alleles in SCCD increased or reduced risk breeds other than STPOs and in dog breeds as a whole , our data clearly indicated a strong and unique association between the expanded 5 . 7 Kb CNV and SCCD in STPOs . Data from the corresponding human genome sequence ( Chr12:89 , 170 , 403–89 , 176 , 159 in build GRCh37 ) suggested that the 5 . 7 Kb sequence contains elements of an enhancer binding site ( Figure S3 ) . Thus , we hypothesized that an enhancer-mediated increase in KITLG transcription is likely key to the disease process although we cannot exclude the possibility that the expanded CNV affects another gene in the region . Finally , we wanted to determine why black STPOs are uniquely at risk for SCCD while light colored STPOs are not . Of the 84 SCCD STPOs enrolled in our study , which included all that came to our attention and met the eligibility criteria in terms of pathology and disease status , 82 had a black coat color , one was blue ( dilute black ) , one was brown and none had a light coat color ( white , cream , apricot or red ) , in spite of the fact that light colored STPOs comprise approximately 31 . 8% of the STPO population in the United States , as calculated from the Standard Poodle Database version 6 . 2 [28] . We first tested the range of CNV alleles in 26 unrelated light colored STPOs ( Table 4 ) . We observed that the frequency of the risk alleles ( ≥4 copies of the CNV ) in light colored STPOs was similar to that observed in 45 unrelated black STPO controls ( P = 0 . 81 ) as well as the 34 unrelated , unaffected young STPOs chosen without regard to coat color , that served as population controls ( P = 0 . 77 ) . Additionally , the surrounding haplotypes on which the CNV alleles occur in the light colored and young STPOs were the same as the ones observed in the black STPOs . This indicated that the light colored STPOs carry the putative SCCD causal variant at a similar frequency as the black STPOs , and since the light colored STPOs do not get SCCD , some other factor or factors must protect them from the disease . We hypothesized that the protection might be from a compensatory mutation ( s ) located elsewhere in the genome . Towards this end , the melanocortin 1 receptor ( MC1R ) , a frequently studied pigmentation and skin cancer susceptibility locus , is the obvious candidate , as it is well established that a homozygous MC1R R306X mutation causes light versus dark coat color in STPOs and many other dog breeds [29] . We performed a GWAS to test whether the MC1R locus is the only locus where allele frequencies differ significantly between black and light colored STPOs . If it is , the locus could reasonably be proposed as protecting light colored STPOs from SCCD . In order to test the MC1R hypothesis , we performed a GWAS using DNA from 24 unrelated black STPO controls and 24 unrelated light colored STPO controls using the Illumina CanineHD BeadChip . Association analysis of 126 , 697 genome-wide SNPs revealed a single statistically significant result on canine chromosome 5 ( CFA5 , Figure 6 ) . The 22 most strongly associated SNPs ( Praw = 3 . 58×10−7 to 2 . 52×10−15 ) were statistically significant at the genome-wide level after permutations and all were located on CFA5 . The region of significant association extends from the peak SNP , CFA5:66 , 664 , 263 to CFA5:67 , 022 , 978 in the telomeric direction encompassing the entire MC1R locus . Importantly , no other locus was significantly different between black and light colored STPOs , indicating that the MC1R locus was the only candidate locus for the protection of light colored STPOs from SCCD . We then genotyped the previously identified MC1R R306X mutation in the black and light colored STPOs we had sampled . The mutation segregated perfectly with coat color and had an identical segregation pattern as the peak GWAS SNP , CFA:66 , 664 , 263 ( P = 2 . 52×10−15 ) , indicating that the GWAS peak was likely tagging the previously identified mutation within MC1R . Although we cannot formally exclude the possibility that other variants in MC1R or nearby genes are in perfect LD with the peak GWAS SNP and the MC1R R306X mutation , our data supports the hypothesis that the MC1R R306X mutation is a good candidate for the protective variant , especially considering the mutation has functional consequences . The MC1R R306X mutation alters the protein and most likely acts as a loss-of-function allele . This is well supported by previously published studies of 833 dogs from 58 breeds in which the variant is consistently associated with light coat color [29] , [30] , [31] , [32] .
We demonstrate here the utility of the canine system for studying the genetics of complex traits such as cancer . Previous efforts to use the canine system for finding cancer genes have focused on either linkage studies of large single breed families , as was the case with canine cystadenocarcinoma [33] , or have focused on diseases of single breeds , such as histiocytic sarcoma found in Bernese Mountain dogs [34] . While each study provided interesting and useful data , neither made extensive use of dog breed structure [13] , [26] , [35] , which allows investigators to reasonably hypothesize that dogs with similar diseases who share recent common ancestors likely share both the disease haplotype and mutation [10] , [13] . Indeed , in the case of SCCD , the fact that multiple breeds share the same haplotype at the disease locus was key in reducing a large region of association to 144 . 9 Kb , which could easily be interrogated by DNA sequencing . Prior to that , however , we performed a GWAS using DNA from 31 STPO cases and 34 unrelated STPO controls and identified a significant peak on CFA15 at CFA15:32 , 383 , 555 . The fact that such a small number of individuals could be used for the GWAS was predicted by Lindblad-Toh [15] , proven shortly thereafter [14] , and is highlighted in a myriad of subsequent GWAS ( for review see [8] ) . In the case of SCCD , after additional fine mapping in 38 STPO cases , we resolved the association peak to the KITLG locus . Comparison of STPO cases with cases from two other high-risk breeds refined the locus to 144 . 9 Kb . Haplotype analysis using 84 STPO cases narrowed the region to only 28 . 3 Kb , where we identified the putative SCCD causal variant as a 5 . 7 Kb CNV that is 183 Kb upstream of KITLG . Risk of SCCD in STPOs was strongly associated with the presence of the four copy or five copy allele of this CNV ( P = 1 . 72×10−8 ) , and all 47 STPO cases that we successfully tested carried at least one allele with ≥4 copies of the 5 . 7 Kb element . We found no STPO cases which lacked at least one copy of the risk allele . Four studies have investigated CNVs genome-wide in dogs [36] , [37] , [38] , [39] . Two of the four found evidence for the SCCD 5 . 7 Kb CNV region [36] , [38] . In one study , all known canine CNVs were interrogated by array comparative genomic hybridization ( aGCH ) using DNA from 61 dogs representing 12 diverse breeds [38] . CNV loss was detected for several breeds and copy gains were found for one of the five Dachshunds and one of the six STPOs [38] . Interestingly , Dachshunds are another breed at increased risk for SCCD ( OR = 2 . 2 , 95% C . I . 1 . 6–3 . 0 ) [25] . Since the putative SCCD causal variant is a reiterated 5 . 7 Kb element located 183 Kb upstream of the primary gene , KITLG , it is interesting to hypothesize how the variant might modulate disease risk . Several studies have reported causal variant duplications in upstream regions leading to increased expression of nearby genes , including a study of hereditary mixed polyposis syndrome ( HMPS ) in humans and periodic fever syndrome in Chinese Shar-Pei dogs [40] , [41] . HMPS is a Mendelian colorectal polyposis syndrome that results from an approximately 40 Kb duplication spanning the 3′ end of SCG5 gene and the upstream region of the GREM1 locus [41] . The duplication is associated with increased allele-specific expression of GREM1 and not SCG5 [41] . The HMPS duplication contains Encyclopedia of DNA Elements ( ENCODE ) predicted enhancer elements , some of which were shown to interact with the GREM1 promoter and drive gene expression in vitro [41] . For the putative SCCD 5 . 7 Kb CNV causal variant , data from the corresponding human genome sequence ( Chr12:89 , 170 , 403–89 , 176 , 159 in build GRCh37 ) suggests that it might also function to increase expression of nearby genes . The multiple species conservation site on the telomeric edge of the 5 . 7 Kb element contains elements of an enhancer binding site ( Figure S3 ) . Specifically , the ENCODE DNaseI Hypersensitivity analysis was positive in 47 out of the 148 cell lines tested including the only keratinocyte line assayed . The ENCODE Transcription Factor ChIP-seq analysis identified binding for four different transcription factors in cell lines that were derived from mammary epithelial tissue . Finally , the ENCODE and Broad Chromatin State Segmentation analysis by Hidden Markov Modeling predicted the presence of a strong enhancer binding site in both the normal epidermal keratinocytes and normal mammary epithelial cells . Therefore , one possible mechanism by which the risk alleles could affect disease susceptibility is that the additional copies of the 5 . 7 Kb element would create additional enhancer binding sites , which up-regulate transcription . As such , we hypothesize that the three , four and five copy alleles would each have a corresponding increase in expression and that the total number of copies also determine the level of transcription with , for example , individuals homozygous for the three copy allele having a lower expression level compared to individuals heterozygous for the three and four copy alleles . If this mechanism of action for the 5 . 7 Kb CNV is validated , we further hypothesize that the CNV would affect SCCD risk in a dose-dependent manner , leading to an increase in disease penetrance for individuals carrying two versus one of the CNV risk alleles . Although our data is not a population-based sampling of STPOs , the proportion of cases among the total number of STPOs increases according to the number of CNV risk alleles ( Table 3; zero risk alleles , 0%; one risk allele , 38 . 5%; two risk alleles , 80% ) , suggesting an increase in disease penetrance with two risk alleles compared to only one risk allele . At the same time , our data suggests that age-dependent penetrance or incomplete penetrance might also be involved to account for the small number of dogs that are homozygous for the risk allele and do not yet have the disease . Of course , we cannot formally exclude the possibility that a variant at another locus further modifies disease susceptibility . Finally , since our hypothesis indicates that the five copy allele would have higher expression compared to the four copy allele , it would be interesting to look at the correlation between genotype and phenotypes like age at onset or recurrence of SCCD once we have a large enough collection of STPO cases with the five copy allele . While functional studies would provide more definitive support for the 5 . 7 Kb CNV mechanism of action , the optimal experiment is difficult to perform in pet dogs , as expression studies would require difficult to obtain nail bed tissue from STPOs , with and without the putative causal variant CNV . Owners of both cases and , especially , controls are understandably reluctant to provide such tissue from their pets , as it would incur significant discomfort . KITLG encodes the ligand for the tyrosine kinase receptor KIT . Together they are involved in multiple processes including melanocyte development and epidermal homeostasis and , as such , play a role in pigmentation . Specifically , KITLG has been associated with intensity of hair color pigmentation in humans [42] , [43] . In stickleback fish , it is associated with skin pigmentation such that decreased KITLG expression reduces pigmentation [44] . When the KITLG locus was examined in humans , Miller et al . found strong signatures of selection in Europeans and East Asians and an association with skin pigmentation from admixture mapping in African Americans , suggesting that the KITLG locus contributes to human skin pigmentation as well [44] . Interestingly , like the human KITLG locus , the canine locus is also under strong selection . It is one of the top 20 loci with signatures for selection as assessed by FST in two independent datasets [45] , [46] . In the study of Boyko et al . , which included 80 dog breeds and over 900 individuals , the FST region at KITLG extends from CFA15:32 , 383 , 555–33 , 021 , 330 , which starts at the original peak SNP of the SCCD GWAS and extends beyond the 5 . 7 Kb CNV [45] . In the study of Vaysse et al . , the FST region observed in 46 breeds is smaller , extending from CFA15:32 , 638 , 117–32 , 853 , 840 , but it still overlaps the putative causal variant 5 . 7 Kb CNV [46] . Given the effect of KITLG on hair and skin pigmentation intensity in humans , the signature of selection at KITLG in dogs most likely represents breeders' attempts to propagate dogs of a certain color . Additional work is required to demonstrate if the SCCD 5 . 7 Kb CNV risk haplotypes specifically have signatures of selection within this locus . However , since the putative SCCD causal variant is well within a region under strong selection , it is intriguing to think that the SCCD susceptibility locus might be one of the first to demonstrate what has long been hypothesized for dogs that breeder-based trait selection can unknowingly lead to the entrapment of cancer causing alleles [5] , [9] , [10] . KITLG/KIT signaling has also been implicated in oncogenesis . The KITLG locus was initially identified as a cancer susceptibility locus for human testicular germ cell tumors in two independent GWASs , although the specific mutation and mechanism of action remains unknown [47] , [48] . In addition , somatic activating KIT mutations are associated with several cancers , including human gastrointestinal stromal tumors and human melanomas ( reviewed in [49] , [50] ) . However , our study is the first to report the involvement of the KITLG locus in skin cancer susceptibility . One interesting finding from our data is that the MC1R locus is the only candidate locus for the putative protection of light colored STPOs from SCCD . If a functionally active MC1R is proven to be required for SCCD susceptibility , we hypothesize that this is likely due to a necessary interaction of the MC1R pathway with the KITLG/KIT pathway to promote SCCD oncogenesis and/or that dark pigmentation is required within the nail bed . Although we cannot formally exclude the more distant possibility that the protection from SCCD is provided by a mutation in another gene or genetic element within the MC1R locus selective sweep , we believe that a loss-of-function mutation in MC1R is the most likely cause since both pathways are known to be involved in oncogenesis and there is previous evidence for multiple interactions between the two pathways . One such interaction involves signaling from MC1R , which can cause transactivation of the KIT receptor via Src tyrosine kinase [51] . Additionally , signaling from both KITLG and MC1R affects the MITF transcription factor , whose functions include cell cycle regulation and antiapoptotic signaling [52] . Indeed , MC1R pathway activity increases MITF expression and the KIT pathway phosphorylates MITF via the MAPK pathway to activate the protein [52] . Thus , both pathways could interact in SCCD oncogenesis via MITF . While the specifics of why functionally active MC1R signaling is required for SCCD oncogenesis remains elusive , our study identified a potential genetic interaction between the KITLG and MC1R loci such that mutations in the MC1R locus may be responsible for protecting dogs from KITLG-induced SCCD susceptibility . One unanswered question from this study is how alteration of the KITLG/KIT and MC1R signaling pathways lead to SCCD , since both pathways are known to function within the melanocyte and not necessarily within the keratinocyte , which is the originating cell for SCCD . One theory for how the putative overexpression of KITLG can lead to SCCD is that the keratinocyte and melanocyte are adjacent cells in skin with well known paracrine activity between the cell types [53] . Indeed , KITLG is produced in the keratinocyte and released to simulate the melanocyte , which is how the KITLG/KIT pathway regulates important communication signals between the melanocytes and surrounding keratinocytes in the skin [53] . Therefore , it is possible that some other factor ( s ) , perhaps one of the cell cycle or antiapoptotic factors downstream of MITF , that are produced in the melanocyte might promote oncogenesis in the keratinocyte . If loss-of-function mutations in MC1R are proven to protect canines from SCCD , it may initially seem to be a surprising result , as loss-of-function MC1R variants are associated with increased incidence of skin cancer in humans . Consistently , a relationship between the MC1R loss-of-function ‘R’ alleles ( D84E , R142H , R151C , I155T , R160W , and D294H ) and risk of cutaneous basal cell carcinoma ( OR 1 . 37–3 . 16 ) , SCC ( OR 1 . 99 ) and melanoma ( OR 1 . 38–4 . 64 ) has been shown ( reviewed in [54] ) . However , our study is not the only one to suggest that functionally active MC1R signaling may promote rather than protect against skin cancer incidence/progression . Rather , a study of melanoma in gray horses where increased wild-type MC1R signaling was shown to promote melanoma incidence was the first [55] , and additional supporting data comes from studies of melanoma survival in humans [56] . Specifically , individuals who were homozygous for MC1R mutant alleles had a significantly lower risk of melanoma-specific death in a series of 3060 cases from Europe and the United States ( HR , 0 . 78; 95% CI , 0 . 65–0 . 94 ) , implying that a functional MC1R pathway promotes melanoma progression in humans . Both studies are consistent with our findings for SCCD in STPOs . A functionally active MC1R pathway can play a distinct role in oncogenesis unique from what has been proposed previously , i . e . functional MC1R signaling does not always protect against , but can actively promote cancer incidence and/or progression . Our findings highlight the value of studying complex diseases in non-human systems such as the dog , where we have the ability to exploit breed-specific reduced genetic variability and interbreed relatedness to find genetic variants . Our studies of SCCD allowed us to not only identify a single cancer susceptibility causal variant candidate , but also a multiple locus interaction that would be difficult to uncover in a genetically diverse population . These discoveries , if confirmed in future analyses , not only allow us to better understand the interplay between two well-studied pathways , but provide additional evidence that the MC1R pathway can contribute to oncogenesis in multiple ways .
All samples were collected from pet dogs after the owners provided informed consent . Study materials were approved by the Animal Care and Use Committees at the collection institutions . All procedures and materials were approved by the Animal Care and Use Committee of the National Human Genome Research Institute . DNA from blood was extracted using standard protocols . Saliva DNA was collected and extracted using the Oragene-Animal collection kit ( DNA Genotek , Ontario , Canada ) . SCCD cases were all confirmed with biopsy reports from veterinary pathologists . Controls are ≥8 years old at the time of the analysis with pedigree information and unrelated at the grandparent level . For the original STPO controls ( n = 34 ) , Briards ( n = 18 ) and Giant Schnauzers ( n = 13 ) , dogs were considered controls if born before 2002 and unaffected . In the 5 . 7 Kb CNV analysis and black versus light colored STPO GWAS , the unrelated black STPO controls ( n = 45 ) and light colored controls ( n = 26 ) were born before 2005 , while the young STPOs ( n = 34 ) were born in or after 2005 . The first GWAS compared 31 STPO cases and 34 unrelated black STPO controls using the Affymetrix v2 Canine SNP Chip ( Affymetrix , Santa Clara , CA ) . The BRLMM-P algorithm was used to genotype the SNPs . SNPs were removed from the analysis if greater than 10% of the data were missing , there were more than 60% heterozygous calls , or the minor allele frequency was <5% . The final dataset consisted of 36 , 897 SNPs . The second GWAS compared 24 unrelated black STPO controls and 24 unrelated light colored STPO controls using the Illumina CanineHD BeadChip ( Illumina , San Diego , CA ) . SNP genotypes were called using the Illumina Genome Studio software package . SNP clusters were evaluated if the call rate was <90% , the heterozygous excess was −1 to −0 . 7 or 0 . 5 to 1 , and if the GenTrain score was <0 . 5 . SNPs were removed from the analysis if the evaluated SNP clusters could not be improved or if the minor allele frequency was <5% . The final set consisted of 126 , 697 SNPs . The genotypes and phenotypes for both GWASs will be submitted to Gene Expression Omnibus ( GEO ) . Both datasets were analyzed for population stratification using principle components analysis . The principle components ( PCs ) were calculated in Eigenstrat [57] and Tracy-Widom statistics were utilized to determine if the PCs were statistically significant . For those deemed significant ( TW p-value< = 0 . 05 ) , ANOVA F-statistics were calculated within the assigned populations ( either case/control for the first GWAS or black/light in the second GWAS ) to determine if the PCs divided the population based on the phenotype of interest . The SCCD case/control GWAS did not have evidence of population stratification by phenotype and was analyzed by calculating the allelic association ( Praw ) of each SNP with the disease using the statistical package PLINK v1 . 06 ( http://pngu . mgh . harvard . edu/purcell/plink/ ) [58] . Correction for multiple testing was performed using 100 , 000 MaxT permutations in PLINK ( Pgenome ) . The results of the MaxT permutations matched those obtained from Bonferroni correction at the 0 . 05 level . The GWAS comparing black/light coat colored STPOs did have evidence for population stratification by phenotype and the allelic association ( Praw ) of each SNP with the phenotype was performed using the program EMMAX to correct for population structure [59] . To correct for false positive associations due to multiple testing , phenotypes were randomly permuted and association was repeated 1000 times . Pgenome values were based on the number of permutations out of 1000 that produced an equal or lower result . The results of the EMMAX-based permutations also matched those obtained from Bonferroni correction at the 0 . 05 level . Over 1 , 268 amplicons were sequenced within the broad original genomic region ( CFA15:30 , 280 , 088–35 , 714 , 394 ) . Primers were designed using Primer3 v0 . 4 . 0 [60] . Primer sequences are available ( Table S1 ) . Amplification used standard PCR methods and sequencing was done using BigDye Terminator v3 . 1 on an ABI 3730xl DNA Analyzer ( Applied Biosystems , Life Technologies , Grand Island , NY ) . Sequences were analyzed using the Phred/Phrap/Consed software packages [61] , [62] , [63] and SNPs were identified using Polyphred [64] . Typically , 38 STPO cases and 30 STPO controls were resequenced . However , for a small proportion of the KITLG introns , the KITLG upstream region and the 144 . 9 Kb overlapping region , a set of six STPO cases and four STPO controls were resequenced . The ten samples were selected to represent the haplotypes in the region . Of the cases , two were homozygous for the risk haplotype , two were heterozygous and two were homozygous for the non risk haplotype . For the controls , three were heterozygous for the risk haplotype and one was homozygous for the non risk haplotype . Genotypes for the variants identified are available ( Table S1 ) . Recombination mapping was performed with 862 variants identified from resequencing 38 STPO cases and 30 STPO controls in a 1 . 2 Mb region surrounding the initial peak ( CFA15:31 , 900 , 000–33 , 100 , 000 ) . Seven new cases were enrolled subsequent to the initial GWAS for a total of 38 STPO cases . We evaluated only the 35 cases which shared at least one copy of the risk-associated allele at the peak SNP , CFA15:32 , 383 , 555 , for recombination mapping . In this analysis , a position was identified as the location of a recombination event if a case no longer shared at least one copy of the STPO case major allele ( i . e . homozygous for the STPO case minor allele ) . Additionally , the case needed to continue to be homozygous for the STPO case minor allele for more than one Kb . We set this requirement in order to take the most conservative approach , and to only identify persistent changes in the risk-associated haplotype pattern . We note that within the entire 1 . 2 Mb region only four variants were excluded as recombination events since the change in genotype did not persist for more than one Kb . For two variants , the minor allele only occurred in a subset of dogs with the risk haplotype indicating that these variants are likely mutations that arose on the haplotype after the causal variant . The other two variants were only 611 bp apart and the STPO case minor allele is the STPO control major allele . In this case , the association with disease is equally as strong , either centromeric or telomeric of these variants . As such , these two variants most likely resulted from a series of unique crossover events in different generations on the risk haplotype where we cannot unambiguously determine that the causal variant is within the centromeric or telomeric section . The additional association analysis compared all 38 STPO cases to 30 unrelated black STPO controls . Four controls were excluded since they did not have sufficient DNA . The allelic association was calculated for all 862 variants in a 1 . 2 Mb region surrounding the initial peak ( CFA15:31 , 900 , 000–33 , 100 , 000 ) . Since none of the variants with minor allele frequencies <10% were significant , the data was plotted with the 658 variants having minor allele frequencies >10% , for clarity ( Figure 3 ) . As with the GWASs , the allelic association of each variant with the disease phenotype was calculated using PLINK v1 . 06 . For the haplotype mapping comparing either Giant Schnauzer ( n = 28 ) or Briard cases ( n = 11 ) to the STPO cases ( n = 38 ) , we scanned the STPO three recombination interval ( CFA15:32 , 088 , 047–32 , 901 , 086 ) for the largest region of haplotype sharing . In the previous resequencing effort , either the Giant Schnauzer or Briard cases were sequenced with the STPO cases and controls . Variants from this resequencing were included in the interbreed haplotype analysis along with additional variants , which were then genotyped in either breed to make sure that there was a variant , on average , every 1500 bp . First , we started at the centromeric edge of the interval , CFA15:32 , 088 , 047 , and moved variant by variant through the interval . We identified variants where all Giant Schnauzer or Briard cases had at least one copy of the STPO case major allele ( i . e . where no Giant Schnauzer or Briard cases were homozygous for the STPO case minor allele ) . We then calculated the size of these intervals and the haplotypes within each interval were determined . If the haplotype started within the three recombination region , we included the area until the end of the haplotype sharing with STPO cases . Finally , the regions of interest were intervals where the Giant Schnauzer or Briard cases share at least one copy of the same haplotype as the majority of STPO cases ( >50% ) . Four SNPs , CFA15:32 , 724 , 674 , CFA15:32 , 749 , 603 , CFA15:32 , 795 , 285 and CFA15:32 , 832 , 982 , assumed to have arisen on the haplotype after the mutation or as the result of a series of unique crossover events in separate generations , disrupted the haplotype sharing between STPO , Giant Schnauzer and/or Briard cases , and were removed from future analyses . The LD block patterns in the 144 . 9 Kb overlapping region were determined with 186 variants in the STPO cases ( n = 38 ) and controls ( n = 30 ) using the Confidence Interval analysis in Haploview v4 . 1 [27] . Tagging variants ( SNPs or indels ) were selected to capture haplotypes predicted by Haploview . There were four SNPs to capture the six haplotypes in LD block A ( CFA15:32 , 782 , 292 G/A; CFA15:32 , 782 , 334 A/G; CFA15:32 , 796 , 712 T/C; CFA15:32 , 796 , 907 C/A ) , with the risk-associated haplotype being G/A/T/C at these SNPs , respectively . One SNP captured the two haplotypes in LD block B ( CFA15:32 , 854 , 334 ) , three SNPs captured the four haplotypes in LD block C ( CFA15:32 , 859 , 750 , CFA15:32 , 862 , 724 , CFA15:32 , 870 , 197 ) , and eight SNPs and indels captured the nine haplotypes in LD block D ( CFA15:32 , 871 , 555 , CFA15:32 , 876 , 284 , CFA15:32 , 880 , 662 , CFA15:32 , 887 , 141 , CFA15:32 , 888 , 465 , CFA15:32 , 888 , 492 , CFA15:32 , 898 , 733 , CFA15:32 , 899 , 461 ) . The nonradioactive DIG Southern blot system ( Roche Applied Science , Gilroy , CA ) was used to analyze the 5 . 7 Kb CNV . Briefly , 1–2 µg genomic DNA was digested with the PstI enzyme for 3 hours at 37°C . High molecular weight DNA was necessary for the assay . Samples were run at 30 volts for 16 hours on a 0 . 6% agarose gel in TAE buffer . A control that was heterozygous for the three and four copy alleles was run on every Southern . The bands on the Southern blot were the following sizes after digestion: 8 . 2 Kb , 13 . 9 Kb , 19 . 6 Kb , 25 . 3 Kb and 31 Kb for the one , two , three , four and five copy alleles , respectively . A subset of samples were sufficiently degraded such that interpretable results were not obtained . All owners of STPO cases were recontacted to provide additional saliva samples . Of the 37 STPO cases without Southern results , 29 had already passed away . For the remaining eight , we were unable to collect a high quality saliva sample . Ultimately , out of the 84 STPO cases that were attempted , Southern blot data was available for 47 ( 55 . 6% ) . We experienced similar results for the STPOs of control age . Blots were processed as specified by the DIG Southern blot system ( Roche Applied Science ) for hybridization targets ≥5 Kb . The probe was prepared using the PCR DIG Probe Synthesis kit ( Roche Applied Science ) with half DIG labeled dNTPs and half regular dNTPs in a two step PCR reaction ( 68°C annealing and extension temperatures ) with the following primers , CTGATTCACATTTCCAAGGTGACAATGA and ACATGGCAGAGAAAGGCAACTAAGACCT . The DIG labeled probe was quantitated on a 1% agarose gel by comparing the probe intensity with the intensity of the Low Mass Ladder ( Invitrogen , Carlsbad CA ) . The DIG Easy Hyb buffer ( Roche Applied Science ) was used for both the pre-hybridization and hybridization solutions . For hybridization , the probe concentration was 10 ng/ml . The low/high stringency washes and the DIG wash and block buffer set washes were performed according to the DIG protocol using CPD-star ( Roche Applied Science ) . Blots were exposed to X-ray film for 30 minutes to two hours depending on the intensity of the signals .
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Domesticated dogs offer a unique mechanism for disentangling complex genetic traits , such as cancer . Over 300 breeds exist worldwide , each selected for particular morphologic and behavioral traits . Unfortunately the breeding programs used to generate such diversity are associated with breed-specific increase in disease . Squamous cell carcinoma of the digit ( SCCD ) is a locally aggressive cancer that causes lytic bone lesions and , occasionally , death . Among the breeds with the highest risk is the Standard Poodle ( STPO ) , where the disease is found only in dark-coated dogs . We show that the KITLG locus is highly associated with SCCD and that a 5 . 7-Kb copy number variant is likely causative for the disease when in an expanded form . Interestingly , light-colored STPO carry the putative causal variant at the same frequency as black STPOs , but are protected from SCCD . We show this is likely due to a compensatory mutation in the well-known coat color locus , MC1R . This work demonstrates the utility of dog breeds for understanding the genetic causes of complex diseases of interest to both human and animal health .
|
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"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
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"genome-wide",
"association",
"studies",
"cancer",
"genetics",
"genetics",
"biology",
"genomics",
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2013
|
A Copy Number Variant at the KITLG Locus Likely Confers Risk for Canine Squamous Cell Carcinoma of the Digit
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Incorporating the cognate instead of non-cognate substrates is crucial for DNA polymerase function . Here we analyze molecular dynamics simulations of DNA polymerase μ ( pol μ ) bound to different non-cognate incoming nucleotides including A:dCTP , A:dGTP , A ( syn ) :dGTP , A:dATP , A ( syn ) :dATP , T:dCTP , and T:dGTP to study the structure-function relationships involved with aberrant base pairs in the conformational pathway; while a pol μ complex with the A:dTTP base pair is available , no solved non-cognate structures are available . We observe distinct differences of the non-cognate systems compared to the cognate system . Specifically , the motions of active-site residue His329 and Asp330 distort the active site , and Trp436 , Gln440 , Glu443 and Arg444 tend to tighten the nucleotide-binding pocket when non-cognate nucleotides are bound; the latter effect may further lead to an altered electrostatic potential within the active site . That most of these “gate-keeper” residues are located farther apart from the upstream primer in pol μ , compared to other X family members , also suggests an interesting relation to pol μ's ability to incorporate nucleotides when the upstream primer is not paired . By examining the correlated motions within pol μ complexes , we also observe different patterns of correlations between non-cognate systems and the cognate system , especially decreased interactions between the incoming nucleotides and the nucleotide-binding pocket . Altered correlated motions in non-cognate systems agree with our recently proposed hybrid conformational selection/induced-fit models . Taken together , our studies propose the following order for difficulty of non-cognate system insertions by pol μ: T:dGTP<A ( syn ) :dATP<T:dCTP<A:dGTP<A ( syn ) :dGTP<A:dCTP<A:dATP . This sequence agrees with available kinetic data for non-cognate nucleotide insertions , with the exception of A:dGTP , which may be more sensitive to the template sequence . The structures and conformational aspects predicted here are experimentally testable .
The integrity of genetic information depends largely on DNA polymerases that are central to DNA replication , damage repair , and recombination . DNA polymerase errors are associated with numerous diseases , including various cancers and neurological conditions [1]–[13] . One of the most basic types of errors that DNA polymerases generate is base substitution error , which means that DNA polymerase inserts an non-cognate ( “non-cognate” ) nucleotide opposite the DNA template base to form a nonstandard base pair ( i . e . , A:dATP base pair , instead of A:dTTP base pair ) . Although DNA polymerases conduct similar nucleotidyl transfer reaction and share a similar structure - palm , thumb and fingers subdomains [14] , they can exhibit varying levels of accuracy ( “fidelity” ) in inserting nucleotides [15] . DNA polymerase μ ( pol μ ) of the X-family , like the other X-family members , participates mainly in DNA repair rather than replication [16] . Like two other X-family members polymerase β ( pol β ) and polymerase λ ( pol λ ) , pol μ can bind to DNA and fill single-strand DNA gaps in a template-dependent manner with moderate fidelity ( 10−4–10−5 ) [17]–[19] . Furthermore , like another X-family member terminal deoxynucleotidyl transferase ( Tdt ) , pol μ can also perform nucleotide insertion in a template-independent manner [20] , [21] . In addition , pol μ can direct template-based DNA synthesis without requiring all upstream primer bases to be paired [17] , [22] . The unique substrate flexibility of pol μ may signal a unique role in the nonhomologous DNA end joining ( NHEJ ) process for double-strand breaks in DNA and V ( D ) J recombination [22]–[28] . Structural and computational studies have uncovered important differences and similarities regarding how pol μ incorporate a cognate nucleotide into single-nucleotide gapped DNA , compared to other X-family members [29] , [30] . For pol β , upon binding the cognate incoming nucleotide , the enzyme undergoes a large-scale protein motion in the thumb subdomain from open ( inactive ) to closed ( active ) conformation [31]–[33] . Such open-to-closed protein motion is also observed in pol X , another X-family polymerase [34] . Pol λ lacks such large-scale protein transitions; instead , a large shift of the DNA template from the inactive to the active state is indicated by both crystal structures [35] and simulations [36] . The large-scale protein motion in pol β and pol X or DNA motion in pol λ is crucial for the polymerization activity [31] , [37] , [38] . In pol μ , studies have suggested the lack of significant DNA or protein motion before chemistry [29] . Pol μ shares with pol β and pol λ the notion that subtle active-site protein residue motions help organize the conformation of the active site and prepare for the following chemical step [39] , but the specific residues are different [29] , [33] , [36] . In pol μ , His329 and Asp330 assemble pol μ's active site , and Gln440 and Glu443 help accommodate the incoming nucleotide . See Fig . 1 ( a ) and ( b ) for key residues and their motion in pol μ's cognate system . In prior mismatch studies on various X-family DNA polymerases such as pol β [40]–[45] , pol X [46] , and pol λ [47] , reduced large-scale protein ( pol β and pol X ) or DNA motions ( pol λ ) were observed , related to the inactivity of non-cognate systems . Varying amounts of active-site distortions are observed . Distortions of the active site are caused by the conformational changes of several key residues ( “gate-keepers” ) [40] , [47] . For example , in pol β , structural and dynamics analyses revealed different behavior of Arg258 , Asp192 , and Phe272 in non-cognate systems [40]–[43] . These residues distort the active site , with the degree of active-site distortions system-dependent and in accord with the sequence of kinetic data for non-cognate base pair incorporations . The different conformational behavior between the cognate and non-cognate systems before and/or after chemistry are also observed and are related to fidelity for DNA polymerases in other families [48]–[51] . From prior results , we further demonstrated that characteristic motions recur within various 2′-deoxyribonucleoside 5′-triphosphate ( dNTP ) contexts . Specifically , correlated protein and dNTP motions occur within cognate dNTP complexes and are altered within non-cognate dNTP complexes . We therefore proposed a hybrid conformational selection/induced-fit model for DNA polymerases [52] . In this model , the cognate dNTP selectively binds to a near-active conformation from an ensemble of possible polymerase/DNA conformations , and then the bound dNTP induces small adjustments within the active site , driving the complex to a fully-active state ready for catalysis . Non-cognate dNTPs that are relatively efficiently handled by the polymerase would also selectively bind to a near-active conformation , but the active-site changes induced by the non-cognate dNTP binding would differ from those by cognate dNTP binding . For non-cognate dNTPs that are relatively poorly inserted by the polymerase , dNTP may bind to a variable inactive conformation . The resulting incomplete organization of the active site would reduce the efficiency for inserting an non-cognate dNTP . This proposed broader view better reflects both the intrinsic motions of polymerases and the highly specific nature of polymerase/ligand interactions , and has gained further support from additional computations [53]–[57] ( Arora , Zahran , and Schlick , in preparation ) . Several key experimental studies of pol μ's fidelity exist [17] , [19] , but no structure of an non-cognate incoming nucleotide bound to pol μ has been reported . Modeling and all-atom dynamics simulations can help study the structural and dynamic properties of non-cognate pol μ systems , which in turn can be related to specific functions of pol μ . Needless to say , all dynamics simulation data are subject to the approximations and limitations of an empirical force field , limited sampling , and large computational requirements [58] . Yet , modeling and simulation have demonstrated many successes in biomolecular structure and function problems , and can be valuable especially when few experimental data are available [59] . In this study , we investigate dynamics of pol μ bound to various mismatches ( A:dCTP , A:dATP , A:dGTP , T:dCTP , and T:dGTP ) to determine the factors that contribute to insertion differences of pol μ during its conformational pathway before chemistry . We also analyze simulations of the bulky purine-purine mismatches with the template base in both the anti and syn orientations to determine whether particular base pair geometry might facilitate mismatch incorporation . We find that His329 and Asp330 near the active site help discriminate cognate from non-cognate incoming nucleotides . In addition , we suggest that Trp436 , Gln440 , Glu443 , and Arg444 play the role of “gate-keepers” in pol μ by tightening ( deactivating ) the nucleotide-binding pocket when non-cognate nucleotides are bound . Compared to pol β and pol λ , most of these residues are much farther from the upstream primer in pol μ . A comparison of the correlated motions in cognate and non-cognate pol μ systems indicates decreased interactions in non-cognate systems , especially those between the incoming nucleotides and the nucleotide-binding pocket , and suggests that pol μ also fits into the hybrid conformational selection/induced-fit model . As in pol β and pol λ , the degree of active-site distortion in pol μ mirrors trends in kinetic data , except for A:dGTP , which is more disordered and sequence-context dependent as indicated by kinetic data . Though the chemical step can also impact the fidelity of pol μ , the conformational pathway is a pre-requisite for chemistry [39] . Indeed , in non-cognate systems , the conformational pathway produces a deformed active site that is farther from the chemistry competent state . Thus , even if the chemical step is hindered in non-cognate systems , it is the distorted conformational pathway that leads to initial hindrance in the chemical pathway . Finally , we suggest that the ability of pol μ to incorporate nucleotides when the upstream primer is not paired may arise in part from the fact that most “gate-keeper” residues in pol μ are much farther from the upstream primer , compared to pol β and pol λ; thus , pol μ may be less sensitive to changes around the upstream primer .
Seven pol μ non-cognate models were prepared on the basis of the X-ray crystal murine pol μ cognate ternary complex ( PDB entry 2IHM ) [30] . In the crystal structure , two loops in the palm ( Loop1 , His366-Arg389; Loop2 , Pro397-Cys411 ) are partially missing . Missing protein residues His366-Val386 and Ala403-Ala405 were inserted with the InsightII package ( Accelrys Inc . , San Diego , CA ) . A hydroxyl group was added to the 3′ carbon of the 2′ , 3′-dideoxythymidine 5′-triphosphate ( ddTTP ) sugar moiety to form 2′-deoxythymidine 5′-triphosphate ( dTTP ) . All other missing atoms from the crystal structure were similarly added . The Na+ occupying the catalytic ion site in the crystal structure was modified to Mg2+ . In our previous study on pol μ cognate system [29] , we observed that different protonation states of His329 do not affect the geometry of active site or the conformation of key residues significantly . Therefore , in this study , we only modeled His329 in its default protonation state ( Nδ ) . In each model , the A:dTTP nascent base pair was replaced with a different non-cognate base pair; namely , A:dCTP , A:dATP , A:dGTP , T:dCTP , or T:dGTP ( the template base's symbol is written first , followed by the incoming nucleotide's symbol ) . Purine bases can assume both anti and syn orientations . Because a crystal structure of pol β with a template base in syn conformation has been reported [60] , we modeled the template adenine in the A:dATP and A:dGTP systems in both orientations . The protein residues and other DNA base sequences remain unchanged . We also built a cognate T:dATP system to discern similarities of cognate base pairs . All models were solvated with explicit TIP3 water model in a water box using the VMD program [61] . The smallest image distance between the solute and the faces of the periodic cubic cell was 7 Å . Besides the water molecules in the crystal structure , 13 , 625 water molecules were added into each model using VMD program . The total number of water molecules is 13 , 716 . To obtain a neutral system at an ionic strength of 150 mM , 46 Na+ and 28 Cl− ions were added to each system . All of the Na+ and Cl− ions were placed at least 8 Å away from both protein and DNA atoms and from each other . All initial models contained approximately 47 , 621 atoms , 91 crystallographically resolved water molecules from the ternary complex , 13 , 625 bulk water molecules , 2 Mg2+ ions , incoming nucleotide dNTP , and 46 Na+ and 28 Cl− counter-ions . Initial energy minimizations and equilibration simulations were performed using the CHARMM program ( version c35b2 ) [62] with the CHARMM all-atom force field including the cross term energy correction map ( CMAP ) specification for proteins [63]–[65] . The system was minimized with fixed positions for all heavy atoms of protein or nucleotides , using SD for 10 , 000 steps followed by ABNR for 20 , 000 steps . Then the atoms of added residues ( His366-Val386 and Ala403-Ala405 ) and non-cognate nucleotide base-pair were released . Another cycle of minimization was performed for 10 , 000 steps using SD followed by 20 , 000 steps of ABNR . The equilibration process was started with a 100 ps simulation at 300 K using single-time step Langevin dynamics , while keeping all the heavy atoms of protein or nucleotides fixed . The SHAKE algorithm [66] was employed to constrain the bonds involving hydrogen atoms . This was followed by unconstrained minimization consisting of 10 , 000 steps of SD and 20 , 000 steps of ABNR . The missing loop construction was performed using the program NAMD [67] with the CHARMM force field . All protein or DNA atoms were fixed , except those from the added residues ( His366-Val386 and Ala403-Ala405 ) and the non-cognate base-pair in order to relax the added loop , the non-cognate base-pair , and the water around our complexes . Each system was equilibrated for 1 ns at constant pressure and temperature . Pressure was maintained at 1 atm using the Langevin piston method [68] with a piston period of 100 fs , a damping time constant of 50 fs and a piston temperature of 300 K; the temperature was maintained at 300 K using weakly coupled Langevin dynamics of non-hydrogen atoms with a damping coefficient of 10 ps−1 . Bonds to all hydrogen atoms were kept rigid using SHAKE , permitting a time step of 2 fs . The system was simulated in periodic boundary conditions with full electrostatics computed using the PME method [69] with grid spacing on the order of 1 Å or less . Short-range non-bonded terms were evaluated at every step using a 12 Å cutoff for van der Waals interactions and a smooth switching function . Molecular dynamics at a constant temperature and volume for 4 ns were followed , using the same constraints as above . The final dimension of each system is approximately 78 . 95 Å × 74 . 61 Å × 79 . 91 Å . The model of the A:dCTP system is shown in Fig . 1 ( c ) as an example . In prior study , we found that the conformation of the added Loop1 does not affect the behavior of pol μ system significantly [29] . In addition , Loop1 is far away from the active-site region we are interested in . Therefore , we only modeled one conformation of Loop1 for all systems . Production dynamics were also performed using the NAMD program with the CHARMM force field . In all trajectories , all heavy atoms were free to move . Each simulation was run for 120 ns . Molecular dynamics simulations using the NAMD package were run on the IBM Blue Gene/L at Rensselaer Polytechnic Institute and the Dell computer cluster at New York University .
No substantial protein subdomain or DNA motions were captured during all our non-cognate simulations ( Fig . S1 ) . This agrees with our prior suggestion that unlike pol β or pol λ , an open-to-closed transition characterized by large-scale protein or DNA motions may not exist in pol μ [29] . Due to the larger size of dGTP and dATP than that of the cognate dTTP , the template base A5 at the gap pairing with dNTP shifts from its original position significantly ( at 95% confidence level , Fig . S1 ( b ) and Fig . S2 ) in A:dGTP and A:dATP non-cognate systems , to better accommodate the incoming nucleotide . In the A:dCTP system , dCTP is relatively smaller , therefore dCTP can be accommodated without the shift of A5 . However , the shift of the single base A5 does not incur wide range movements in DNA backbones of pol μ complexes . This agrees with our prior work that pol μ binds to the DNA more tightly than pol λ [29] . Active sites in the non-cognate systems are significantly distorted compared to those in the cognate systems because the Watson-Crick base-pair between the incoming nucleotide and its corresponding template base no longer exist ( Fig . 2 ) . New hydrogen bonds between those two bases form ( directly , or through a water molecule in T:dCTP system ) . However , these new hydrogen bonds are less stable than those in the Watson-Crick base pair . In addition , the steric hindrance between the two large purine bases in purine:purine non-cognate systems like A:dATP and A:dGTP further destabilize their interactions . Thus , the nucleotide fluctuates substantially within the active site , indicating a lower active-site conformational stability . In the A:dATP and A ( syn ) :dATP systems , the non-cognate dATP interacts with both A5 and A6 in the template , without breaking the hydrogen bonds between A6 and the primer terminus T17 . Thus , dATP stacks between A5 and A6 during the simulation . A similar nucleotide-stacking was also observed in pol λ's A ( syn ) :dATP system . However , in pol λ , a positively-charged residue ( Lys273 ) near A5 attracts A5 further away from dATP and stabilizes the DNA backbone , thereby shifting the DNA backbone [47] . In contrast , pol μ's negatively-charged Glu173 at the corresponding position “pushes” A5 back and keeps the DNA backbone near to its original position . As a result , the following shift of DNA backbone in pol λ's A ( syn ) :dATP system does not occur in pol μ's A:dATP or A ( syn ) :dATP systems . The geometry of the active-site conformation in each system is shown in Fig . 3 , and the critical distances in the active site are summarized in Table 1 . The cognate A:dTTP and T:dATP systems share a similar active-site conformation: two water molecules coordinate with the catalytic Mg2+ ion ( A ) . Mg2+ ( A ) connects with the primer terminus through two water molecules , and connects with the incoming nucleotide both directly and through a water molecule . Thus , the active site is relatively tight and appears ready for the chemical reaction . In the A:dGTP , A ( syn ) :dATP , and T:dGTP non-cognate systems , few rearrangements in the active-site geometry occur . Mg2+ ( A ) connects to both the incoming nucleotide and the primer terminus through two water molecules , and the catalytic aspartate residues remain in their active conformation . The T:dCTP system has a similar active-site geometry in the beginning of simulation , but after 75 ns , O1A in the dCTP shifts away from the nucleotide-binding Mg2+ ion ( B ) . After the shift , Mg2+ ( B ) coordinates with O in Asp330 . Other coordination interactions in the T:dCTP system remains the same as the cognate system . In a prior study of cognate pol μ systems , we found that His329 is the most sensitive residue to the absence or presence of incoming nucleotide . Its conformational change triggers the flip of the catalytic aspartate residue Asp330 , thus contributing to the assembly of the active site [29] . In the A:dCTP system , His329 flips to an alternative conformation within 10 ns [Fig . S3 ( a ) ] . In the new conformation , His329 does not fully “open” to the inactive conformation , though still interrupts binding with dCTP . His329 further flips to its inactive “open” conformation but then flips back to the alternative conformation . Following the flip of His329 , Asp330 rotates to an alternative conformation , where both OD1 and OD2 on Asp330 coordinate with Mg2+ ( A ) . As a result , Mg2+ ( A ) coordinates with only one water molecule instead of two , and its connection with the primer terminus through water molecules weakens . Interestingly , the distance between and O1A on dCTP is significantly smaller than that in cognate A:dTTP system . However , O1A in the dCTP shifts away from Mg2+ ( B ) , and Mg2+ ( B ) coordinates with O in Asp330 , just as in the T:dCTP system . In the A:dATP system , His329 also flips , but this is only followed by a slight rotation of Asp330 [at an 80% significance level , Fig . S3 ( b ) ] . The coordination around Mg2+ ( B ) remains the same . Asp420 rotates toward Mg2+ ( A ) , and Mg2+ ( A ) coordinates with both OD1 and OD2 on Asp420 . Due to attraction by Asp420 , Mg2+ ( A ) shifts away from dATP , no longer able to directly coordinate with O1A on dATP , though it still interacts with O1A through a water molecule . Though Mg2+ ( A ) directly coordinates with the primer terminus T17 , the distance between Mg2+ ( A ) and O3′ in T17 is significantly larger than that in the cognate system . In fact , the distance between O3′ in T17 and Pα in dATP is more than 8 Å ( compared to ∼5 Å in the cognate system , Fig . S4 ) , significantly larger than the optimal distance for chemical reaction . Again , distortion in the active site in the A:dATP system can be correlated to inactivity . The A ( syn ) :dGTP system also has a significantly larger O3′ - Pα distance . Like in A:dATP system , Mg2+ ( A ) also deviates from O1A in the incoming nucleotide , interacting with it only through a water molecule . Three water molecules coordinate with Mg2+ ( A ) instead of two in the cognate system . Because the third water molecule coordinate with neither the primer terminus nor the incoming nucleotide , interactions within the active site weaken overall . The three aspartate residues and His329 all remain in their active conformation . In the A:dCTP , A:dATP , and A ( syn ) :dGTP systems , water-mediated hydrogen bonds are generally weaker than direct hydrogen bonds in cognate systems . Therefore , active sites in those non-cognate systems have weaker internal interactions and thus may be more likely to deform . We observe that even in the cognate system , the crucial O3′ - Pα distance ( ∼5 Å ) appears to be longer than that is required for the chemical reaction ( ∼3 Å ) [70] , and also longer than the O3′ - Pα distance in the crystal structure ( ∼4 Å ) . Similar observations have been noted and discussed for various pol X family members [33] , [36] . Such deviations likely occur because of the imperfection of force fields . For example , the energetics of divalent ions like Mg2+ are considered in the van der Waals ( described by the phenomenological Lennard-Jones potential ) and Coulombic interactions . Thus , while data generated for divalent ions with these force fields are generally useful and informative , ligand/ion distances may differ from those observed in high resolution x-ray crystal structures . Nonetheless , because our study focuses on general trends in Mg2+ ion coordination and involves systematic comparisons of the trends among closely-related systems , the above limitations are acceptable . Recent crystallographic studies also reveal that the O3′ - Pα distance may be much longer than the expected value [51] . In all the cognate and non-cognate systems we studied , the sugar puckers at the upstream primer and the dNTP remain in the C2′-endo state during our simulations . Further rearrangements occur in the non-cognate systems that increase active-site disorder . A summary of residue rearrangements involved in each non-cognate system are provided in Table 2 and Fig . 4 . In the cognate system of pol μ , a cognate incoming nucleotide triggers the rotation of Gln440 and Glu443 , and this “loosens” the nucleotide-binding pocket and helps accommodate the incoming nucleotide . When an non-cognate nucleotide is present , Glu443 flips to an inactive state , thus “tightening” the nucleotide-binding pocket and deactivating the active site . Following the flip , Glu443 may interact with the non-cognate nucleotide through water molecules in several non-cognate systems , though the water-bridged interactions are dynamic . Interestingly , after the flip , the distance between Glu443 and the nucleotide does not decrease ( Fig . S5 ) . Thus , the deactivation effect of Glu443's flip may be due to an electrostatic effect rather than the steric hindrance . We discuss this further in the next section . We hypothesize that a mutation of Glu443 to a residue with similar length but neutral charge ( for example , methionine ) may reduce the fidelity of pol μ . Such an E443M substitution may reduce the catalytic ability for both cognate and non-cognate systems , but the cognate system may be affected more . Thus , the fidelity of the E443M mutant may decrease . This hypothesis may be tested by further experimental and computational studies . The motion of Gln440 is more flexible . Without dNTP , Gln440 flips to its inactive form and binds to the primer terminus . In the non-cognate systems , Gln440 cannot bind to the primer terminus because of the hindrance , and therefore it cannot reach a stable inactive nor active state . When we plot the distance between the center of mass of Gln440 and the center of mass of dNTP in Fig . S6 ( a ) , we see that in the A ( syn ) :dGTP and T:dGTP systems , Gln440 is significantly closer to the incoming nucleotide than in the cognate systems ( computed with the data from the last 40 ns , at a confidence level of 90% and 85% , respectively ) . In the A:dCTP and A:dGTP systems , Gln440 also displays a tendency to shift towards dNTP . The average distance between Gln440 and dNTP decreases for 0 . 44 Å and 0 . 62 Å over the simulation in A:dCTP and A:dGTP systems , respectively . In contrast , overall change is only 0 . 02 Å in the cognate A:dTTP system . Therefore , Gln440 also participates in “tightening” the active site by shifting towards the non-cognate nucleotide . These two residues are not conserved in pol β or pol λ , and thus must be unique to pol μ function . As its corresponding residue Arg514 in pol λ , Arg444 in pol μ mainly helps stabilize the template base at the gap through stacking interactions [29] , [36] . It also stabilizes Gln440 in its active conformation by hydrogen bonding to it . However , unlike Arg514 in pol λ , Arg444 in pol μ does not participate in the conformational change of active site upon binding a cognate nucleotide . Because of the distortion in the mispaired bases , the stacking interactions are interrupted in non-cognate systems . Therefore , Arg444 flips away from the active site in all non-cognate systems except A ( syn ) :dGTP and T:dGTP [Fig . S7 ( a ) ] . The flip of Arg444 increases the flexibility of Gln440 because the hydrogen bond between Arg444 and Gln440 breaks . However , the flip of Arg444 does not necessarily cause the shift of Gln440 towards the non-cognate dNTP . In addition , because Arg444 binds to the backbone of the template base A5 , its conformational change may also induce the shift of A5 away from the active site . Trp436 in pol μ is analogous to Phe272 in pol β , or Phe506 in pol λ , residues that initiate DNA or subdomain motions through a flip during the conformational transition of the polymerase complex [33] , [36] . When pol μ incorporates a cognate nucleotide , no significant motion of Trp436 is observed because DNA or subdomain motion is not part of pol μ's conformational pathway . However , in the A ( syn ) :dGTP system , Trp436 rotates its indole ring towards dGTP [Fig . S7 ( b ) ] . The rotation of Trp436 limits the space in the active site and pushes the dGTP away from the active site , thereby also “tightening” the nucleotide-binding pocket . We observe a similar rotation occasionally in the A:dCTP system toward the end of the simulation . Arg447 in pol μ is analogous to Arg283 in pol β and Arg517 in pol λ , both important for checking the cognate base-pairing [47] , [71]–[73] . Arg517 in pol λ is also crucial in pol λ's ability to accommodate frame-shifted DNA [74] . This arginine binds to both the base at the gap and the one pairing with primer terminus in the template DNA , and stabilizes DNA in the closed form of complex . However , in pol β and pol λ , this binding is sensitive to the incoming nucleotide context . When an non-cognate nucleotide is present and the active site is distorted by abnormal base pairing , fewer direct hydrogen bond interactions between Arg283 ( in pol β ) and Arg517 ( in pol λ ) with the DNA occur [41] , [47] . This leads to the poor stabilization of the DNA template bases , which incurs further rearrangements of incoming nucleotides and/or shift of DNA backbone . In contrast , in pol μ , the binding of Arg447 to DNA is not affected significantly by the non-cognate nucleotides . The direct hydrogen bonding of Arg447 - A6:N3 and Arg447 - A6:O4′ , as well as Arg447 - A6:O1P interaction through a water molecule , are present in all non-cognate systems . Arg447 - A5:N3 or Arg447 - T5:O2 interaction is also present in all systems except A ( syn ) :dATP and A ( syn ) :dGTP , where the syn conformation of A5 keeps N3 away from Arg447 . In T:dGTP system , Arg447 - T5:O2 interaction is not stable . The hydrogen bond between them does not form until after 90 ns , and deforms near the end of our 120 ns simulation [Fig . S6 ( b ) ] . However , in the A ( syn ) :dGTP and T:dGTP systems , Arg444 does not flip and stacks with A5 or T5 . Thus , the mispaired bases are still stable , and further rearrangements or motions caused by the lack of Arg447 interactions are not observed . This may suggest that pol μ's active site is more flexible than those in pol β and pol λ , so it might better accommodate the non-cognate nucleotide without breaking Arg447/DNA interactions . The flexibility of active site also supports the observation that pol μ can accommodate and insert ribonucleotides in the active site [75] . Motions of “Gate-keeper” residues , namely the flip of Glu443 , shifting of Gln440 , flip of Arg444 , and rotation of Trp436 , are not observed in our modeled cognate T:dATP system . This further confirms that “gate-keeper” residues can help discriminate non-cognate nucleotides from cognate ones and thus may have a significant role in controlling the fidelity of pol μ . Three of the four “gate-keeper” residues in pol μ ( Gln440 , Glu443 , and Arg444 ) are located apart from the upstream primer ( >8 Å ) and near the downstream primer; Trp436 , which is near the upstream primer , functions as “gate-keeper” residue in only one non-cognate system ( A:dGTP ) . In comparison to other X-family members , both “gate-keeper” residues in pol β ( Arg258 and Phe272 ) , as well as two of three “gate-keeper” residues in pol λ ( Tyr505 and Phe506 ) , are located near the upstream primer ( <6 . 5 Å , Fig . 5 ) . This difference may be related to the fact that pol μ can incorporate and insert the incoming nucleotide when the upstream primer is not paired . That is , pol μ may be less sensitive to changes around the upstream primer . Residue flexibility differences when the upstream primer is not paired may be interesting to explore in future computational and experimental studies of pol μ . Using the number of dNTP and protein residue changes in Table 1 and Table 2 , we suggest the following sequence for difficulty of nucleotide incorporation by pol μ: T:dGTP<A ( syn ) :dATP<T:dCTP<A:dGTP<A ( syn ) :dGTP<A:dCTP<A:dATP ( T:dGTP is the easiest to incorporate and A:dATP is the most difficult ) . This sequence agrees with the observed trends in the reaction kinetics data for nucleotide insertion [17] , [18] , as summarized in Table 3 , with the exception of A:dGTP , which may depend sensitively on the surrounding sequence [76] . For example , kinetic data obtained with another DNA sequence [19] suggests a different trend: T:dCTP<A:dCTP<T:dGTP<A:dATP<A:dGTP . Another possible explanation for our observing greater difficulty in the A:dGTP mispair relative to T:dCTP and T:dGTP while kinetic data indicate that A:dGTP is more favorable is that T:dCTP and T:dGTP mispairs are less favorable overall for chemical reaction following the conformational changes , as discussed below . We further examine in Fig . 6 the electrostatic potential of pol μ's active site with the cognate A:dTTP and T:dATP base pairs and various non-cognate systems . Unfavorable protein/dNTP interactions emerge in the non-cognate systems that destabilize the dNTP . Though subtle differences exist , the active site in pol μ's cognate A:dTTP and T:dATP systems have mainly negative ( red ) electrostatic potential , whereas the non-cognate systems have more neutral ( white ) or positive ( blue ) electrostatic potentials . Interestingly , for pol λ , changes in electrostatic potential are also observed , but in an opposite way: more neutral or positive for the cognate system , and more negative for the non-cognate system [47] . The changes in electrostatics environments suggest altered interactions within the active site , which in turn affect active-site rearrangements . In the A:dCTP system , Arg447 ( green circle in Fig . 6B ) appears in a negatively charged region , thus its stabilization effect to DNA template base A5 and A6 weakens , which in turn may destabilize the dCTP and primer terminus pairing with A5 and A6 . In A:dATP and A ( syn ) :dATP system , following the flip of Glu443 , the region near N1 and N3 atoms of dATP becomes more negative ( pink circle in Fig . 6C and 6D ) , while the region near the amino group of dATP is relatively more positive ( cyan circle in Fig . 6C and 6D ) . These two disruptive forces together destabilize dATP and drive it towards the primer terminus direction , allowing dATP to stack between A5 and A6 . Moreover , in the A:dCTP , T:dCTP , and T:dGTP systems , the end of the phosphate group on dNTP falls into a mainly positive region ( cyan circle in Fig . 6B , 6H , and 6I , compared to pink circle in the cognate systems , Fig . 6A and 6G ) , which is unfavorable for the proton transfer reaction to follow . Therefore , not only does the altered electrostatic potential around dNTP disturb the conformational rearrangements in active site , but it also may it affect the chemical step after the conformational changes . In prior work we studied the coupled conformational changes within polymerase complex upon binding a cognate or non-cognate incoming nucleotide for pol λ , pol β , and pol X [52] . Similar coupled motions within the same subdomain , among different subdomains , and between protein and DNA/dNTP , were revealed across the X family . Even within the same subdomain , the coupled regions can be distant in space . These correlated motions together drive the polymerase towards its active form . When an non-cognate nucleotide is bound , such correlated motions decrease . Correlated motions in pol μ system are shown in Fig . 7 . The cognate system of pol μ displays a similar network of coupled motions as pol β and pol λ , but with fewer interactions . Specifically , within the palm subdomain , correlated motions are observed among three regions as follows ( region A in Fig . 7 ) : a conserved X-family loop [77] ( Thr314-Thr336 ) containing two of the three catalytic aspartates ( Asp330 and Asp332 ) with a region ( Thr288-Val290 ) near the finger including Pro289 ( its analogous residue Arg149 in pol β or Arg346 in pol λ binds with the incoming nucleotide , though Pro289 in pol μ does not has such binding ability ) ; the Asp loop with the Loop 2 ( Ala407-Lys417 ) that is apart from the active site; and the Pro289 region with the Loop 2 . Gly435-Arg444 in the thumb that includes the nucleotide-binding pocket residues Gly435 , Trp436 , Gln440 , Glu443 , and Arg444 , also correlate with the Asp loop and Pro289 region in the palm ( region B ) . All these regions in the palm and thumb are further correlated to the dTTP ( region C ) . Non-cognate systems of pol μ generally have less correlated motions than the cognate system . In all the three non-cognate systems , the correlated motions between Gly435-Arg444 and the dTTP , and those between Gly435-Arg444 and Pro289 region are greatly reduced or missing . The A:dGTP system has the least changes of coupled motions , and is most similar to the cognate A:dTTP system . In the A:dCTP system , more intense motions correlated within the fingers are observed . The correlated motions between the polymerase fingers and 8-kDa domain , and between the fingers and DNA also increase . These motions may suggest that pol μ requires more conformational rearrangements in the finger when accommodating dCTP . With these additional conformational changes , pol μ deviates from its active conformation . The A:dATP non-cognate system is the most different of the three , compared to the cognate system . Correlated motions between the Asp loop and Gly435-Arg444 are reduced significantly . Because both the Asp loop and Gly435-Arg444 are within the active site , the reduced interactions among active-site residues largely hamper the orchestration of cooperative events to reach at an optimal active-site conformation . Almost all other correlated motions in the A:dATP system also appear reduced . The limited correlated motions suggest that A:dATP system remains in an inactive . Overall , our correlated motion analysis suggests an order of A:dTTP≈A:dGTP>A:dCTP>A:dATP for the degree of correlated motions . This order also agrees with the trend we suggested above from active-site distortion and key residue motion . We further present the difference matrices between the A:dTTP cognate system and the A:dATP/A:dCTP/A:dGTP non-cognate systems in Fig . S8 . Within the three systems , the correlated motion of A:dGTP system is most similar to that of the cognate A:dTTP system , suggesting a more favorable active site for the following chemical step . This may explain the high misincorporation rate of A:dGTP observed in experiments ( Table 3 ) . These results provide further support for the hybrid conformational selection/induced-fit model for polymerases: before substrate binding , the polymerase/DNA complex adapts a series of possible conformations , and substrate binding stabilizes specific conformation . This inherent flexibility is evident from Fig . S9 , which reveals the correlated motions when the substrate ( dNTP ) is absent . From this ensemble of conformations , in the A:dTTP cognate system , dTTP would selectively bind to a near-active conformation and guide the system into a fully active form as well as trigger required active-site changes . In the relatively active A:dGTP system , dGTP would also selectively bind to a near-active conformation with correlated motions similar to those in A:dTTP system . However , the suboptimal fit of dGTP within the active site induces active-site changes that differ from that in A:dTTP system . In the A:dCTP and A:dATP systems , the dNTPs bind to variable conformations of pol μ that deviate from the active forms; those tailored fits , however , hamper correlated motions that are essential for preparing the enzyme for subsequent catalysis .
Our molecular dynamics simulations of pol μ cognate and non-cognate systems reveal significant differences in the active site and regarding the correlated motions upon binding an non-cognate nucleotide compared to a cognate substrate . The results suggest that , compared to pol β or pol λ , no significant changes in global motion of protein or DNA would occur for pol μ . His329 and Asp330 in the active site , as well as Trp436 , Gln440 , Glu443 , and Arg444 in the nucleotide-binding pocket , play the role of “gate-keeper” in pol μ . These residues alter the electrostatic potential in the active site and trigger the distortion of active site when an non-cognate nucleotide is bound . Because most “gate-keeper” residues in pol μ are relatively far from the upstream primer , this fact may explain in part pol μ's ability to incorporate nucleotides when the upstream primer is not paired . Furthermore , in non-cognate systems , correlated motions within the complex are reduced . These results suggest that like other X-family polymerase , pol μ also fits in a hybrid conformational select/induced-fit model; the cognate substrate would bind to the active form and trigger active-site changes , while non-cognate substrates with relative high efficiency would bind to an active form but not trigger the following active-site changes , and non-cognate substrates with poor efficiency would bind to variable conformations . The degree of active-site geometry distortion determined from our simulations roughly parallels the kinetic data , suggesting a direct relation between active-site structural distortions and fidelity of pol μ . We also suggest experimentally testable predictions that mutation on pol μ's “gate-keeper” residues , like E443M , may reduce the fidelity of pol μ .
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DNA polymerase μ ( pol μ ) is an enzyme that participates in DNA repair and thus has a central role in maintaining the integrity of genetic information . To efficiently repair the DNA , discriminating the cognate instead of non-cognate nucleotides ( “fidelity-checking” ) is required . Here we analyze molecular dynamics simulations of pol μ bound to different non-cognate nucleotides to study the structure-function relationships involved in the fidelity-checking mechanism of pol μ on the atomic level . Our results suggest that His329 , Asp330 , Trp436 , Gln440 , Glu443 , and Arg444 are of great importance for pol μ's fidelity-checking mechanism . We also observe altered patterns of correlated motions within pol μ complex when non-cognate instead of cognate nucleotides are bound , which agrees with our recently proposed hybrid conformational selection/induced-fit models . Taken together , our studies help interpret the available kinetic data of various non-cognate nucleotide insertions by pol μ . We also suggest experimentally testable predictions; for example , a point mutation like E443M may reduce the ability of pol μ to insert the cognate more than of non-cognate nucleotides . Our studies suggest an interesting relation to pol μ's unique ability to incorporate nucleotides when the upstream primer is not paired .
|
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"Abstract",
"Introduction",
"Materials",
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"Methods",
"Results/Discussion",
"Conclusion"
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"computational",
"chemistry",
"molecular",
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2013
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“Gate-keeper” Residues and Active-Site Rearrangements in DNA Polymerase μ Help Discriminate Non-cognate Nucleotides
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During development , the Drosophila wing primordium undergoes a dramatic increase in cell number and mass under the control of the long-range morphogens Wingless ( Wg , a Wnt ) and Decapentaplegic ( Dpp , a BMP ) . This process depends in part on the capacity of wing cells to recruit neighboring , non-wing cells into the wing primordium . Wing cells are defined by activity of the selector gene vestigial ( vg ) and recruitment entails the production of a vg-dependent “feed-forward signal” that acts together with morphogen to induce vg expression in neighboring non-wing cells . Here , we identify the protocadherins Fat ( Ft ) and Dachsous ( Ds ) , the Warts-Hippo tumor suppressor pathway , and the transcriptional co-activator Yorkie ( Yki , a YES associated protein , or YAP ) as components of the feed-forward signaling mechanism , and we show how this mechanism promotes wing growth in response to Wg . We find that vg generates the feed-forward signal by creating a steep differential in Ft-Ds signaling between wing and non-wing cells . This differential down-regulates Warts-Hippo pathway activity in non-wing cells , leading to a burst of Yki activity and the induction of vg in response to Wg . We posit that Wg propels wing growth at least in part by fueling a wave front of Ft-Ds signaling that propagates vg expression from one cell to the next .
Growth is a fundamental property of animal development . Under normal conditions , animals of a given species , as well as their various body parts , achieve a characteristic size , shape , and pattern under tight genetic control . However , the basis of this control is poorly understood . Morphogens , such as secreted factors of the Wingless/Int ( Wnt ) , Bone Morphogenetic Protein ( BMP ) , and Hedgehog ( Hh ) families , control growth . For example , in the classic paradigm of the Drosophila wing , the morphogens Wingless ( Wg , a Wnt ) and Decapentaplegic ( Dpp , a BMP ) drive a rapid ∼200-fold increase in cell number and mass that occurs during larval life [1] , [2] , [3] , [4] , [5] . Removal of either morphogen results in truncated wings [4] , [5] , [6] , [7] . Conversely , their ectopic expression induces supernumerary wings [1] , [2] , [4] , [5] , [8] . Another system involved in growth is the evolutionarily conserved Warts-Hippo tumor suppressor pathway [9] , [10] , [11] , [12] . This pathway includes the Warts ( Wts ) and Hippo ( Hpo ) kinases , the FERM domain proteins Expanded ( Ex ) and Merlin ( Mer ) , and the accessory proteins Salvador ( Sav ) and Mob-as-tumor-suppressor ( Mats ) . All of these proteins limit growth by mediating the phosphorylation and cytosolic retention of the transcriptional co-activator Yorkie ( Yki ) /YES Associated Protein ( YAP ) [9] , [11] , preventing Yki from up-regulating genes that promote growth [9] , [13] , [14] . In Drosophila , two protocadherins , Dachsous ( Ds ) and Fat ( Ft ) , have been implicated as a ligand-receptor pair that acts , via the atypical myosin Dachs ( D ) , to regulate Wts kinase activity [11] , [15] , [16] , [17] , [18] , [19] . Previous studies have shown that morphogens such as Wg , Dpp , and Hh direct the formation of opposing , tissue-wide gradients of Ds and Ft activity [20] , [21] , [22] , [23] , [24] . Further , it has been proposed that the differential ( i . e . , slope ) of Ds-Ft signaling across each cell sets the level of Wts activity and thereby governs the rate of growth and division on a cell-by-cell basis [24] , [25] ( see also [26] ) . In support , experiments that create sharp disparities in morphogen receptor activity or Ds-Ft signaling down-regulate Wts-Hpo activity and induce abnormal growth [24] , [25] , [27] . Conversely , experiments that flatten Ds-Ft signaling ( e . g . uniform over-expression of Ds ) suppress growth [22] , [24] , [25] , [28] . Ft and Ds are also important for planar cell polarity ( PCP ) , in which cells within epithelial sheets adopt a common orientation , e . g . as manifest by their secreting hairs that point in the same direction [20] , [21] , [29] , [30] , [31] . In this case , the ligand-receptor relationship between the two proteins appears more complex [23] , [32] . Cells that express only Ds or only Ft can polarize their neighbors , whereas cells that lack either Ds or Ft cannot respond to their neighbors . Hence , in PCP , Ds and Ft each have intrinsic signaling activities , and both are required to receive and transduce each signal [23] , [32] . Recently , we defined a new mechanism for the control of Drosophila wing growth by morphogen [33] , [34] . Focusing on Wg , we showed that morphogen propels growth at least in part by fueling a reiterative process of recruitment of non-wing cells into the wing primordium . Recruitment depends on a special , auto-regulatory property of vestigial ( vg ) , the selector gene that defines the wing state [35] . This is the capacity of vg expressing cells to send a feed-forward ( FF ) signal that induces neighboring cells to activate vg in response to Wg [33] , [34] . Early in larval life , specialized “border” cells along the boundary between the dorsal ( D ) and ventral ( V ) compartments are induced to express Vg and secrete Wg . These cells initiate the FF recruitment process , which then reiterates , propagating vg expression from cell to cell in response to Wg spreading from the border cells . In our initial analysis of the recruitment process , we speculated that Ft and Ds might be involved in the FF mechanism [33] . Here , we confirm this speculation and show that Ft is required for cells both to send and , together with Ds , to receive the FF signal , concordant with the dual ligand and receptor activities of both proteins in PCP . Further , we show that Ft and Ds transduce the FF signal via D , the Wts-Hpo pathway , and Yki to activate vg expression and initiate a new cycle of FF signaling . Based on these findings , we posit that Wg ( and likely Dpp ) promote wing growth by fueling the propagation of a wave front of Ft-Ds signaling that transiently suppresses the Wts-Hpo pathway and elevates Yki activity to recruit new cells into the wing primordium .
The main phase of wing growth begins early in larval life with the segregation of the prospective wing primordium into D and V compartments [36] , [37] , [38] . Short-range Notch signaling across the D-V boundary activates the vg Boundary Enhancer ( BE ) to generate a stripe of vg expressing “border cells” [35] , [39] . It also induces border cells to secrete Wg [40] , [41] , [42] , which activates and sustains vg expression in surrounding cells via the vg Quadrant Enhancer ( QE ) ( Figure 1A , 1B ) [4] , [5] , [33] , [34] , [35] , driving the rapid increase of the wing primordium from a population of ∼25–50 cells to one of ∼5 , 000–10 , 000 cells . D-V compartmentalization depends on the heritable activation of the selector gene apterous ( ap ) in D , but not V , cells [36] , [43] . In ap null discs ( henceforth apo discs ) , the D-V segregation fails , vg and wg expressing border cells are not specified , and the nascent wing primordium is subsequently lost ( Figures 1C , 2B ) . However , it is possible to rescue wing development in apo discs by experimental protocols that provide both Wg and a population of ectopic Vg expressing cells ( Figure 1D–I; Figure 2G , H ) [33] , [34] . Under these conditions , the ectopic Vg expressing cells induce neighboring cells that receive Wg to activate QE-dependent vg expression ( turquoise shading in Figure 1 ) , and these newly recruited vg expressing cells can similarly induce their non-expressing neighbors , the process reiterating to increase the size of the wing primordium [33] , [34] . These results establish that Vg expressing cells send a short-range , inductive signal that is required , together with Wg , to activate QE-dependent vg expression in neighboring cells . We term this Vg-dependent , Vg-inducing signal the FF signal [33] , [34] . In the experiments below , we exploit the same experimental protocols ( Figure 1C–I ) to identify gene functions that are required to send and/or to receive the FF signal . We monitor the results of these manipulations by assaying QE activity as visualized by the expression of 1XQE . lacZ and 5XQE . DsRed reporters , as well as endogenous Vg [33] , [35]; all three responses behave similarly , and we use them interchangeably . During normal development , vg activity drives production of the FF signal , and transduction of the signal occurs at the periphery of the wing primordium , where recruitment occurs . Strikingly , two genes involved in Ft-Ds signaling , four-jointed ( fj ) and ds , itself , are expressed at peak levels in complementary domains that abut at the wing periphery , fj in the vgON domain ( Figure 2A ) and ds in the vgOFF surround ( Figure 2C ) . fj encodes a Golgi resident ecto-kinase that functions in PCP to potentiate signaling by Ft and inhibit signaling by Ds [20] , [21] , [23] , [44] , [45] , [46] . Hence , vg may generate the FF signal by activating fj transcription and repressing ds transcription to create steep and opposing differentials in Ft and Ds signaling between wing and non-wing cells . One prediction of this hypothesis is that Vg should be both necessary and sufficient to activate fj and repress ds in prospective wing cells . To test this , we used fj-lacZ and ds-lacZ reporters to monitor the consequences of ectopically expressing Vg in apo discs . Mature apo discs lack the wing primordium as well as adjacent portions of the hinge primordium ( Figures 1C , 2B ) ; the remaining cells ( which correspond to the rest of the prospective hinge and body wall ) express high levels of ds-lacZ ( Figure 2D ) but not fj-lacZ ( Figure 2B ) . To determine if Vg is sufficient to activate fj-lacZ and repress ds-lacZ , we generated clones of Tub>vg cells in apo discs that are also vgo ( to eliminate any contribution from endogenous Vg activity ) . Such clones express moderate levels of exogenous Vg , a few fold lower than the peak endogenous level observed in wild type discs , and rescue wing development cell-autonomously [33] . They also express fj-lacZ and repress ds-lacZ ( Figure 2E , 2F ) . Thus , ectopic Vg acts cell-autonomously to up-regulate fj and down-regulate ds in apo vgo discs . A second prediction of the hypothesis that vg generates the FF signal by activating fj and repressing ds is that FF propagation should correlate with the up-regulation of fj transcription at the expense of ds transcription . To test this we analyzed the effects of Tub>vg clones on fj-lacZ and ds-lacZ expression in apo discs supplemented with exogenous Wg , a context in which they induce long-range propagation of QE-dependent vg expression and wing growth ( as in Figure 1G; [33] ) . As previously shown , Tub>vg clones generated in such discs cell-autonomously activate peak levels of QE-dependent vg expression and induce the long-range propagation of QE-dependent vg expression in surrounding tissue ( Figure 2G , 2H; [33] ) . They also induce the long-range propagation of fj-lacZ expression at the expense of ds-lacZ expression ( Figure 2G , 2H ) , establishing a correlation between FF propagation and the control of fj and ds transcription by vg . Two additional properties of Tub>vg clones are important to note . First , Tub>vg clones activate fj-lacZ and repress ds-lacZ only in the prospective wing ( white/turquoise territory depicted in Figure 1A , 1B ) and not in the prospective hinge and body wall ( grey territory in Figure 1A , 1B ) , as is also the case for activation of the QE ( Figure 2E , 2F ) . This is expected , as the FF recruitment process operates only in the prospective wing , where the selector gene teashirt is off , and not in the more proximal domains where it is on [33] , [34] . Second , Tub>vg clones activate QE-dependent vg expression , albeit weakly , in apo discs , even in the absence of exogenous Wg , despite the fact that these discs are devoid of D-V border cells , the normal source of Wg required for QE activity . As previously shown [33] , [34] , this response depends on low levels of cryptic Wg , possibly emanating from the surrounding hinge primordium , which allows the QE to be activated cell-autonomously by the exogenous Vg produced by the Tub>vg transgene . Both the presence of cryptic Wg signal in apo discs as well as the restriction of FF propagation to the prospective wing territory are relevant preconditions for the experiments presented below . Given that fto and dso discs show extra wing growth , we previously speculated that Ft and Ds normally suppress QE activity in non-wing cells and that the FF signal acts as an antagonist to alleviate this suppression , allowing the QE to respond to Wg [33] . Accordingly , the removal of either protein should mimic receipt of the FF signal and alleviate the block to Wg-dependent activation of the QE . We tested this prediction by assaying QE activity in fto apo and dso apo discs , either in the presence or absence of exogenous Wg . As described above , apo discs do not activate QE-dependent vg expression and fail to sustain a wing primordium ( Figures 1C and 2B ) [33] , [34] . In contrast , fto apo discs show at least partial rescue of the wing primordium , and cells within the primordium express both 5XQE . DsRed and Vg , albeit at barely detectable levels ( Figure 3B and unpublished data; the rescue observed is due to this low level Vg activity , as it does not occur in fto apo vgo discs ) . Hence , prospective wing cells in these discs behave as if they have constitutively activated the FF signal transduction pathway but can mount only a weak QE response owing to the low levels of cryptic Wg available [34] . This interpretation is supported by two experiments that show that QE activity in fto apo discs is Wg dependent . First , the QE response is abolished in clones of fzo Dfz2o cells , which are unable to transduce Wg ( Figure 3D ) [47] . Second , clones of cells that express a membrane tethered form of Wg ( Nrt-Wg; [4] , [5] ) under Gal4/UAS control ( henceforth , UAS . Nrt-wg clones ) drive peak levels of Vg and 5XQE . DsRed expression in fto apo discs , both within the clones and in abutting cells ( Figure 3E; unpublished data ) . By contrast , Nrt-Wg fails to rescue Vg expression or wing development in apo discs that are wild type for ft ( Figure 1F ) [33] , confirming that it is the absence of Ft activity in fto apo discs that allows them to activate the QE in response to Wg . dso apo discs behave similarly to fto apo discs , except that they express even lower levels of 5XQE . DsRed and Vg , and the rescued wing primordium is smaller ( Figure 3A; unpublished data ) . Nevertheless , as in fto apo discs , both responses are activated to peak levels by UAS . Nrt-wg clones ( Figure S1 ) . The effect of removing ds appears to be additive to that of removing ft: the rescued wing primordium in triply mutant , dso fto apo discs tend to be larger , on average , than those in fto apo discs ( Figure 3B , 3C ) . The distinct and additive effects of removing Ft and Ds suggest that neither condition corresponds to normal , peak activation of the FF transduction pathway . Instead , as we describe below , each appears to lock the FF transduction pathway into a state of weak , constitutive activity , rendering the level of QE activity refractory to the presence or absence of incoming FF signal . We conclude that Ft and Ds are normally required in non-wing cells to block QE activity and that receipt of the FF signal alleviates this suppression , allowing the QE to be activated by Wg . Below , we present evidence that Ft , itself , corresponds to the FF signal sent by wing cells and that Ft and Ds function in non-wing cells to receive and transduce this signal . If , as we posit above , vg generates the FF signal by up-regulating Ft signaling at the expense of Ds signaling , wing cells should require ft , but not ds , to induce QE-dependent vg expression in neighboring non-wing cells . To test this , we generated dso and fto clones in apo discs . Given that the loss of either Ds or Ft mimics reception of the FF signal , such clones should cell-autonomously activate QE-dependent vg expression and survive as wing tissue in apo discs . Accordingly , they should serve as ectopic sources of FF signal , allowing us to determine if their capacity to send FF signal depends on either Ds or Ft activity . As expected from the behavior of entirely mutant dso apo and fto apo discs ( Figure 3A , 3B ) , both dso and fto clones survive and develop as wing tissue in apo discs ( Figure 4A , 4B ) . However , they express only cryptic , low levels of 5XQE . DsRed and Vg ( Figure 4B; unpublished data; see also Figure 4D , 4E ) , like cells within the wing primordia of dso apo and fto apo mutant discs ( Figure 3A , 3B ) . Strikingly , dso clones also act non-autonomously to induce higher levels of QE activity in neighboring cells ( Figure 4A ) . In contrast , fto clones do not ( Figure 4B ) . Thus , it appears that Ft , but not Ds , is required to send the FF signal . To determine if the non-autonomous induction of QE activity by dso clones is due specifically to Ft activity in the mutant cells , we generated dso fto clones . Such clones behave like fto clones in showing strictly cell-autonomous QE activity ( Figure 4C ) . Hence , dso cells require Ft to generate ectopic FF signal . Assaying FF signaling is limited in apo discs by the dependence of QE activity on cryptic Wg input ( Figure 3D , 3E; [34] ) . We therefore repeated the dso and fto clone experiments , this time supplementing this cryptic Wg signal with uniformly expressed Nrt-Wg ( as in Figure 1G ) . In the presence of Nrt-Wg , dso clones expressed peak levels of Vg and 5XQE . DsRed cell-autonomously and induced the long-range propagation of both responses in surrounding cells ( Figure 4D; unpublished data ) . Similar results were obtained when we supplied exogenous Wg by generating dso clones that express a UAS . wg transgene ( using the MARCM technique [48]; unpublished data ) and by generating UAS . Nrt-wg expressing clones next to dso clones in the same disc ( Figure 4F ) . In the latter case , the dso clones behave indistinguishably from Tub>vg clones in the original experimental paradigm used to define the FF signal ( Figure 1I; [33] ) : they induce the long-range propagation of peak levels of Vg and 5XQE . DsRed expression in abutting UAS . Nrt-wg clones ( an effect that can extend to the immediate , wild type neighbors of the UAS . Nrt-wg clone ) . These results confirm that dso clones serve as ectopic sources of FF signal , capable of inducing QE-dependent vg expression in neighboring cells , provided that the responding cells also receive Wg . In contrast , and with only limited exceptions ( Figure S2 ) , fto clones elicited a strictly cell autonomous response , both in Nrt-Wg expressing apo discs ( Figure 4E ) and when exogenous Wg was supplied using the MARCM technique ( unpublished data ) . Such fto clones form ectopic wing primordia composed solely of mutant cells , excluding even cells of their wild type sibling clones from contributing to the rescued wing tissue ( Figure 4E; the sibling clone is marked by elevated GFP staining; compare with the inclusion of the corresponding sibling cells in the case of dso clones , Figure 4D ) . The cell autonomous response of these fto clones is especially significant because all cells within such clones express peak levels of Vg and fj-lacZ ( unpublished data ) and hence should be potent sources of FF signal; nevertheless they behave as if devoid of the capacity to signal . Note that this failure cannot be attributed to a generic inability of fto cells to send intercellular signals . First , fto clones repolarize their neighbors , whereas dso fto clones do not , indicating that they have the capacity to send the Ds PCP signal [21] , [23] , [30] , [44] . Second , we have verified by experiment that fto clones in the wing primordium can also send DSL-Notch , Wg , and Dpp signals ( Figure S3 ) . Thus , we conclude that Ft is normally required in vg expressing cells to send the FF signal . Ft and Ds have a complex ligand-receptor relationship in PCP: both proteins have intrinsic signaling activity , and both are required , together , to receive and transduce each of the signals [23] . Hence , as in PCP , Ft may be required both to generate the FF signal in wing cells and , together with Ds , to receive the FF signal in non-wing cells . To test this , we generated abutting , sibling clones ( “twin spots” ) in which one clone is UAS . ft and the other is either dso or fto and assayed for the capacity of the UAS . ft clones to induce QE activity in neighboring wild type , dso , or fto cells ( Figure 5A , 5B ) . UAS . ft clones express levels of Ft that are several fold higher than endogenous Ft ( unpublished data ) and generate ectopic FF signal in apo discs , as monitored by the induction of 5XQE . DsRed expression in adjacent wild type cells ( Figure 5A , 5B; unpublished data ) . However , adjacent clones of fto cells appear unresponsive to this FF signal , even when they abut the UAS . ft clones over an interface of many cell diameters ( Figure 5B ) . Instead , they express 5XQE . DsRed uniformly and at cryptic , low levels ( as in Figure 3B ) , indicating that the FF transduction pathway is only weakly , albeit constitutively , active in fto cells . Similarly , although clones of dso cells can induce 5XQE . DsRed expression in abutting wild type cells ( as in Figure 4A ) , they too appear to be incapable of responding to adjacent UAS . ft clones ( Figure 5A ) . Thus , clonal over-expression of Ft is sufficient to generate an ectopic FF signal , but abutting dso and fto cells are refractory to this signal . Notably , we detect either no , or very little , expression of Vg or the 5XQE . DsRed reporter in the Ft over-expressing cells , themselves . Hence , it appears that Ft itself , and not some other molecule under the control of Vg , is responsible for the FF signal sent by these cells . Taken together with our preceding results , these findings indicate ( i ) that wing cells require Ft to generate FF signal and ( ii ) that non-wing cells require both Ft and Ds to receive the signal . Although wing cells require Ft , but not Ds , to send the FF signal , cells undergoing recruitment are also in position to receive an opposing Ds signal coming from non-wing cells on the other side , raising the possibility that this Ds input may also contribute to activating the QE and recruiting cells into the wing primordium . To assess this , we generated Ds over-expressing clones in apo discs and asked if the resulting disparity in Ds signaling across the clone border is sufficient to induce the QE response in surrounding cells . Clones of UAS . ds cells in apo discs generate levels of Ds that are several fold higher than endogenous Ds ( which is expressed at peak levels in these discs , owing to the absence of vg activity ) . In the absence of exogenous Wg , such UAS . ds clones had little effect on surrounding cells , only occasionally inducing 5XQE . DsRed expression just outside the clone ( unpublished data ) . However , when supplemented with exogenous Wg ( using co-expression of a UAS . wg transgene ) , most UAS . ds clones induced 5XQE . DsRed expression both within the clone and in surrounding cells ( Figure 5D ) , as is also the case for UAS . ft UAS . wg clones ( Figure 5C ) . Thus , Ds over-expressing clones , like Ft over-expressing clones , can induce neighboring cells to activate QE-dependent vg expression in apo discs , consistent with the possibility that recruitment of cells into the wing primordium normally depends on opposing Ft and Ds signals ( Ft presented by wing cells and Ds presented by non-wing cells; see Discussion ) . The Wts-Hpo pathway is known to function downstream of Ft and Ds , as well as the atypical myosin D , in the generic control of growth by the transcriptional co-activator Yki [11] , [15] , [16] , [17] , [18] , [19] . Hence , it may similarly link reception of the FF signal by Ft and Ds to the induction of QE-dependent vg expression . D activity normally promotes Yki activity by inhibiting the Wts kinase ( which would otherwise phosphorylate Yki and prevent it from gaining access to the nucleus ) . Hence , if the FF signal is transduced by the Wts-Hpo pathway , manipulations that promote Yki action ( e . g . , removal of Ex or Wts , or over-expression of D or Yki [9] , [11] ) should activate QE-dependent Vg expression cell-autonomously , subject to Wg input . Moreover , such QE-Vg expressing cells should , themselves , act as sources of ectopic FF signal and induce surrounding cells to activate the QE . We tested these predictions by manipulating D , Ex , Wts , and Yki function in apo discs , either with or without exogenous Wg . apo discs that uniformly over-express Yki , or which contain large clones of wtso cells , appear similar to fto apo discs ( Figure 3B ) , forming wing primordia that express 5XQE . DsRed and Vg , albeit at barely detectable levels ( Figure S1B , S1C; unpublished data ) . However , as in the case of fto apo and dso apo discs ( Figure 3E; Figure S1A ) , clones of UAS . Nrt-wg cells in these apo wtso and apo UAS . yki discs induce peak levels of both Vg and 5XQE . DsRed expression within the clone and in adjacent cells ( Figure S1B , S1C ) , indicating that both the removal of Wts as well as the over-expression of Yki constitutively activate the FF signal transduction pathway . Corroborating these results , clones of UAS . d and UAS . yki cells that co-express UAS . wg in apo discs activate peak levels of 5XQE . DsRed expression , cell-autonomously , and can also induce 5XQE . DsRed expression in surrounding cells ( Figure 6A , 6B ) . Likewise , clones of exo or wtso cells generated in UAS . Nrt-wg apo discs express peak levels of Vg and 5XQE . DsRed cell-autonomously and can induce both responses in the surround ( Figure 6C , 6D ) . These results link reception of the FF signal by Ft and Ds , via D , the Wts-Hpo pathway , and Yki , to activation of the QE . Of the various cytosolic components that function downstream of Ft and Ds , D is distinct in that it functions to promote , rather than to prevent , nuclear action of Yki and that it acts by repressing , rather than facilitating , Wts kinase activity [18] , [19] , [24] , [49] . Hence , in the absence of D , Wts is constitutively active and Yki is excluded from the nucleus , irrespective of Ft-Ds signaling . Accordingly , removal of D should block transduction of the FF signal , preventing the recruitment of non-wing cells into the wing primordium . To test this , we performed the following four experiments . First , we examined the consequences of generating dso apo , fto apo , and dso fto apo discs that are also null for d . Discs of all three genotypes appear indistinguishable from apo discs ( unpublished data ) , as expected if D is not available to block Wts activity in the absence of Ds and/or Ft . Second , we generated twin spots of sibling dso and do clones in UAS . wg apo discs . Under these conditions , the dso clones both expressed Vg and induced Vg expression in neighboring wild type cells but failed to induce detectable expression in abutting cells belonging to the do clone , resulting in their exclusion from the rescued wing pouch ( Figure 7A ) . Third , we generated clones of Tub>vg cells in both apo and do apo discs supplemented with uniform Nrt-Wg ( as in Figure 1G ) . Such clones express peak levels of Vg and induce a long-range propagation of Vg and 5XQE . DsRed expression in apo discs ( Figure 2G; [33] ) but only a poorly penetrant and local induction of 5XQE . DsRed expression in abutting cells in do apo discs ( Figure 7B ) . Finally , we tested if the requirement for D in activating the QE is specific to transduction of the FF signal in “receiving” cells as opposed to production of the FF signal in “sending” cells by generating clones of dso do double mutant clones that co-express UAS . wg in apo discs . Such clones behave like corresponding clones of dso single mutant cells ( Figure 4D ) in that they induce 5XQE . DsRed expression in surrounding cells ( Figure 7C ) . However , cells within the clone show either no or only low levels of 5XQE . DsRed expression . We conclude that the loss of D activity severely and selectively compromises the capacity of non-wing cells to transduce the FF signal , blocking activation of the QE and recruitment into the wing primordium .
To date , Ft-Ds signaling has been studied in two contexts: the control of Yki target genes in tissue growth and the orientation of cell structures in PCP . Most work on tissue growth has focused on Yki target genes that control basic cell parameters , such as survival , mass increase , and proliferation ( e . g . , diap , bantam , and cyclinE ) . In this context , Ds and Ft are thought to function as a ligand-receptor pair , with tissue-wide gradients of Ds signal serving to activate Ft to appropriate levels within each cell [11] , [18] , [19] , [24] , [25] . In contrast , Ft and Ds behave as dual ligands and receptors in PCP , each protein having intrinsic and opposite signaling activity and both proteins being required to receive and orient cells in response to each signal [23] , [32] . Here , we have analyzed a different , Yki-dependent aspect of growth , namely the control of organ size by the regulation of a selector gene , vg . In this case , Ft appears to correspond to a ligand , the FF signal , and Ds to a receptor required to receive the ligand—the opposite of the Ds-Ft ligand-receptor relationship inferred to regulate other Yki target genes . Moreover , as in PCP , we also find evidence that Ft and Ds operate as bidirectional ligands and receptors: like Ds , Ft is also required for receipt of the FF signal , possibly in response to an opposing signal conferred by Ds ( Figure 8 ) . Studies of Ft-Ds interactions , both in vivo and in cell culture , have established that Ft and Ds interact in trans to form hetero-dimeric bridges between neighboring cells , the ratio of Ft to Ds presented on the surface of any given cell influencing the engagement of Ds and Ft on the abutting surfaces of its neighbors [28] , [30] , [44] , [58] . These interactions are thought , in turn , to polarize the sub-cellular accumulation and activity of D [19] , [24] . Accordingly , we posit that vg activity generates the FF signal by driving steep and opposing differentials of Ft and Ds signaling activity between wing ( vgON ) and non-wing ( vgOFF ) cells . Further , we posit that these differentials are transduced in cells undergoing recruitment ( yellow cells in Figure 8 ) by the resulting polarization of D activity , acting through the Wts-Hpo pathway and Yki to activate vg . Thus , we propose that FF propagation and PCP depend on a common mechanism in which opposing Ft and Ds signals polarize D activity , both proteins acting as dual ligands and receptors for each other . However , the two processes differ in the downstream consequences of D polarization . For FF propagation , the degree of polarization governs a transcriptional response , via regulation of the Wts-Hpo pathway and Yki . For PCP , the direction of polarization controls an asymmetry in cell behavior , through a presently unknown molecular pathway . FF propagation and PCP may also differ in their threshold responses to D polarization . We note that Figure 8 portrays vg expression and Ft-Ds signaling in an overly simplified form , in which the landscape is flat within frank wing and non-wing territories and steeply graded at the wing periphery , where recruitment occurs . In reality , vg expression is also graded , albeit weakly , within the wing primordium , due to the response of the QE to graded Wg and Dpp inputs [4] , [50] . Hence , a shallow differential of Ft-Ds signaling reflecting that of Vg may be sufficient to orient cells in most of the prospective wing territories , but only cells in the vicinity of the recruitment interface may experience a steep enough differential to induce Yki to enter the nucleus and activate vg . Finally , FF propagation and PCP differ in at least one other respect , namely , that they exhibit different dependent relationships between Ft and Ds signaling . In PCP , clonal removal of either Ft or Ds generates ectopic polarizing activity , apparently by creating an abrupt disparity in the balance of Ft-to-Ds signaling activity presented by mutant cells relative to that of their wild type neighbors [23] . By contrast , in FF propagation , only the removal of Ds , and not that of Ft , generates ectopic FF signal ( Figure 4A–D ) . We attribute this difference to the underlying dependence of Ft and Ds signaling activity on vg . In dso cells , Ft signaling activity is promoted both by the absence of Ds and by the Vg-dependent up-regulation of fj . However , in fto cells , Ft is absent and Vg down-regulates ds , rendering the cells equivalent to dso fto cells ( which are devoid of signaling activity in PCP [23] ) . Thus , for FF propagation , the underlying circuitry creates a context in which only the loss of Ds , but not that of Ft , generates a strong , ectopic signal . For PCP , no such circuit bias applies . Morphogens organize gene expression and cell pattern by dictating distinct transcriptional responses at different threshold concentrations , a process that is understood conceptually , if not in molecular detail . At the same time , they also govern the rate at which developing tissues gain mass and proliferate , a process that continues to defy explanation . One long-standing proposal , the “steepness hypothesis , ” is that the slope of a morphogen gradient can be perceived locally as a difference in morphogen concentration across the diameter of each cell , providing a scalar value that dictates the rate of growth [26] , [59] , [60] . Indeed , in the context of the Drosophila wing , it has been proposed that the Dpp gradient directs opposing , tissue-wide gradients of fj and ds transcription , with the local differential of Ft-Ds signaling across every cell acting via D , the Wts-Hpo pathway , and Yki to control the rate of cell growth and proliferation [24] , [25] , [26] . The steepness hypothesis has been challenged , however , by experiments in which uniform distributions of morphogen , or uniform activation of their receptor systems , appear to cause extra , rather than reduced , organ growth [61] , [62] . Our results provide an alternative interpretation . As discussed above and illustrated in Figure 8 , we posit that “steepness , ” as conferred by the local differential of Ft-Ds signaling across each cell , is not a direct reflection of morphogen slope but rather an indirect response governed by vg activity . Moreover , we propose that it promotes wing growth not by functioning as a relatively constant parameter to set a given level of Wts-Hpo pathway activity in all cells but rather by acting as a local , inductive cue to suppress Wts-Hpo pathway activity and recruit non-wing cells into the wing primordium . How important is such local Ft-Ds signaling and FF propagation to the control of wing growth by morphogen ? In the absence of D , cells are severely compromised for the capacity to transduce the FF signal ( Figure 7 ) , and the wing primordium gives rise to an adult appendage that is around a third the normal size , albeit normally patterned and proportioned [19] . A similar reduction in size is also observed when QE-dependent vg expression is obviated by other means [34] . Both findings indicate that FF signaling makes a significant contribution to the expansion of the wing primordium driven by Wg and Dpp . Nevertheless , wings formed in the absence of D are still larger than wings formed when either Wg or Dpp signaling is compromised [4] , [5] , [6] , [7] . Hence , both morphogens must operate through additional mechanisms to promote wing growth . Previously , we identified at least three other outputs of signaling by Wg ( and likely Dpp ) that work in conjunction with FF propagation [33] , [34] . First , as discussed above , Wg is required to maintain vg expression in wing cells once they are recruited by FF signaling , and hence to retain them within the wing primordium . Second , it functions to provide a tonic signal necessary for wing cells to survive , gain mass , and proliferate at a characteristic rate ( see also [62] ) . And third , it acts indirectly , via the capacity of wing cells , to stimulate the growth and proliferation of neighboring non-wing cells , the source population from which new wing cells will be recruited . All of these outputs , as well as FF propagation , depend on , and are fueled by , the outward spread of Wg and Dpp from D-V and A-P border cells . Accordingly , as we argue above , we think that wing growth is governed by the progressive expansion in the range of Wg and Dpp signaling . Our identification of Ft-Ds signaling , the Wts-Hpo pathway , and Yki as key components of the FF recruitment process provides a striking parallel with the recently discovered involvement of the Wts-Hpo pathway and Yki/YAP in regulating primordial cell populations in vertebrates , notably the segregation of trophectoderm and inner cell mass in early mammalian embryos [63] and that of neural and endodermal progenitor cells into spinal cord neurons and gut [57] , [64] . As in the Drosophila wing , Wts-Hpo activity and YAP appear to function in these contexts in a manner that is distinct from their generic roles in the regulation of cell survival , growth , and proliferation , namely as part of an intercellular signaling mechanism that specifies cell type . We suggest that this novel employment of the pathway constitutes a new , and potentially general , mechanism for regulating tissue and organ size .
( i ) Flp/FRT mediated mitotic recombination [65] , [66] , ( ii ) “flp-out cassette” excision [67] , [68] , [69] , and ( iii ) Mosaic analysis with a repressible cell marker ( MARCM [48] ) techniques were used , in conjunction with the Gal4/UAS method [70] , to manipulate gene function in genetically marked clones of cells in developing wing imaginal discs ( e . g . , as in [33] , [34] ) . Animals were cultured at 25°C , and clones were induced during the first larval instar ( 24–48 h after egg laying ) by heat shock induced expression of an Hsp70 . flp transgene ( usually 36°C for 20 min ) . Wing discs from mature third instar larvae were dissected , fixed , and processed for immuno-fluorescence by standard methods , using anti-Vg , anti-Wg , anti-HA , and anti-βGal antisera ( as in Zecca and Struhl , 2007a , b [33] , [34] ) . vg QE activity was monitored by expression of 1XQE . lacZ and 5XQE . DSRed reporter transgenes as well as by the expression of Vg protein in the absence of DSL-Notch signaling [33] , [34] , [35] . In some experiments , expression of the fj-lacZ enhancer trap allele fjP1 [71] , which is strongly up-regulated under Vg control , was also used in the absence of DSL-Notch input as a proxy for QE-dependent vg expression . All four assays gave similar results , with the 5XQE . DSRed and fj-lacZ reporters showing the greatest sensitivity . The following amorphic mutant alleles and transgenes were employed ( http://flybase . bio . indiana . edu/ ) [9] , [19] , [22] , [24] , [28] , [33] , [34]: Mutant alleles: ap56f , dGC13 , Df ( 2L ) Exel6006 , dsUA071 , ds2D60b , exE1 , fjP1 , ft15 , fzP21 , Dfz2 C1 , vg83b27R , and wtsX1 . Transgenes: UAS . Nintra , UAS . Nrt-wg , UAS . wg , Tubα1>GFP , y+>vg , C765 . Gal4 , nub . Gal4 , Tubα1>Gal80>Gal4 , UAS . dsGS , UAS . ft , UAS . d , UAS . yki , Hsp70 . GFP . Exact genotypes , by Figure panel: ( 2A ) y w 5XQE . DsRed/y w Hsp70 . flp; FRT39 ap56f fjP1/+ . ( 2B ) y w 5XQE . DsRed/y w Hsp70 . flp; FRT39 ap56f fjP1/FRT39 ap56f . ( 2C ) y w 5XQE . DsRed/y w Hsp70 . flp; ds2D60b FRT39 ap56f vg83b27R/+ . ( 2D ) y w 5XQE . DsRed/y w Hsp70 . flp; ds2D60b FRT39 ap56f vg83b27R/FRT39 ap56f . ( 2E ) y w Hsp70 . flp/y w Hsp70 . flp; ap56f vg83b27R 5XQE . DsRed/FRT39 ap56f vg83b27R fjP1; Tubα1>flu-GFP , y+>vg/+ . ( 2F ) y w Hsp70 . flp/y w Hsp70 . flp; ap56f vg83b27R 5XQE . DsRed/ds2D60b FRT39 ap56f vg83b27R; Tubα1>flu-GFP , y+>vg/+ . ( 2G ) y w 5XQE . DsRed/y w Hsp70 . flp; FRT39 ap56f/Hsp70 . flu-GFP FRT39 ap56f fjP1; Tubα1>flu-GFP , y+>vg UAS . Nrt-flu-wg/C765 . Gal4 . ( 2H ) y w 5XQE . DsRed/y w Hsp70 . flp; FRT39 ap56f/ds2D60b FRT39 ap56f vg83b27R; Tubα1>flu-GFP , y+>vg UAS . Nrt-flu-wg/C765 . Gal4 . ( 3A ) y w 5XQE . DsRed/y w Hsp70 . flp; dsUA071 FRT39 ap56f/dsUA071 FRT39 ap56f; UAS . wg/+ . ( 3B ) y w 5XQE . DsRed/y w 5XQE . DsRed; ft15 FRT39 ap56f/dsUA071 ft15 FRT39 ap56f fjP1 . ( 3C ) y w 5XQE . DsRed/y w 5XQE . DsRed; dsUA071 ft15 FRT39 ap56f/dsUA071 ft15 FRT39 ap56f fjP1; Tubα1>CD2 , y+>Gal4/+ . ( 3D ) y w 5XQE . DsRed/y w Hsp70 . flp; ft15 FRT39 ap56f/ft15 FRT39 ap56f; fzP21 Dfz2C1 FRT2A/Hsp70 . CD2 Hsp70 . flu-GFP FRT2A . ( 3E ) y w 5XQE . DsRed/y w Hsp70 . flp; ft15 FRT39 ap56f/ft15 FRT39 ap56f; UAS>CD2 , y+>Nrt-flu-wg C765 . Gal4/+ . ( 4A ) y w 5XQE . DsRed/y w Hsp70 . flp Tuba1 . Gal4 UAS . GFPnls; dsUA071 FRT39 ap56f/Hsp70 . flu-GFP Tubα1 . Gal80 FRT39 ap56f fjP1 . ( 4B ) y w 5XQE . DsRed/y w Hsp70 . flp; ft15 FRT39 ap56f/Hsp70 . flu-GFP Tubα1 . Gal80 FRT39 ap56f fjP1; UAS . wg/+ . ( 4C ) y w 5XQE . DsRed/y w Hsp70 . flp; dsUA071 ft15 FRT39 ap56f fjP1/Hsp70 . flu-GFP Tubα1 . Gal80 FRT39 ap56f; C765 . Gal4/+ . ( 4D ) y w 5XQE . DsRed/y w Hsp70 . flp; dsUA071 FRT39 ap56f/Hsp70 . flu-GFP FRT39 ap56f; UAS . Nrt-flu-wg/C765 . Gal4 . ( 4E ) y w 5XQE . DsRed/y w Hsp70 . flp; ft15 FRT39 ap56f/Hsp70 . flu-GFP FRT39 ap56f; UAS . Nrt-flu-wg/C765 . Gal4 . ( 4F ) y w Hsp70 . flp/y w Hsp70 . flp; dsUA071 FRT39 ap56f/Hsp70 . flu-GFP FRT39 ap56f; UAS>CD2 , y+>Nrt-flu-wg C765 . Gal4/1XQE . lacZ . ( 5A ) y w 5XQE . DsRed/y w Hsp70 . flp; dsUA071 Tubα1 . Gal80 FRT39 ap56f vg83b27R/Hsp70 . flu-GFP FRT39 ap56f fjP1; UAS . ft/Tuba1 . Gal4 . ( 5B ) y w 5XQE . DsRed/y w Hsp70 . flp; ft15 Tubα1 . Gal80 FRT39 ap56f/Hsp70 . flu-GFP FRT39 ap56f fjP1; UAS . ft/Tubα1 . Gal4 . ( 5C ) y w 5XQE . DsRed/y w Hsp70 . flp UAS . GFPnls; FRT39 ap56f fjP1/FRT39 ap56f UAS . flu-wg; UAS . ft/Tubα1>Gal80 , y+>Gal4 . ( 5D ) y w 5XQE . DsRed/y w Hsp70 . flp UAS . GFPnls; ap56f 1XQE . lacZ/dsUA071 FRT39 ap56f; UAS . ds/Tubα1>Gal80 , y+>Gal4 UAS . wg . ( 6A ) y w 5XQE . DsRed/y w Hsp70 . flp Tuba1 . Gal4 UAS . GFPnls; FRT39 ap56f/Hsp70 . flu-GFP Tubα1 . Gal80 FRT39 ap56f fjP1; UAS . d/UAS . wg . ( 6B ) y w 5XQE . DsRed/y w Hsp70 . flp UAS . GFPnls; FRT39 ap56f UAS . flu-wg/FRT39 ap56f fjP1; Tubα1>Gal80 , y+>Gal4 UAS . yki/+ . ( 6C ) y w Hsp70 . flp/y w Hsp70 . flp; nub-Gal4 FRT39 ap56f/ap56f UAS . flu-Nrt-wg; FRT82 wtsx1/FRT82 Hsp70 . flu-GFP . ( 6D ) y w 5XQE . DsRed/y w Hsp70 . flp; exe1 FRT39 ap56f/Hsp70 . flu-GFP FRT39 ap56f fjP1; UAS . wg/C765 . Gal4 . ( 7A ) y w 5XQE . DsRed/y w Hsp70 . flp; dsUA071 Hsp70 . flu-GFP FRT39 ap56f/dGC13 FRT39 ap56f fjP1; UAS . wg/C765 . Gal4 . ( 7B ) y w 5XQE . DsRed/y w Hsp70 . flp; dGC13 FRT39 ap56f fjP1/dGC13 FRT39 ap56f; Tubα1>flu-GFP , y+>vg UAS . Nrt-flu-wg/C765 . Gal4 . ( 7C ) y w 5XQE . DsRed/y w Hsp70 . flp Tuba1 . Gal4 UAS . GFPnls; dsUA071 dGC13 FRT39 ap56f/Hsp70 . flu-GFP Tuba1 . Gal80 FRT39 ap56f fjP1; UAS . wg/+ . ( S1A ) y w 5XQE-DsRed/y w Hsp70 . flp; dsUA071 FRT39 ap56f/dsUA071 FRT39 ap56f; UAS . Nrt-flu-wg/Tubα1>Gal80 , y+>Gal4 . ( S1B ) y w Hsp70 . flp/y w Hsp70 . flp; ap56f UAS>CD2 , y+>Nrt-flu-wg/nub-Gal4 FRT39 ap56f; FRT82 wtsx1/FRT82 Hsp70 . flu-GFP . ( S1C ) y w Hsp70 . flp/y w Hsp70 . flp; ap56f 1XQE . lacZ/FRT39 ap56f; UAS>CD2 , y+>Nrt-flu-wg C765 . Gal4/UAS . yki . ( S2A ) as ( 4E ) . ( S2B ) y w 5XQE-DsRed/y w Hsp70 . flp; ft15 FRT39 ap56f/Df ( 2L ) Exel6006 Hsp70 . flu-GFP FRT39 ap56f; UAS . Nrt-flu-wg/C765 . Gal4 . ( S2C ) y w Hsp70 . flp/y w Hsp70 . flp; ft15 Tuba1 . Gal80 FRT39 ap56f/Hsp70 . flu-GFP FRT39 ap56f; UAS>CD2 , y+>Nrt-flu-wg C765 . Gal4/1XQE . lacZ . ( S3A ) y w Hsp70 . flp Tubα1 . Gal4 UAS-GFPnls/y w Hsp70 . flp; wgcx4 FRT39 ap56f/Hsp70 . flu-GFP Tubα1 . Gal80 FRT39 ap56f; UAS . Nintra/1XQE . lacZ . ( S3B ) y w 5XQE-DsRed/y w Hsp70 . flp Tubα1 . Gal4 UAS-GFPnls; ft15 wgcx4 FRT39 ap56f/Hsp70 . flu-GFP Tubα1 . Gal80 FRT39 ap56f; lqf1227 Hsp70-CD2 FRT2A UAS . Nintra/+ . ( S3C ) y w Hsp70 . flp Tubα1 . Gal4 UAS-GFPnls/y w Hsp70 . flp; ft15 FRT39 ap56f/Tubα1 . Gal80 FRT39; UAS . wg/+ . ( S3D ) y w omb-lacZ/y w Hsp70 . flp Tubα1 . Gal4 UAS-GFPnls; ft15 FRT39 ap56f/Tubα1 . Gal80 FRT39; UAS . dpp/+ .
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Under normal conditions , animals and their various body parts grow until they achieve a genetically predetermined size and shape—a process governed by secreted organizer proteins called morphogens . How morphogens control growth remains unknown . In Drosophila , wings develop at the larval stage from wing primordia . Recently , we discovered that the morphogen Wingless promotes growth of the Drosophila wing by inducing the recruitment of neighboring cells into the wing primordium . Wing cells are defined by the expression of the “selector” gene vestigial . Recruitment depends on the capacity of wing cells to send a short-range , feed-forward signal that allows Wingless to activate vestigial in adjacent non-wing cells . Here , we identify the molecular components and circuitry of the recruitment process . We define the protocadherins Fat and Dachsous as a bidirectional ligand-receptor system that is controlled by vestigial to generate the feed-forward signal . Further , we show that the signal is transduced by the conserved Warts-Hippo tumor suppressor pathway via activation of its transcriptional effector Yorkie . Finally , we propose that Wingless propels wing growth by fueling a wave front of Fat-Dachsous signaling and Yorkie activity that propagates vestigial expression from one cell to the next .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology"
] |
2010
|
A Feed-Forward Circuit Linking Wingless, Fat-Dachsous Signaling, and the Warts-Hippo Pathway to Drosophila Wing Growth
|
Clearance of anogenital and oropharyngeal HPV infections is attributed primarily to a successful adaptive immune response . To date , little attention has been paid to the potential role of stochastic cell dynamics in the time it takes to clear an HPV infection . In this study , we combine mechanistic mathematical models at the cellular level with epidemiological data at the population level to disentangle the respective roles of immune capacity and cell dynamics in the clearing mechanism . Our results suggest that chance—in form of the stochastic dynamics of basal stem cells—plays a critical role in the elimination of HPV-infected cell clones . In particular , we find that in immunocompetent adolescents with cervical HPV infections , the immune response may contribute less than 20% to virus clearance—the rest is taken care of by the stochastic proliferation dynamics in the basal layer . In HIV-negative individuals , the contribution of the immune response may be negligible .
Infection with the human papillomavirus ( HPV ) is responsible for a large fraction of anogenital and oropharyngeal cancers in both women and men . Over 90% of cervical cancers are caused by HPV infections , and up to 60% of squamous cell carcinomas of the vulva , vagina , anus and penis are associated with high-risk types of HPV [1] . More recently , it has been shown that infection with HPV also plays a critical role in the genesis of certain head and neck cancers , particularly in cancers of oropharynx and base of tongue [2] . The incidence of these cancers in men has been increasing over the past decade , suggesting the emergence of a virus-related cancer epidemic [3] . Even though the lifetime risk of HPV infections is as high as 80% [4] , most individuals clear the virus within 1–2 years [5] . However , if infection with a high-risk type of HPV persists , the viral genes can interfere with the cellular control mechanisms and trigger neoplastic changes , which can eventually develop into an invasive carcinoma [6] . To date , several aspects of the HPV infection dynamics remain poorly understood [7 , 8] . In particular , the mechanisms of virus clearance are controversial [8] . Clearance of HPV infection is usually attributed to an effective immune response , and the observation of longer clearance times in immunocompromised individuals further corroborates this assumption [9] . On the other hand , the fact that development of antibodies preventing future re-infection after clearing of the virus ( known as seroconversion ) occurs only partially [10–14] suggests that mechanisms other than an effective immune response may contribute to viral clearance . One potential contributor in the clearing of HPV that has received little attention is chance itself , or more precisely , the stochasticity of the stem cell dynamics in the infected epithelia . Across different organs ( both anogenital and oropharyngeal ) , oncogenic types of HPV preferentially infect areas of stratified squamous epithelium ( SSE ) , and these SSE are not just a static backdrop to the unfolding infection process [2 , 15] . They have a relatively fast turnover rate and the entire thickness of the epithelium is renewed every few weeks . During the renewal process , stem cell-like progenitor cells ( hereafter denoted as S cells ) in the lowest layer of the tissue ( the basal layer ) produce commited daughter cells ( denoted as D cells ) that differentiate and move upwards into the intermediate and superficial layers , and eventually get sloughed off into the lumen [15] , see Fig . 1 . The critical role of the dynamic differentiation and maturation process in the viral life cycle is well established [16] . However , the hypothesis that stochastic dynamics in the basal layer could contribute significantly to the clearing of new infections has not been addressed elsewhere . Until recently , the driving cellular processes in the basal layer were only poorly understood , but novel lineage tracing techniques have provided valuable insight into the stochastic dynamics of basal cells [17] . Several mouse studies have used fluorescent labeling to observe lineage dynamics over time , and have concluded that while S cell division is prominently asymmetric ( yielding one S and one D cell ) , a small fraction of S cell divisions are symmetric , yielding either two stem cells or two differentiated daughter cells [18 , 19] . Considering that HPV infections start with a small number of infected basal cells in the SSE [16] , it seems plausible that these stochastic division patterns in basal cells may have an impact on the persistence properties of the infection . To investigate the relevance of cellular proliferation patterns and tissue homeostasis on HPV infection dynamics , we develop in this study a stochastic model of HPV infection in the SSE . By explicitly accounting for the stochasticity in stem cell proliferation , as well as cytotoxic T-cell mediated elimination of infected basal cells , we investigate the potential role of chance in the viral clearing process . Combining the model with a longitudinal data set of cervical HPV infections , we provide evidence for the critical role of stochasticity in HPV clearance .
Across affected anogenital and oropharyngeal sites , the dynamics of HPV infections are similar in nature . There is a large overlap among HPV types found in lesions of different sites , and HPV-16 is the most common type found in all HPV-related invasive cancers [20] . In addition , the viral replication strategy is essentially the same across affected sites [21 , 22] . On the other hand , there are some organ-specific differences with respect to the biology of the affected stratified squamous epithelia . In fact , cervical , anal and oropharyngeal infections are usually restricted to a confined metaplastic transformation zone that separates columnar and squamous regions of the epithelium , whereas infections of e . g . the vulva , vagina and penis do not take place in such a transformation zone [23 , 24] . Nevertheless , the bottom-up renewal dynamics ( as explained below ) of the affected epithelia are very similar , and the parametric model developed here can be applied to different tissue types by virtue of adjusting the relevant parameters , such as density of stem cells in the basal layer and regeneration time of the epithelium .
The first objective was to combine the model introduced in Methods with the REACH data set to obtain estimates of the proliferation dynamics , the immune capacity , and the number of initially infected basal cells . For this purpose , we made the assumption of a well-mixed basal layer: upon removal of an infected cell , division of an S cell occurs with probability pS = nS/ ( nS + nS* ) , and division of an S* cell with probability pS* = nS*/ ( nS + nS* ) . In other words , we assumed that the spatial arrangement of cells in the 2D basal layer can be ignored ( the opposite end of the spectrum—a spatially clustered population of infected cells—is discussed below ) . Since the relative size of the infected population compared to the entire basal layer is small throughout the infection , nS ≫ nS* , we can approximate pS ≈ 1 and pS* ≈ 0 . As outlined in section 2 in S1 Text , it follows that the S* cell dynamics reduce to a subcritical branching process , S * → S * + S * at rate λ r , ∅ at rate λ r + μ . ( 5 ) The probability of survival to time t for this process is , according to results in [32] , ℙ n S * ( t ) > 0 = 1 1 + λ r + μ μ e μ t - 1 . ( 6 ) In particular , addition of the immune capacity transforms the ∼ 1/t decay in ( 3 ) into an exponential decay . Next , we used the longitudinal HPV data from the REACH study to infer the model parameters via maximum likelihood estimation ( MLE ) . Thereby , we faced the issue of non-identifiability of the model , a common problem in statistical inference . To understand where these issues arise , we first consider the probability density function f for the persistence time of the infection ( see section 3 in S1 Text for its derivation ) f ( t ) = n 0 ( λ r ) n 0 t n 0 - 1 1 + λ r t n 0 + 1 , μ = 0 , n 0 A n 0 μ e μ t e μ t - 1 n 0 - 1 1 + A e μ t - 1 n 0 + 1 , μ > 0 , ( 7 ) where A ≡ ( λr + μ ) /μ , and n0 is the initial number of infected stem cells . From ( 7 ) we see that the values of λ and r cannot by inferred individually , and the best we can do is infer their product , α ≡ λr . Even though there are no further apparent identifiability issues , we found that for n0 large enough , the density ( 7 ) only depends on the ratio α/n0 ( see section 4 in S1 Text ) . As a consequence , α and n0 cannot be inferred individually , and we perform the inference over μ and n0 for fixed values of α , across a prior range of biologically meaningful values α ∈ [0 . 01 , 0 . 25] d−1 ( see section 5 in S1 Text for a justification of this range ) . In addition to the identifiability issues , the MLE required the derivation of a non-standard likelihood function that takes into account the different combinations of data types: infections were either present at the time of the first visit ( prevalent infections ) , or they were initiated after the first visit ( incident infections ) ; some individuals were lost to follow-up before clearing the virus ( right-censoring ) , and both the time of initiation and the time of clearance were only determined up to the between-visit intervals ( interval-censoring ) . The derivation of the corresponding likelihood function is found in section 3 in S1 Text . A final comment regarding parameter inference concerns the interpretation of negative test results . In fact , it has been shown that longitudinal HPV studies bear a significant amount of misclassifications due to short-term variation [37] , and that apparently cleared infections can reappear after variable amounts of time [38 , 39] . The time before reappearance of seemingly cleared infections could be interpreted as a latency period during which the infection temporarily regresses to subdetection levels . However , molecular evidence for this latency mechanism has so far only been established in animal models [40] . Therefore , we decided to interpret the first of two consecutive negative test results as the time of clearance of the infection . The inference results are summarized in Fig . 3A-B . In what follows , the maximum likelihood estimates are denoted by a hat ( ^ ) on the parameter name , and subscripts ( − ) and ( + ) are used to refer to the HIV-negative and HIV-positive cohorts , respectively . As explained above , the number of initially infected cells n0 is a linear function of α , which varies over the prior range [0 . 01 , 0 . 25] . The inferred ranges for the initial number of infected cells are n̂0 , − ( α ) ∈ [5 , 80] in the HIV-negative cohort , and n̂0 , + ( α ) ∈ [5 , 120] in the HIV-positive cohort , see Fig . 3A . Across the prior range of α , the inferred number of initially infected cells is slightly higher ( but of the same order of magnitude ) in HIV-positive compared to HIV-negative individuals: n̂0 , + ( α ) >n̂0 , − ( α ) , for all α . To our knowledge , there is no experimental data that would allow us to assess the validity of these model predictions . Regarding the immune capacity μ , we find a stark difference between the cohorts: the estimated capacity μ̂− in the HIV-negative cohort ( μ̂−=1 . 4⋅10−3d−1 ) is two orders of magnitude larger than the estimated capacity μ̂+ in the HIV-positive cohort ( μ̂+=3⋅10−3d−1 ) , see Fig . 3B . In particular , the estimates μ̂+ and μ̂− are constant over the prior range of α . Using the inferred parameter values μ̂+ and μ̂− for the immune capacity , and the inferred ranges n̂0 , − ( α ) ∈ and n̂0 , + ( α ) ∈ for the number of initial cells , we then derived the parametric clearance time distributions according to ( 7 ) , see Fig . 3C . Since the clearance time distributions were found to be insensitive to α over the prior range ( see section 6 in Text SI ) , the distribution in Fig . 3C is only shown for an intermediate value of α = 0 . 14 . Due to the reduced immune capacity in the HIV-positive cohort , its median clearance time is considerably larger ( 689 days ) than the median time in the HIV-negative cohort ( 340 days ) . The main goal of this study was to assess the relative roles of stochastic cell dynamics and immune response in the process of HPV clearance . Therefore , we compared the model-based persistence distributions for varying immune capacities μ . As shown in Fig . 4A , the median time to clearance is a decreasing function of μ , and the distributions become more localized with increasing μ . However , comparing the distributions for μ = 0 and μ/μ̂−=1 ( where μ=μ̂− is the estimated immune capacity of HIV-negative individuals ) , the contribution of the immune response appears to be small in comparison to the contribution of the stochastic cell dynamics ( compare the box plots for μ = 0 and μ/μ̂−=1 in Fig . 4A ) . This is particularly clear when plotting the clearance probability as a function of time as shown in Fig . 4B . In particular , comparing the ( μ/μ̂−=0 ) -curve with the ( μ/μ̂−=1 ) -curve after 2 years , the clearance probability without immune response ( 0 . 66 ) is only ∼ 17% smaller than the clearance probability with normal immune capacity ( 0 . 79 ) . In other words , the stochastic dynamics contribute to as much as ∼ 83% of the viral clearing mechanism in healthy individuals , and the contribution from the immune system is comparatively small . The subcritical branching process model above was derived under the assumption of a well-mixed basal layer where infected cells are surrounded primarily by susceptible cells . In this situation , elimination of an infected cell prompts division of an S cell with high probability , justifying the approximation pS = 1 − pS* = 1 . As a consequence , the persistence distribution could be derived analytically ( 6 ) , rendering the model amenable to MLE inference . To assess whether the ensuing results were an artifact of the well-mixing assumption , we developed the following alternative model that takes into account the spatial clustering of infected cells . If we assume that the initial cell population is subject to tight clustering , then radial symmetry implies growth in the form of a radially expanding disk in the basal layer . That is , all the infected cells are inside the disk , whereas the outside is populated only by uninfected cells . Since the number of D* cells is roughly proportional to the number of S* cells ( see section 2 . 2 in Text SI ) , the disk radius is proportional to n S * . Accordingly , whenever an infected cell in the interior of the disk is eliminated by a T-cell , the probability to trigger an S cell division is given by the ratio of disk circumference to disk area: p S = min { 1 / n S * , 1 } and pS* = 1 − pS . Under these assumptions , the S* cell dynamics are now decoupled from the S cell dynamics , but they still depend on the D* cell dynamics , see also section 2 in S1 Text for details . Since closed-form expressions for the clearance time distributions are out of reach for this model , even with the approximation , we resorted to simulations . As in Fig . 4A for the well-mixed model , we investigated the impact of increasing immune capacity μ on the clearance time distribution in Fig . 5A . We make the following observations . First , time to clearance is generally longer in the branching process model: the three dotted horizontal lines correspond to the three quartiles for the ( μ/μ̂−=1 ) -distribution in Fig . 4 . Only for the ( μ/μ̂−=8 ) -distribution , which corresponds to an 8-fold increase in immune capacity , are all three quartiles of the spatial model below the corresponding quartiles of the branching process model . Second , the impact of the immune capacity on the clearance time for the clustered model is even weaker than in the well-mixed model . Whereas the well-mixed model yields a decrease in median time to clearance for increasing μ , small μ values yield a slight increase in median clearance time for the spatial version . This is due to the fact that , in contrast to the branching process model , elimination of an infected cell can trigger division of an S* cell ( with probability pS* > 0 ) , therefore compensating for the loss of the infected cell and delaying clearance . The relative insensitivity of the persistence time distribution to μ is further illustrated in Fig . 5B , where we observe that the clearance probability is only slightly increased for small μ values . Finally , since the prior estimates of several model parameters have a relatively large interval of uncertainty ( see section 5 in S1 Text ) , we performed a combined sensitivity analysis . By means of a Monte-Carlo simulation ( with the parameters r , α , ρ and μ drawn from their prior ranges ) , we computed the corresponding persistence time distribution , and found that it did not substantially differ from the fixed parameter distribution ( see section 7 in S1 Text for details ) .
Clearance of anogenital and oropharyngeal HPV infections has primarily been attributed to a successful adaptive immune response . To date , little attention has been paid to the potential role of homeostatic cell dynamics in clearing HPV infections . In this study , we combined mechanistic mathematical models at the cellular level with epidemiological data at the population level to disentangle the respective roles of immune capacity and cell dynamics in the clearing mechanism . Our results suggest that chance—in form of the stochastic dynamics of basal stem cells—plays a critical role in the elimination of HPV-infected cell clones . In particular , we found that in individuals with normal immune capacity ( HIV-negative cohort ) , the immune response may contribute to less than 20% of the clearing task overall—the rest is taken care of by the random succession of symmetric and asymmetric stem cell divisions . Furthermore , in immunocompromised individuals ( HIV-positive cohort ) the contribution of the immune response is likely to be negligible . Based on our results , we may be able to shed new light onto questions currently debated in the literature . First , in view of the high prevalence of HPV infections and the relatively small risk of persistent infections that eventually lead to malignant disease , the identification of predictive markers for persistence would be valuable [8] . However , if stochasticity does indeed play a key role in viral clearance , and if the major difference between individuals who clear effectively and individuals who develop persistent infections is largely a matter of chance , then there may not be any predictive markers to discover . Hence , we may want to rephrase the question , and ask if there is a way of modulating the cellular dynamics to achieve an increase in the clearance probability . Our results suggests that by increasing either the probability of a symmetric division ( r ) or the proliferation frequency ( λ ) through a locally administered drug , time to clearance and risk of progression could be substantially reduced . Second , the suggested clearing mechanism could provide an alternative explanation for the correlation between long-term use of combined oral contraceptives and increased risk of persistent infections and cervical cancer [41] . Since estrogen stimulates [42] and progesterone inhibits [43] epithelial proliferation , it seems plausible that a decrease in cervical proliferation could be caused directly via increased progesterone levels , and indirectly via loss of the estrogenic mid-cycle peak . The resulting decrease in proliferation ( smaller λ ) would imply an increase in time to clearance and a higher risk of progression to cancer . While the same reasoning would imply an increased risk of cervical cancer in progestin-only users , the effect of progestin-only contraceptives on HPV persistence and cervical cancer development is less consistent in the literature [44 , 45] . This highlights the need for future research into the influence of sex steroids on the natural history of oncogenic HPV infection . Finally , the suggested model of chance-driven clearance is interesting in view of the ongoing debate about viral latency [46–48] . To date , the existence of latent infections has been demonstrated in animal models , and it is assumed to occur in HPV infections as well . The current theory of latency is based on the assumption that the virus stays present inside long-lived basal stem cells [48] . But while the notion of such long-lived , asymmetrically dividing and slow-cycling stem cells is consistent with a theory of epithelial homeostasis developed in the 1970’s [49] , it is not aligned with the new paradigm that is based on fast-cycling stem cells that divide both asymmetrically and symmetrically [18 , 19 , 29] . According to our model , which is based on this more recent theory of homeostasis , viral latency is again a stochastic phenomenon and occurs if the number of infected cells becomes very small ( latent period ) before growing back to a detectable size . A more thorough discussion of the latency issue will be the subject of future work . While population-level models of HPV transmission and progression are commonly used by epidemiologists and health economists , only few groups have developed mathematical models of HPV infection at the tissue level . In two recent studies [50 , 51] , deterministic ( partial ) differential equation models were used to study evolutionary and ecological aspects of HPV infections and competition between coexisting HPV types . To our knowledge , we are the first to develop a stochastic model of HPV infection that couples stem cell dynamics with viral infection and immune response . In addition , the methods introduced here provide a useful tool in the parametric analysis of longitudinal data sets that contain both prevalent ( present at study begin ) and incident ( initiation after study begin ) infections , as well as right-censoring ( study exit before viral clearance ) and interval-censoring ( duration of infection only known up to an interval ) . In fact , 70% of the individuals in the analyzed REACH data set had an unknown time of initiation , rendering conventional nonparametric approaches problematic ( see section 1 in S1 Text for details ) . Thanks to the mechanistic models introduced and analyzed in this study , we were able to account for the unknown time lapse between infection initiation and study entry . Finally , the approach employed in this study may prove useful in other situations . In fact , mathematical models at the tissue-level are often difficult to parametrize because sample sizes in pathology studies are generally small and exhibit large between-patient variation . By combining longitudinal population-level data with cell-level mechanistic models as done in this study , insights can be gained across the scales . Every model comes with its limitations . First , it is known that there can be time-lags between inoculation and productive infection [22] . Since these lag times vary widely among individuals , and since we wanted to avoid adding to the complexity of the model , we set the incubation period to zero . Second , since infected cells acquire a selective growth advantage only at later , symptomatic stages of the infection [31] , we assumed that the presence of viral DNA did not alter the proliferation rates of infected stem cells . In addition , there is , to our knowledge , no experimental evidence regarding HPV-mediated modulation of symmetric and asymmetric division patterns in infected tissues . Third , we assumed that the interactions between virus and immune system are independent of the specific HPV strains , and that there are no synergistic or competitive effects among co-infecting types , see also [51] . Since we believe that adding these more subtle aspects would not change the main conclusion of the importance of stochasticity , we did not incorporate them into the current model . However , we plan to address these issues in future work . Fourth , a more realistic alternative to the clustered model version is provided by explicitly spatial models with lattice-based voter dynamics [52 , 53] . Such a spatial model extension is subject of ongoing work . Fifth , even though the stratified squamous epithelia at different anogenital and oropharyngeal sites affected by HPV are qualitatively similar , we parametrized our model for cervical infections , and our insights regarding the role of stochastic stem cell proliferation in viral clearance may not apply to other organs . Finally , our model predicts extinction of infection with probability 1 due to the subcritical nature of the process . This is not in contradiction with the observation that a small fraction of infections persist and progress . In fact , progression from HPV infection to sustained neoplastic growth is associated with cellular changes triggered by the viral genome . These transformations are themselves stochastic processes , and hence progression only takes place in the small group of individuals where the oncogenic transformation takes place before extinction of the infected population .
|
Worldwide , 5% of all cancers are associated with the sexually transmitted human papillomavirus ( HPV ) . The most common cancer types attributed to HPV are cervical and anal cancers , but HPV-related head and neck cancers are on the rise , too . Even though the lifetime risk of infection with HPV is as high as 80% , most infections clear spontaneously within 1–2 years , and only a small fraction progress to cancer . In order to identify who is at risk for HPV-related cancer , a better understanding of the underlying biology is of great importance . While it is generally accepted that the immune system plays a key role in HPV clearance , we investigate here a mechanism which could be equally important: the stochastic division dynamics of stem cells in the infected tissues . Combining mechanistic mathematical models at the cell-level with population-level data , we disentangle the contributions from immune system and cellular dynamics in the clearance process . We find that cellular stochasticity may play an even more important role than the immune system . Our findings shed new light onto open questions in HPV immunobiology , and may influence the way we vaccinate and screen individuals at risk of HPV-related cancers .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
HPV Clearance and the Neglected Role of Stochasticity
|
The East/Central/South African genotype of Chikungunya virus with the E1-A226V mutation emerged in 2011 in Cambodia and spread in 2012 . An outbreak of 190 cases was documented in Trapeang Roka , a rural village . We surveyed 425 village residents within 3–4 weeks after the outbreak , and determined the sensitivity and specificity of case definitions and factors associated with infection by CHIKV . Self-reported clinical presentation consisted mostly of fever , rash and arthralgia . The presence of all three clinical signs or symptoms was identified as the most sensitive ( 67% ) and specific ( 84% ) self-reported diagnostic clinical indicator compared to biological confirmation by MAC-ELISA or RT-PCR used as a reference . Having an indoor occupation was associated with lower odds of infection compared with people who remained at home ( adjOR 0 . 32 , 95%CI 0 . 12–0 . 82 ) . In contrast with findings from outbreaks in other settings , persons aged above 40 years were less at risk of CHIKV infection , likely reflecting immune protection acquired when Chikungunya circulated in Cambodia before the Khmer Rouge regime in 1975 . In view of the very particular history of Cambodia , our epidemiological data from Trapeang Roka are the first to support the persistence of CHIKV antibodies over a period of 40 years .
Chikugunya is caused by an alphavirus transmitted by the bite of Aedes mosquitoes . In humans , it is mostly a self-limiting illness marked with debilitating joint pains but severe illness occurs in about 1 clinical case in 1000 [1] . Although it may have circulated since the late 1800s [2] , the chikungunya virus ( CHIKV ) was first detected in Africa in 1952 [3] . The Asian strain spread through Asia in the 1960s causing a series of outbreaks throughout the region , including Cambodia . After several decades of absence , CHIKV re-emerged in the early 2000s [3–5] , with large outbreaks of significant public health concern in Asia and Africa . In 2005 , a major epidemic in La Réunion island [6] displayed different epidemiological characteristics than previous outbreaks , with a higher attack rate and causing a number of deaths . Genetic analysis attributed this outbreak to a mutated strain of the East/Central/South African ( ECSA ) strain of CHIKV bearing the E1-A226V and other mutations on the E2 glycoprotein gene [7 , 8] , termed the Indian Ocean Lineage ( IOL ) strain [8] . Subsequently , outbreaks of the IOL strain have been recorded in the Indian Ocean [9–11] , South- [12] , Southeast- [13–17] and East Asia [18] and the Pacific [19] . The first outbreak in a temperate country was recorded in 2007 [20] , and cases have been detected in Arabia [21 , 22] . In 2013 , another CHIKV strain , this time of Asian lineage [23] stormed through the Americas , causing over 1 . 5 million suspected or confirmed cases to date [24–27] . That outbreak is still ongoing . Chikungunya poses a real and imminent threat to all yet unaffected areas where Aedes aegypti or Aedes albopictus are present , including various regions of Europe [28] , the USA [29] , Brazil [30] or Australia [31] . Chikungunya re-emerged in Cambodia in 2011 [16] , when the IOL strain of CHIKV was identified , never previously recorded in Cambodia . In this article , we explore the epidemiological and clinical characteristics of a 2012 outbreak in Trapeang Roka village of Kampong Speu province [17] , Cambodia , including an analysis of the sensitivity and specificity of clinical signs and their combination , as well as the association of various factors with the risk of CHIKV infection .
The method , dates and duration of the outbreak investigation in Cambodia have been detailed elsewhere [17] . Briefly , a one-day outbreak investigation was conducted in 2012 , three to four weeks after the onset of the CHIKV outbreak in Trapeang Roka village caused by an ECSA strain with the E1-A226V mutation , using a standardized , anonymized questionnaire . All village residents were eligible for the investigation; consenting individuals were interviewed regarding socio-demographic characteristics and information on potential risk factors for exposure and were screened for CHIKV . Participants were asked about self-reported clinical features ( fever , arthralgia and skin rash ) using a short questionnaire and the Wong-Baker Pain Rating scale . For children who were too young to answer , parents/guardians were asked to answer for the child . Interviews were conducted by teams from the Epidemiology and Public Health unit of the Institut Pasteur du Cambodge ( IPC ) and other teams . Dried blood spots were obtained from consenting participants to test for CHIKV IgM [32] , as well as recent infection by dengue ( DENV ) and Japanese encephalitis B ( JEV ) viruses using antibody capture enzyme-linked immunosorbent assay ( MAC-ELISA ) [33 , 34] . Participants with ongoing fever were also tested by quantitative real-time reverse transcriptase PCR ( qRT-PCR ) for CHIKV as well as DENV and JEV . Participants ( N = 91 ) with current or very recent signs or symptoms were also screened for malaria by PCR ( all negative ) . The laboratory methods used were detailed in the previous report [11] . The investigation was undertaken as part of an urgent public health investigation of emerging CHIKV in Cambodia , with a National Ethics Committee waiver under the authority of the Ministry of Health . After explaining the investigation in Khmer , participants were asked for written informed consent to undergo an interview and a fingerprick for blood sampling . Participants received advice on how to reduce their risk of CHIKV infection and received their laboratory results at a later visit . All data collected were anonymised , with no personal identifiers .
Findings are presented in Table 1 . The combined signs of fever , arthralgia and skin rash was 67% sensitive as a CHIKV diagnostic tool compared to the reference laboratory diagnostic test . The combination of all three signs or symptoms also identified the highest proportion of laboratory confirmed CHIKV infections during the outbreak ( PPV = 77 . 3% ) , while those who did not experience these combination of signs or symptoms represented 76 . 3% ( NPV ) of the truly uninfected . The specificity of individual sign or symptoms , or combination thereof , was higher than the sensitivity , with between 84 . 4% to 98 . 7% of those without the sign or symptom being correctly identified as CHIKV IgM-negative , depending on which combination of signs or symptoms was considered . Age was strongly associated with laboratory-confirmed CHIKV infection in both the univariate and multivariate models ( p<0 . 001 ) ; the shape of the association is shown in Fig 1 . The predicted risk of CHIKV peaked at 50% among those age 15 to 26 years ( born between 1986 and 1997 ) and then declined abruptly , reaching a low of 0 . 1% by age 87 . After adjusting for gender and occupation , the predicted adjusted risk of CHIKV was highest ( 58% ) among 24–32 year-olds ( born between 1980 and 1988 ) . Table 2 shows the association of selected risk factors with laboratory-confirmed CHIKV infection , none of which showed strong evidence of an association , likely because of the relatively small sample size . There was some evidence that males were more likely to be infected than women ( adjusted ( adj ) OR = 1 . 61; 95%CI 0 . 93–2 . 77; p = 0 . 09 ) . There was also some evidence of an association with occupation , with CHIKV infection being less likely among participants who had an indoor occupation compared with those who stayed at home ( adjOR 0 . 32 , 95%CI 0 . 12–0 . 84 , p = 0 . 07 ) . There was also some evidence that those who had a healthcard–a government-issued certificate to allow the poorest Cambodians access to free healthcare–were at lower risk of infection . There was no evidence of an association of CHIKV infection with level of education .
Studies of emergent pathogens in the laboratory or in the hospital setting are very important to identify risk factors for increased circulation ( such as CHIKV mutations [7 , 8] ) or severe clinical forms [1] of infection . However , the findings that will guide surveillance , risk assessment and public health prevention and response should originate mainly from careful epidemiological documentation in the community of the true health burden of disease , risk factors associated with infection and the performance of clinical case definitions . Our data show that current case definitions are both sensitive and specific enough to guide initial epidemiological assessments but must be complemented by virological tests performed by experienced laboratories . Importantly , these data from Cambodia—with its unique and dramatic history—strongly suggest that immunity against CHIKV may last several decades , an important element for future risk assessment in non-endemic settings and as this virus spreads across the New World and the Pacific . These epidemiological findings will be verified in the laboratory by testing immunity against the CHIKV strain which circulated in the Mekong Region in the 1960s .
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After first being identified in the 1950s and spreading from Africa in the 1960s , a new pandemic strain of Chikungunya virus emerged in East Africa and the Indian Ocean in 2004–2005 , progressing to Asia . Cases have since been described in previously unaffected territories , as well as regions where Chikungunya transmission was never interrupted . Chikungunya circulated in Cambodia in the 1960s and 1970s until the tragic historical events that followed the civil war . After nearly 40 years of absence of the virus , the new pandemic strain was first detected in 2011 . We undertook a field investigation of a Chikungunya outbreak in Cambodia in 2012 . The usefulness of clinical signs for diagnosis of infection is discussed . Unlike studies from other settings , we show that older age was associated with a lower risk of Chikungunya infection , even after behavioural and occupational factors have been taken into account . This is the first evidence suggesting that infection in the 1960s and 1970s likely provided long-lasting cross-protection against this new strain . These findings , which will be further explored in the laboratory , are important to understand immunity against Chikungunya and to predict future epidemics and public health needs .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2016
|
Long-Lasting Immune Protection and Other Epidemiological Findings after Chikungunya Emergence in a Cambodian Rural Community, April 2012
|
Methicillin-resistant Staphylococcus aureus ( MRSA ) is an important cause of morbidity and mortality in both hospitals and the community . Traditionally , MRSA was mainly hospital-associated ( HA-MRSA ) , but in the past decade community-associated strains ( CA-MRSA ) have spread widely . CA-MRSA strains seem to have significantly lower biological costs of resistance , and hence it has been speculated that they may replace HA-MRSA strains in the hospital . Such a replacement could potentially have major consequences for public health , as there are differences in the resistance spectra of the two strains as well as possible differences in their clinical effects . Here we assess the impact of competition between HA- and CA-MRSA using epidemiological models which integrate realistic data on drug-usage frequencies , resistance profiles , contact , and age structures . By explicitly accounting for the differing antibiotic usage frequencies in the hospital and the community , we find that coexistence between the strains is a possible outcome , as selection favors CA-MRSA in the community , because of its lower cost of resistance , while it favors HA-MRSA in the hospital , because of its broader resistance spectrum . Incorporating realistic degrees of age- and treatment-structure into the model significantly increases the parameter ranges over which coexistence is possible . Thus , our results indicate that the large heterogeneities existing in human populations make coexistence between hospital- and community-associated strains of MRSA a likely outcome .
Over the past ten years community-associated strains of methicillin-resistant Staphylococcus aureus ( CA-MRSA ) have emerged and spread rapidly , accounting for large increases in disease both in the community and in the hospital [1] , [2] . While originally thought to be primarily a hospital-associated pathogen ( HA-MRSA ) , the emergence of a community-associated strain , which has a different genetic background [2] and drug susceptibility profile [3] , [4] , has raised questions about how the epidemiology and the ecology of the disease will evolve , particularly with respect to which strain will predominate . MRSA resistance is mediated by the integration of a staphylococcal cassette chromosome mec ( SCCmec ) in a site-specific manner into the staphylococcal genome [5] . Eight different SCCmec allotypes , as well as numerous subtypes , which encode varying levels of resistance to multiple antibiotics , have been described to date [2] . In vitro growth assays have demonstrated an inverse correlation between resistance level and growth rate [6] , [7] , which presumably limits the spread of HA-MRSA strains – characterized by high levels of resistance to multiple antibiotics –beyond hospitals [8] , [9] . On the other hand , the maintenance of resistance in the most common community-associated strains , which are characterized by resistance to only a limited set of antibiotics , seems to cause only a negligible reduction in the growth rate relative to non-resistant strains [10] , [11] . This in turn accounts for its wide dissemination in the community and the assumption that it is more easily transmitted than HA-MRSA strains [2] . Given the presumed relatively lower cost of resistance in CA-MRSA , it has been speculated that CA-MRSA strains may eventually replace HA-MRSA strains in the hospital [12] , [13] . However , the high costs of resistance for HA-MRSA strains might be offset by the fact that they are resistant to a much broader range of antibiotics than CA-MRSA strains [3] , [4] . If this were the case , coexistence between the two strains might be a plausible long-term scenario . In fact , a recent empirical study [14] indicates that despite a substantial increase in patients infected with CA-MRSA strains , the frequency of HA-MRSA strains in the hospital has remained remarkably stable . Intuitively , both outcomes , coexistence and replacement , are possible . On the one hand , replacement , or competitive exclusion , is the standard outcome expected by ecological theory for two strains occupying the same ecological niche . Accordingly , explaining observed coexistence in other bacterial pathogens has proven challenging [15] , [16] . On the other hand , structural differences in hospital and community populations may impose sufficiently different selective advantages to allow coexistence . Thus , HA-MRSA with its broad resistance spectrum may be better adapted to the hospital environment where antibiotic use is common , whereas CA-MRSA may be better adapted to the community , where antibiotic use is less frequent and hence a broad resistance spectrum cannot compensate for the reduced transmissibility of HA-MRSA . One factor , which may counteract this mechanism , is that the average length of stay of a patient in the hospital ( 4–5 days ) is much shorter than the time until a patient colonized with MRSA clears the bacteria ( several 100 days [17] ) . Accordingly , a given colonization ( bacterial population within a host ) almost never experiences only the hospital environment , hence making local adaptation difficult . It follows from the above reasoning that addressing the question of coexistence is not possible from the hospital perspective alone , but instead it is necessary to take both hospital and community populations ( and their frequent exchange ) into account . While this question of coexistence is an interesting ecological problem , it is also an important question for public health as the outcome of the interaction between CA-MRSA and HA-MRSA may have epidemiological and clinical consequences: HA-MRSA has a much broader resistance spectrum than CA-MRSA [18] and may therefore be more difficult to treat . Moreover , the two strains also differ with respect to their pathogenicity . While CA-MRSA has primarily been associated with skin- and soft-tissue infections , there have also been suggestions that it may be more invasive and virulent than HA-MRSA [2] . If CA-MRSA completely replaces HA-MRSA , hospitals might be confronted with a more virulent but also more treatable pathogen . Moreover , their ability to replicate and transmit in the community may mean significantly more infections as well . In this analysis , we use epidemiological models which integrate realistic data on drug-usage frequencies , resistance profiles , contact , and age structures to assess the impact of competition between HA- and CA-MRSA strains . In particular , we examine the likelihood of coexistence as an outcome .
We considered three epidemiological models of increasing complexity and assessed how the interaction between hospital and community populations could lead to stable coexistence between HA- and CA-MRSA . The basic model assumes that all individuals , regardless of age , have similar hospital admission and discharge rates as well as antibiotic usage rates . In this case the only difference between the hospital and the community is the usage frequency of antibiotics , which may lead to selection favoring one strain in the community and the other in the hospital . Next we considered two extensions of this model . First we examined how heterogeneity between age-classes with respect to hospitalization rates and antibiotic usage impacted coexistence between strains in each setting . Second , we explicitly distinguished between treated and untreated patients , thereby capturing the prophylactic effect of treatment , which is likely to be much stronger in the hospital than in the community . The epidemiological dynamics of CA- and HA-MRSA were described by set of ordinary differential equations . Based on estimates from the literature and an analysis of public-use data in the United States , we assume differing dynamics of colonization , infection , and antibiotic use between the hospital and the community and consider how differing implementations of the host population structure impacts the dynamics of each strain and examine the parameter ranges over which coexistence occurs . In each of these models , the possibility of coexistence between HA- and CA-MRSA for a given parameter-combination was determined by an invasibility analysis: First , the system is allowed to reach the equilibrium with one strain only ( burn-in time: 5×104 days ) ; then the other strain is introduced at low abundance; if the introduced strain increases in frequency after the introduction , we say that it can invade the equilibrium determined by the resident strain . If both strains ( HA-MRSA and CA-MRSA ) can invade the equilibrium of the other strain , this indicates coexistence . In the basic model we assume that populations in the hospital and community are homogenous . The two populations are connected through admission into the hospital population ( with rate a ) and discharge into the community with rate ( d ) and are each subdivided into individuals that are uncolonized ( SC and SH ) , colonized with CA-MRSA ( CC , CA and CH , CA ) , and colonized with HA-MRSA ( CC , CA and CH , CA ) . In the community , colonized individuals infect uncolonized individuals with a transmission rate βC , CA for CA-MRSA and βC , HA for HA-MRSA . In the hospital the corresponding rates are βH , CA and βH , HA . We assume that regardless of location , in the absence of treatment HA-MRSA suffers a fitness cost ( s ) against CA-MRSA , which is assumed to be due to a reduced transmission rate; i . e . βX , HA = βX , CA ( 1-s ) . Colonization can be cleared either spontaneously , with rate cBL , or through treatment . Since colonization is significantly more common than infection , we assume that antibiotic use is independent of the colonization status of the patient . Antibiotic use occurs at rate τC and τH in the hospital and community , respectively . As treatment is in most cases not specific for S . aureus , we assume that the probability ( fC , X and fH , X ) that a given course of treatment is effective against either strain corresponds to the proportion of drugs to which each is susceptible among all prescribed drugs ( see parameters section ) . We further assume that even if the drug consumed is effective , there are reasons other than antibiotic resistance that a bacterial colonization may not be cleared , i . e . effectively treated patients clear the bacterial population only with a probability cT<1 . The basic model is described by the following set of ordinary differential equations: The age-structured model is derived from the basic model by sub-dividing each compartment into 18 different age classes ( five-year bins for the ages from 0 to 85 and one bin for 85+ ) . For instance , the compartment SC ( uninfected individuals in the community ) is subdivided into the compartments SC1 , SC2… SC18 , where SC1 covers susceptible individuals of age 0–5 , SC2 of 5–10 , etc . Admission rates , aj , and discharge , dj , rates are assumed to depend on the age class j ( see parameters section ) . The impact of age structure on contact rates is captured by assuming that the transmission rates in the community , βC , Xj , k , are proportional to the frequency of physical contacts ( divided by the number of people in that age class ) . Because detailed contact data from the US were not available , we used data on contact rates measured in the UK [19] . Finally , the treatment rate τCj in the community also varies with age class j . Similar data on the age-dependency of contact rates and treatment rates in the hospital were not available to our knowledge . Because contact rates are likely to be more uniform in the hospital , since most of transmission is indirect , we made the conservative assumption that contact and treatment rates in the hospital are uniform regardless of age . The age-structured model is described by the following set of ordinary differential equations:A diagram of the age-structured model is found in Figure 1 . The treatment-structured model ( Equation S1 in the online supplementary material ) is derived from the basic model by subdividing each compartment according to treatment status . Specifically , we distinguish between four treatment classes: 1 ) Untreated ( U ) ; 2 ) treated with a drug that is effective against neither CA-MRSA nor HA-MRSA ( treatment T ( 1 ) ) ; 3 ) treated with a drug that is effective against CA-MRSA but not HA-MRSA ( treatment T ( 2 ) ) ; and 4 ) treated with a drug that is effective against both CA-MRSA and HA-MRSA ( treatment T ( 3 ) ) . Treatment with a drug from class j is initiated at rate τCj and τHj . Upon treatment initiation with an effective drug , the infection is either cleared immediately with a probability cT or alternatively remains colonized ( this is an approximation to the real dynamics in which the patient would clear after a given amount of time ) . Finally , treated individuals stop treatment at a rate ρ ( i . e . the inverse duration of antibiotic use ) . A diagram of the model is found in Figure S1 . The treatment-and-age-structured model is derived from the treatment-structured model in the same way the age-structured model is derived from the basic model . Our models integrate realistic values for drug-usage frequencies , resistance profiles , age structure , age-dependent contact patterns , and hospitalization rates . Usage frequencies , age distribution , hospitalization rates , and the mean length of stay in the hospital were estimated from publicly available data by five-year age groups . Figure 2 summarizes the age-dependency of population size , hospitalization rates , length of stay in the hospital , and antibiotic usage rates in the community . As data on the age-dependency of treatment and contact rates are available for the community only , we make the conservative assumption that these rates are homogenous in the hospital ( see discussion ) . In contrast to these parameters there is large uncertainty concerning the magnitude of transmission rates ( particularly in the hospital ) and especially concerning the degree to which the transmission rate of HA-MRSA is reduced compared to that of CA-MRSA ( i . e . the selective cost of HA-MRSA ) . Therefore we vary these parameters over broad ranges . A summary of the parameter values and ranges can be found in Table 1 . The number of hospitalizations and average length of stay for each age group was estimated from the Nationwide Inpatient Sample ( NIS ) , Healthcare Cost and Utilization Project , Agency for Healthcare Research and Quality for the year 2008 . The NIS contains data on ∼8 million records of hospital stays annually from about 1 , 000 hospitals , approximating a 20% stratified sample of US community hospitals , and includes all nonfederal , short-term , general , and specialty hospitals , such as obstetrics-gynecology , ear-nose-throat , orthopedic , and pediatric institutions . The NIS includes public hospitals and academic medical centers but excludes long- and short-term acute rehabilitation facilities , psychiatric hospitals , and alcoholism and chemical dependency treatment facilities . Hospitalization rates were calculated as the average number of hospitalizations per-person per-day by age group . The numbers of individuals for each age group were obtained from the US Census bureau's annual estimates of the resident population by five-year age groups ( www . census . gov ) . Antibiotic usage in the community was estimated based on data from the National Ambulatory Medical Care Survey ( NAMCS ) and the National Hospital Ambulatory Medical Care Survey ( NHAMCS ) for 2008 . NAMCS is an annual national survey of visits to non-federally employed office-based physicians who are primarily engaged in direct patient care , and NHAMCS is designed to collect data on the utilization and provision of ambulatory care services in hospital emergency and outpatient departments and in ambulatory surgery centers . Weighted patient level data was used to estimate the annual number of prescriptions for antibiotics that were written for each age group . The usage rate was calculated as the average number of prescriptions written per person per day per age group . Antibiotic usage in the hospital was estimated based on the data from [20] , which reported antibiotic use from 130 US hospitals ( see Table 1 ) . To calculate the approximate effectiveness of community antibiotic usage on CA- and HA-MRSA , we calculated the number of prescriptions for each antibiotic class and , based on assumptions about the effectiveness of each antibiotic against CA- and HA-MRSA , we estimated the percentage of drug usage that was effective against each pathogen ( Supplementary Table S1 ) . The effectiveness of drugs used in the hospital is similar to the community though skewed towards some of the more effective drugs [20] , [21] . Thus , we assume that the effectiveness of antibiotic usage on CA- and HA-MRSA is slightly more effective in the hospital than in the community ( see Table 1 ) .
We included age-dependent transmission rates for the community by assuming that transmission rates are proportional to the rate of physical contact [19] . Including age structure in this manner substantially broadens the parameter range over which HA- and CA-MRSA can coexist ( Figure 4 ) . This increase is due in part to relative differences in hospitalization between younger and older individuals , which changes the relative difference in selection between HA- and CA-MRSA strains . Because the hospital admission rate and the average length of stay increases as individuals age , older individuals are more likely to spend time in the hospital , where MRSA is favored , and consequently they are more likely to be colonized with HA-MRSA which increases the range over which HA-MRSA is able to persist despite an influx of CA-MRSA from the community . Moreover , the number of physical contacts an older person has in the community is considerably lower than the corresponding number for young persons . This in turn further reduces the selective advantage of CA-MRSA in old age classes . As physical contact occurs preferentially between members of the same or neighboring age classes [19] , this further contributes to maintaining the association between age and strain . An additional source of heterogeneity is treatment itself . We take this heterogeneity into account by explicitly tracking the treatment status of patients and assuming that individuals receiving a given antibiotic cannot be colonized with strains that are susceptible to this drug . Including treatment heterogeneity in this way leads to an additional , substantial extension of the parameter range over which coexistence occurs ( Figure 5 ) . This is because antibiotic prophylaxis of colonization creates a substantial additional selective advantage for HA-MRSA ( which has the broader resistance spectrum ) in the hospital . However , whereas the fraction of protected patients is large in the hospital , it is negligible in the community and hence prophylaxis does not substantially increase the fitness of HA-MRSA in the community . Treatment heterogeneity and age-structure act synergistically to increase coexistence , such that the broadest coexistence range can be observed for the treatment- and age-structured model ( see Figure 5 ) . HA-MRSA is most likely adapted to the hospital environment in other ways than by its broad antibiotic resistance spectrum ( e . g . tolerance to disinfectants , smaller requirements of invasibility , etc . ) [2] , [22] . Accordingly , it is likely better able to compete against CA-MRSA ( in the absence of therapy ) in the hospital as opposed to the community . Taking this effect into account , we find that as the fitness-cost of HA-MRSA in the hospital decreases relative to CA-MRSA , the maximal fitness cost of HA-MRSA for which coexistence occurs is strongly increased . By contrast the minimal cost for coexistence changes only weakly , because reducing the cost of resistance in the hospital does not affect relative fitness in the community ( Figure 6 ) . Thus , context specific fitness costs further facilitate coexistence between HA- and CA-MRSA . It is remarkable that decreasing the cost of HA-MRSA in the hospital has a much stronger effect in the presence of age structure than in its absence ( which indicates that age structure helps separate the hospital from the community ) . Thus there is a synergistic effect between age-structure and hospital specific reduction of fitness costs . The above analysis was based on the ability of one strain to invade the equilibrium defined by the presence of the other strain . This method indicates where the two strains can coexist at equilibrium and therefore allows one to assess the main ecological forces underlying coexistence and competitive exclusion . However , it has three disadvantages: First , the equilibrium might be attained only very slowly: for instance two strains might coexist for a transient period which can extend over decades even though the equilibrium analysis indicates that one strain should exclude the other . Second , even if the two strains coexist one of them might attain only very low levels ( i . e . even though the two strains can coexist in theory , almost all infections are caused by one single strain ) . Third , the pairwise-invasibility approach only allows an analysis of the competitive interaction of two strains , whereas , in reality , several S . aureus strains compete with each other: Notably , HA-MRSA and CA-MRSA compete with methicillin sensitive S . aureus ( MSSA ) , which could modify their interaction . In order to address these issues , we considered a more pragmatic definition of coexistence: We initiated the population either with HA-MRSA as the only resident strain or with two resident strains ( HA-MRSA and MSSA ) and ran the simulation for 30 years . Then we add the new strain ( CA-MRSA ) and examined how the frequencies of each changed over time . Specifically , we tested after 10 , 20 , 50 , 100 , and 200 years , which strains still exist in substantial frequency ( using a threshold of 5% ) . Note that we focused here only on the invasion of HA-MRSA/MSSA equilibrium by CA-MRSA rather than the opposite , since the former describes the current epidemic development ( whereas the latter is merely of theoretical interest ) . We first considered the interaction between CA-MRSA and HA-MRSA ( in analogy to the above analyses ) . We find that the two strains can coexist during a long transient phase ( 10–50 years ) for a broad range of conditions , which do not support coexistence at equilibrium ( see Figure 7 ) . Moreover , we can substantially reduce the range of realistic parameters by considering the interaction between HA-MRSA and MSSA: as we know that HA-MRSA has attained substantial frequencies ( in the USA at least ) after <50 years of methicillin use , the model is only consistent with reality for those parameter-combinations for which this is the case . Figure S2 shows that an invasion of HA-MRSA into the MSSA equilibrium is only possible if the fitness cost of HA-MRSA is below a threshold that is dependent upon the average number of secondary cases caused by the admission of one patient to the hospital containing only susceptible patients ( R0HA , H ) . This threshold is indicated in Figure 7 by the dashed orange line . As it is also a fact that CA-MRSA was able to invade HA-MRSA , the realistic parameter range in Figure 7 is delimited by the dark grey area ( corresponding to parameter values where the CA-MRSA invasion is impossible ) to the left and the orange line to the right . Thus , Figure 7 indicates that we would expect a long-term coexistence between HA-MRSA and CA-MRSA for most realistic parameter combinations . When we consider the interaction between all three strains by including MSSA as one of the initial resident strains , we find that the parameter range in which all three strains can coexist shrinks successively with increasing time ( see Figure 8 ) and eventually vanishes ( results not shown ) . This is not unexpected , as the model structure assumes that the hospital and the community are two different ecological niches , which can thus maximally support the coexistence of only two strains over the long-term . However , we do find that all three strains can coexist for a broad range of conditions during a long transient time-span of several decades . Overall , these results indicate that transient effects can strongly extend the range of coexistence , and even allow for long-term de-facto coexistence where this would not be expected at equilibrium .
We examined how differences in age-structured patterns of antibiotic use and hospitalization rates can promote coexistence of CA- and HA-MRSA . Overall , our results show that hospital and community-associated strains of MRSA can coexist if the broader resistance spectrum of the hospital-associated strains is balanced by intermediate fitness-disadvantages in the absence of treatment . For such intermediate fitness costs , the hospital-associated strains have higher fitness in the hospital , where treatment rates are high , whereas community-associated strains have a higher fitness in the community were treatment rates are low . Despite opposite directions of selection , both strains are present in both environments if there is coexistence at all ( see Figure S3 for example runs ) . This occurs because of the high rates of discharge and hospitalization , which cycle individuals between the hospital and the community . Moreover , our results also indicate that opposite directions of selection are not sufficient for maintaining coexistence . This is especially true for our basic model describing well-mixed populations in the hospital and community , in which we found coexistence only for a very narrow range of HA-MRSA fitness-costs . Including heterogeneity in the form of realistic age- and treatment-structures into the model significantly increases the range of parameters over which coexistence can occur , making it a likely outcome . Furthermore , the fitness cost of HA-MRSA in the absence of treatment is presumably weaker in the hospital than in the community because of factors such as easier invasion due to open wounds , catheters , etc . , as well as increased use of antiseptics to which the hospital strain might be better adapted . Taking this possibility into account leads to an additional , substantial increase in the range over which coexistence is likely . Thus , coexistence between HA-MRSA and CA-MRSA is a likely outcome due to the combined effect of hospital-community interactions , age-structure , treatment-structure , and possibly setting dependent fitness costs in the absence of treatment . Coexistence is mainly dependent upon the cost of HA-MRSA being neither too high nor too low . It should be noted , however , that the upper bound for resistance costs is , in this context , more informative than the lower bound . For costs of HA-MRSA below the lower bound , we would expect that CA-MRSA could not invade the HA-MRSA equilibrium . However , such an invasion is exactly what occurred during the 1990s . Thus , we know that fitness-costs of HA-MRSA are high enough to allow the invasion of CA-MRSA . The crucial question is whether they are low enough for this invasion to stop before CA-MRSA has completely replaced HA-MRSA . The width of the coexistence range depends strongly on how effectively MRSA can transmit in the hospital . In our simulations we quantified this transmissibility as the average number of secondary cases caused by the admission of one patient to the hospital containing only susceptible patients ( RA ) . If this value is considerably smaller than one ( i . e . hospitals cannot maintain the spread of MRSA on their own ) , then the coexistence range becomes very narrow . This is because coexistence relies on opposite directions of selection in the hospital and community environment . If however , one of these environments does contribute only very weakly to transmission , this balancing effect cannot take place . The only published estimate for RA we are aware of found values of 0 . 68 ( 0 . 47–0 . 95 ) and 0 . 93 ( 0 . 71–1 . 21 ) for two Dutch hospitals; one implies a broad and one a narrow coexistence range ( The same study also reported an RA value of 0 . 16 , which however corresponded to an animal derived strain ) [23] . Because the Netherlands has been exceptionally successful in reducing nosocomial spread of MRSA [23] , [24] , RA values are likely to be higher ( and hence coexistence ranges broader ) in most other settings . The sensitivity on RA also implies that in regions with better infection control in hospitals ( and hence lower RA ) one would expect CA-MRSA to completely replace HA-MRSA and hence also to cause most MRSA infections in hospitals . Even though our model realistically includes several levels of population structure , our analysis might still underestimate the range over which CA-MRSA and HA-MRSA can coexist . First , other types of heterogeneity might promote coexistence in a similar way as the ones discussed here . Examples include spatial heterogeneities like rural vs . urban areas , small vs . large hospitals ( which would impose different levels of stochastic effects and thereby affect strain abundances [25] ) , the cycling of older patients into long-term care facilities [26] , or the highly variable length of time individuals remain colonized [27] . We also neglected ( due to the absence of data ) age- or department-structured antibiotic usage rates in hospitals , though this could further promote coexistence . Temporal heterogeneity , such as the seasonal use of antibiotics might be an additional factor contributing to coexistence in MRSA [28] . We have also broadly categorized the multitude of different MRSA strains as either CA- or HA-MRSA . This diversity could also contribute to coexistence , as different strains may have different resistance phenotypes ( It should be noted however that explaining the coexistence of such individual strains is an additional challenge ) . In addition to such heterogeneities , coexistence might be facilitated by co-infection with different strains [29] , [30] , either through co-colonization of the nares [30] or specialization of different strains to different anatomical sites . For instance , CA-MRSA primarily causes infections of the skin , whereas HA-MRSA infections are generally more invasive [2] , [14] . However , it is not clear to what extent different MRSA strains can co-infect a host , and it has also been shown in a different context that co-infection leads only under very specific conditions to coexistence [15] , [16] . Moreover , other studies have shown that colonization with MSSA can be protective from MRSA [31] , [32] , suggesting that competition may limit the extent of co-colonization with different strains . Even though our model can explain the coexistence between HA-MRSA and CA-MRSA , we did not find any parameter combination that supports coexistence at equilibrium between more than two strains ( HA-MRSA , CA-MRSA and MSSA ) . This suggests that the system as described by our model corresponds to only two ecological niches . This implies that the maintenance of the diversity within HA-MRSA and CA-MRSA has to be explained by mechanisms not included in our model ( such as the geographical and temporal variation mentioned above ) . Moreover , Figures 7 , 8 , and S3 also indicate that the system approaches equilibrium only very slowly , such that a long transient maintenance of this diversity is conceivable even if it would not persist in an equilibrium state . Our model also describes a static situation in which the properties of the strains and the age structure do not change over time . However , both demographic change in the human population and evolutionary change of the MRSA strains are likely to occur and their impact on coexistence between competing strains is an interesting question for future studies . Demographic change will most likely increase the proportion of old people in the US and most western countries . In the context of our model this means that selection will tend to favor hospital adapted strains , as the hospitalization rates are considerably higher for the old age classes . However , the direction of evolutionary change depends very strongly on the physiological constraints underlying antibiotic resistance . For instance , if CA-MRSA can increase its resistance spectrum while maintaining a high transmissibility , it could eventually out-compete HA-MRSA . If on the other hand a higher fitness cost is the inevitable consequence of a broad resistance spectrum , then such a replacement is unlikely to occur . Such evolutionary changes may be particularly important given the very long transient phases during which CA- and HA-MRSA can coexist . These long transient phases provide the opportunity for evolutionary adaptation of the inferior strain ( by way of compensatory mutations or extension of the resistance spectrum ) , which could allow it to persist , even though coexistence is not expected on the basis of the current pathogen fitness . The classical ecological paradigm of niche overlap states that two species can coexist if their resource usage differs sufficiently [33] . The present study represents an application of those concepts to the important public health question of whether hospital- and community-associated strains of MRSA are expected to coexist in the long-term . An eventual replacement of HA-MRSA by CA-MRSA could cause important changes in the epidemiology of S . aureus . CA-MRSA can more readily cause infections in healthy individuals than HA-MRSA [18] and hence symptomatic MRSA infections could extend to a broader class of patients . CA-MRSA strains have also been associated with a higher virulence and invasiveness than HA-MRSA strains [34] , as well as worse clinical outcomes [35] , [36] . This higher virulence and invasiveness has been associated with an increased expression of several cytolytic toxins ( such as PVL ) . However , the exact mechanisms underlying the higher virulence of CA-MRSA are still uncertain [34] . An increase in virulence is also not universal , as other studies have described better clinical outcomes associated with CA-MRSA infections [37] , [38] . This may be because CA-MRSA infections are largely associated with skin and soft-tissue infections , which generally have favorable outcomes [38] , [39] . In addition , CA-MRSA strains have a narrower resistance spectrum which makes it easier to provide effective treatment . Overall , while the empirical evidence is mixed , there does seem to be some indication that CA-MRSA differs from HA-MRSA with regards to virulence , the range of resistance , and transmissibility ( see Table 1 in [18] , and [34] ) . Accordingly , a replacement of HA-MRSA with CA-MRSA in hospitals would entail a change in these important properties of nosocomial MRSA infections . More fundamentally , the transmission route of MRSA in hospitals might change . The current view is that MRSA in hospitals is mainly transmitted indirectly through short-term contaminated health-care workers [40] . This dynamic could change should the more invasive and more transmissible CA-MRSA replace HA-MRSA in hospitals . Accordingly , prevention efforts that focus currently on hand-hygiene among health-care workers could lose their effectiveness in reducing the spread of MRSA . Interestingly , our results suggest that a replacement of HA-MRSA by CA-MRSA is especially likely in those locations in which infection control in hospital is currently successful and hence transmission rates in the hospital are low . However , our results also indicate that due to the large heterogeneities characterizing human populations , coexistence between hospital- and community-associated strains of MRSA is overall a likely outcome .
|
One of the most notorious cases of antibiotic-resistant bacteria is methicillin-resistant Staphylococcus aureus ( MRSA ) , which causes diseases ranging from skin and soft-tissue infections to pneumonia and septicemia . Traditionally , MRSA was mainly hospital-associated , but in the past decade community-associated strains have spread widely . Typically drug-resistant bacteria have lower reproduction or transmission rates , called a fitness cost . Because this cost is estimated to be significantly lower for community-associated strains , it has been predicted that these will eventually replace the hospital-associated strains . However , hospital-associated strains are resistant against a greater variety of antibiotics , which may compensate for the higher fitness cost . Here , we integrate realistic data on drug-usage , resistance profiles , contact , and age structures into a mathematical model of MRSA transmission to predict the competition between hospital- and community-associated strains . We find that for a realistic degree of population structure it is likely that both strains of MRSA will coexist in the long term . This results from significantly different hospitalization and antibiotic consumption rates between age groups . In particular , elderly individuals have much higher rates of antibiotic usage and hospitalizations than other age groups . This generates a situation where community-associated strains can predominate in the community but are outcompeted in the hospital , resulting in coexistence in the population .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"public",
"health",
"and",
"epidemiology",
"ecology",
"epidemiology",
"biology",
"microbiology",
"population",
"biology"
] |
2013
|
Hospital-Community Interactions Foster Coexistence between Methicillin-Resistant Strains of Staphylococcus aureus
|
Although models based on independent component analysis ( ICA ) have been successful in explaining various properties of sensory coding in the cortex , it remains unclear how networks of spiking neurons using realistic plasticity rules can realize such computation . Here , we propose a biologically plausible mechanism for ICA-like learning with spiking neurons . Our model combines spike-timing dependent plasticity and synaptic scaling with an intrinsic plasticity rule that regulates neuronal excitability to maximize information transmission . We show that a stochastically spiking neuron learns one independent component for inputs encoded either as rates or using spike-spike correlations . Furthermore , different independent components can be recovered , when the activity of different neurons is decorrelated by adaptive lateral inhibition .
Independent component analysis is a well-known signal processing technique for extracting statistically independent components from high-dimensional data . For the brain , ICA-like processing could play an essential role in building efficient representations of sensory data [1]–[4] . However , although many algorithms have been proposed for solving the ICA problem [5] , only few consider spiking neurons . Moreover , the existing spike-based models [6] , [7] do not answer the question how this type of learning can be realized in networks of spiking neurons using local , biologically plausible plasticity mechanisms ( but see [8] ) . Classic ICA algorithms often exploit the non-Gaussianity principle , which allows the ICA model to be estimated by maximizing some non-Gaussianity measure , such as kurtosis or negentropy [5] . A related representational principle is sparse coding , which has been used to explain various properties of V1 receptive fields [9] . Sparse coding states that only a small number of neurons are activated at the same time , or alternatively , that each individual unit is activated only rarely [10] . In the context of neural circuits , it offers a different interpretation of the goal of the ICA transform , from the perspective of metabolic efficiency . As spikes are energetically expensive , neurons have to operate under tight metabolic constraints [11] , which affect the way information is encoded . Moreover , experimental evidence supports the idea that the activity of neurons in V1 is sparse . Close to exponential distributions of firing rates have been reported in various visual areas in response to natural scenes [12] . Interestingly , certain homeostatic mechanisms are thought to regulate the distribution of firing rates of a neuron [13] . These intrinsic plasticity ( IP ) mechanisms adjust ionic channel properties , inducing persistent changes in neuronal excitability [14] . They have been reported for a variety of systems , in brain slices and neuronal cultures [14] , [15] and they are generally thought to play a role in maintaining system homeostasis . Moreover , IP has been found to occur in behaving animals , in response to learning ( see [14] for review ) . From a computational perspective , it is believed that IP may maximize information transmission of a neuron , under certain metabolic constraints [13] . Additionally , we have previously shown for a rate neuron model that , when interacting with Hebbian synaptic plasticity , IP allows the discovery of heavy-tailed directions in the input [16] . Here , we extend these results for a network of spiking neurons . Specifically , we combine spike-timing dependent plasticity ( STDP ) [17]–[19] , synaptic scaling [20] and an IP rule similar to [16] , which tries to make the distribution of instantaneous neuronal firing rates close to exponential . We show that IP and synaptic scaling complement STDP learning , allowing single spiking neurons to learn useful representations of their inputs for several ICA problems . First , we show that output sparsification by IP together with synaptic learning is sufficient for demixing two zero mean supergaussian sources , a classic formulation of ICA . When using biologically plausible inputs and STDP , complex tasks , such as Foldiák's bars problem [21] , and learning oriented receptive fields for natural visual stimuli , can be tackled . Moreover , a population of neurons learns to extract several independent components if the activity of different neurons are decorrelated by adaptive lateral inhibition . When investigating the mechanisms how learning occurs in our model , we show that IP is necessary for learning , as it enforces a sparse output , guiding learning towards heavy-tailed directions in the input . Lastly , for specific STDP implementations , we show that IP shifts the threshold between potentiation and depression , similar to a sliding threshold for Bienenstock-Cooper-Munro ( BCM ) learning [22] . The underlying assumption behind our approach , implicit in all standard models of V1 receptive field development , is that both input and output information are encoded in rates . In this light , one may think of our current work as a translation of the model in [16] to a spike-based version . However , the principles behind our model are more general than suggested by our work with rate neurons . We show that the same rule can be applied when inputs are encoded as spike-spike correlation patterns , where a rate-based model would fail .
To illustrate the basic mechanism behind our approach , we first ask if enforcing a sparse prior by IP and Hebbian learning can yield a valid ICA implementation for the classic problem of demixing two supergaussian independent sources . In the standard form of this problem , zero mean , unit variance inputs ensure that the covariance matrix is the identity , such that simple Hebbian learning with a linear unit ( equivalent to principal component analysis ) would not be able to exploit the input statistics and would just perform a random walk in the input space . This is , however , a purely mathematical formulation , and does not make much sense in the context of biological neurons . Inputs to real neurons are bounded and —in a rate-based encoding— all positive . Nonetheless , we chose this standard formulation to illustrate the basic underlying principles behind our model . Below , we will consider different spike-based encodings of the input and learning with STDP . As a special case of a demixing problem , we use two independent Laplacian distributed inputs , with unit variance: , . For the linear superposition , we use a rotation matrix : ( 1 ) where is the angle of rotation , resulting in a set of inputs . Samples are drawn at each time step from the input distribution and are mapped into a total input to the neuron as , with the weight vector normalized ) . The neuron's transfer functions , the same as for our spiking model ( Fig . 1 ) , is adapted based on our IP rule , to make the distribution of firing rates exponential . For simplicity , here weights change by classic Hebbian learning: , with being the synaptic learning rate ( see Methods for details ) . Similar results can be obtained when synaptic changes follow the BCM rule . In Fig . 2A we show the evolution of synaptic weights for different starting conditions . As our IP rule adapts the neuron parameters to make the output distribution sparse ( Fig . 2B , C ) , the weight vector aligns itself along the direction of one of the sources . With this simple model , we are able to demix a linear combination of two independent sources for different mixing matrices and different weights constraints ( Fig . 2D ) , as any other single-unit implementation of ICA . After showing that combining IP and synaptic learning can solve a classical formulation of ICA , we focus on spike-based , biologically plausible inputs . In the following , STDP is used for implementing synaptic learning , while the IP and the synaptic scaling implementations remain the same . So far , learning has been restricted to a single neuron . For learning multiple independent components , we implement a neuron population in which the activities of different neurons are decorrelated by adaptive lateral inhibition . This approach is standardly used for feature extraction methods based on single-unit contrast functions [30] . Here , we consider a simple scheme for parallel ( symmetrical ) decorrelation . The all-to-all inhibitory weights ( Fig . 7A ) change by STDP and are subject to synaptic scaling , as done for the input synapses . We only use a rate-based encoding for this case , due to computational overhead , which also limits the size of networks we can simulate . We consider a population of 10 neurons . In order to have a full basis set for the bars problem , we use 2 pixel wide bars . For this case , our learning procedure is able to recover the original basis ( Fig . 7B ) . As lateral inhibition begins to take effect , the average correlation coefficient between the responses of different neurons in the population decreases ( Fig . 7C ) , making the final inhibitory weights unspecific ( Fig . 7D ) . As decorrelation is not a sufficient condition for independence , we show that , simultaneously , the normalized mutual information decreases ( see Methods for details ) . Using the same network for the image patches , we obtain oriented , localized receptive fields ( Fig . 7E ) . Due to the adaptive nature of IP , the balance between excitation and inhibition does not need to be tightly controlled , allowing for robustness to changes in parameters . However , the inhibition strength influences the time required for convergence ( the stronger the inhibition , the longer it takes for the system to reach a stable state ) . A more important constraint is that the adaptation of inhibitory connections needs to be faster than that of feedforward connections to allow for efficient decorrelation ( see Methods for parameters ) . We wondered what the role of IP is in this learning procedure . Does IP simply find an optimal nonlinearity for the neuron's transfer function , given the input , something that could be computed offline ( as for InfoMax [29] ) , or is the interaction between IP and STDP critical for learning ? To answer this question , we go back to Foldiák's bars . We repeat our first bars experiment ( Fig . 4 ) for a fixed gain function , given by the parameters obtained after learning ( , , ) . In this case , the receptive field does not evolve to an IC ( Fig . 8 ) . This suggests that ICA-like computation relies on the interplay between weight changes and the corresponding readjustment of neuronal excitability , which forces the output to be sparse . Note that this result holds for simulation times significantly larger than in the experiment before , where a bar emerged after , suggesting that , even if the neuron would eventually learn a bar , it would take significantly longer to do so . We could assume that the neuron failed to learn a bar for the fixed transfer function just because the postsynaptic firing was too low , slowing down learning . Hence , it may be that a simpler rule , regulating just the mean firing rate of the neuron , would suffice to learn an IC . To test this hypothesis , we construct an alternative IP rule , which adjusts just to preserve the average firing rate of the neuron ( see Methods ) . With the same setup as before and the new IP rule , no bar is learned and the output distribution is Gaussian , with a small standard deviation around the target value ( Fig . 9A ) . However , after additional parameter tuning , a bar can sometimes be learned , as shown in Fig . 9B . In this case , the final output distribution is highly kurtotic , due to the receptive field . The outcome depends on the variance of the total input , which has to be large enough to start the learning process ( variance was regulated by the parameter , see Methods ) . Most importantly , this dependence on model parameters shows that regulating the mean of the output distribution is not sufficient for reliably learning a bar and higher order moments need to be considered as well . A good starting point for elucidating the mechanism by which the interaction between STDP and IP facilitates the discovery of an independent component is our initial problem of a single unit receiving a two dimensional input . We have previously shown in simulations that for a bounded , whitened , two dimensional input the weight vector tends to rotate towards the heavy-tailed direction in the input [16] . Here , we extend these results both analytically and in simulations . Our analysis focuses on the theoretical formulation of zero mean , unit variance inputs used for the demixing problem before and is restricted to expected changes in weights given the input and output firing rates , ignoring the time of individual spikes . We report here only the main results of these experiments , while a detailed description is provided as supplemental information ( see Text S3 ) . Firstly , for conveniently selected pairs of input distributions , it is possible to show analytically that the weight vector rotates towards the heavy-tailed direction in the input , under the assumption that IP adaptation is faster than synaptic learning ( previously demonstrated numerically in [16] ) . Secondly , due to the IP rule , weight changes mostly occur on the tail of the output distribution and are significantly larger for the heavy-tailed input . Namely , IP focuses learning to the heavy tailed direction in the input . When several inputs are supergaussian , the learning procedure results in the maximization of the output kurtosis , independent of the shape of the input distributions . Most importantly , we show that , for simple problems when a solution can be obtained by nonlinear PCA , our IP rule significantly speeds up learning of an independent component . One way to understand these results could be in terms of nonlinear PCA theory . Given that for a random initial weight vector , the total input distribution is close to Gaussian , in order to enforce a sparse output , the IP has to change the transfer function in a way that ‘hides’ most of the input distribution ( for example by shifting somewhere above the mean of the Gaussian ) . As a result , the nonlinear part of the transfer function will cover the ‘visible’ part of the input distribution , facilitating the discovery of sparse inputs by a mechanism similar to nonlinear PCA . In this light , IP provides the means to adapt the transfer function in a way that makes the nonlinear PCA particularly efficient . Lastly , from an information-theoretic perspective , our approach can be linked to previous work on maximizing information transmission between neuronal input and output by optimizing synaptic learning [23] . This synaptic optimization procedure was shown to yield a generalization of the classic BCM rule [22] . We can show that , for a specific family of STDP implementations , which have a quadratic dependence on postsynaptic firing , IP effectively acts as a sliding threshold for BCM learning ( see Text S4 ) .
Although ICA and related sparse coding models have been very successful in describing sensory coding in the cortex , it has been unclear how such computations can be realized in networks of spiking neurons in a biologically plausible fashion . We have presented a network of stochastically spiking neurons that performs ICA-like learning by combining different forms of plasticity . Although this is not the only attempt at computing ICA with spiking neurons , in previous models synaptic changes were not local , depending on the activity of neighboring neurons within a population [6] , [7] . In this light , our model is , to our knowledge , the first to offer a mechanistic explanation of how ICA-like computation could arise by biologically plausible learning mechanisms . In our model , IP , STDP and synaptic scaling interact to give rise to robust receptive field development . This effect does not depend on a particular implementation of STDP , but it does require an IP mechanism which enforces a sparse output distribution . Although there are very good theoretical arguments why this should be the case [11] , [13] , [16] , the experimental evidence supporting this assumption is limited [12] . A likely explanation for this situation is the fact that it is difficult to map the experimentally observable output spikes into a probability of firing . Spike count estimates cannot be used directly , as they critically depend on the bin size . Additionally , the inter-spike interval ( ISI ) of an inhomogeneous Poisson process with exponentially distributed mean is indistinguishable from the ISI of a homogeneous Poisson distribution with mean . Hence , more complex statistical analyses are required for disentangling the two ( see [35] ) . From a computational perspective , our approach is reminiscent of several by-now classic ICA algorithms . As mentioned before , IP enforces the output distribution to be heavy-tailed , like in sparse coding [9] . Our model also shares conceptual similarities to InfoMax [29] , which attempts to maximize output entropy ( however , at the population level ) by regulating the weights and a neuron threshold parameter . Maximizing information transmission between pre- and post-synaptic spike trains under the constraint of a fixed mean postsynaptic firing rate links our method to previous work on synaptic plasticity . A spike-based synaptic rule optimizing the above criterion [23] yields a generalization of the BCM rule [22] , a powerful form of learning , which is able to discover heavy-tailed directions in the input [36] , [37] and to learn Gabor receptive fields [38] in linear neurons . We have shown that , sliding threshold BCM can be viewed as a particular case of IP learning , for a specific family of STDP models . It is interesting to think of the mechanism presented here in relation to projection pursuit [39] , which tries to find good representations of high-dimensional spaces by projecting data on a lower dimensional space . The algorithm searches for interesting projection directions , a typical measure of interest being the non-Gaussianity of the distribution of data in the lower dimensional space . The difference here is that , although we do not explicitly define a contrast function maximizing kurtosis or other similar measure , our IP rule implicitly yields highly kurtotic output distributions . By sparsifying the neuron output , IP guides the synaptic learning towards the interesting ( i . e . heavy-tailed ) directions in the input . From a different perspective , we can relate our method to nonlinear PCA . It is known that , for zero mean whitened data , nonlinear Hebbian learning in a rate neuron can successfully capture higher order correlations in the input [40] , [41] . Moreover , it has been suggested that the precise shape of the Hebbian nonlinearity can be used for optimization purposes , for example for incorporating prior knowledge about the sources' distribution [40] . IP goes one step further in this direction , by adapting the transfer function online , during learning . From a biological perspective , there are some advantages in adapting the neuron's excitability during computation . Firstly , IP speeds up the nonlinear decorrelation of inputs . Secondly , the system gains great robustness to changes in parameters ( as demonstrated in Text S2 ) . Additionally , IP regulation plays a homeostatic role , making constraints on the input mean or second order statistics unnecessary . In the end , all the methods we have mentioned are closely related and , though conceptually similar , our approach is another distinct solution . Our previous work was restricted to the a rate model neuron [16] . Beyond translating our results to a spiking neuron model , we have shown here that similar principles can be applied when information is encoded as spike-spike correlations , where a model relying just on firing rates would fail . It is a interesting challenge for future work to further investigate the exact mechanisms of receptive field development for different types of input encoding .
We consider a stochastically spiking neuron with refractoriness [23] . The model defines the neuron's instantaneous probability of firing as a function of the current membrane potential and the refractory state of the neuron , which depends on the time since its last spike . More specifically , the membrane potential is computed as where is the resting potential , while the second term represents the total incoming drive to the neuron , computed as the linear summation of post-synaptic potentials evoked by incoming spikes . Here , gives the strength of synapse , is the time of a presynaptic spike , and the corresponding evoked post-synaptic potential , modeled as a decaying exponential , with time constant ( for GABA-ergic synapses , ) and amplitude . The refractory state of the neuron , with values in the interval , is defined as a function of the time of the last spike , namely:where gives the absolute refractory period , is the relative refractory period and is the Heaviside function . The probability of the stochastic neuron firing at time is given as a function of its membrane potential and refractory state [23] where is the time step of integration , and is a gain function , defined as: Here , and are model parameters , whose values are adjusted by intrinsic plasticity , as described below . Our intrinsic plasticity model attempts to maximize the mutual information between input and output , for a fixed energy budget [16] , [42] . More specifically , it induces changes in neuronal excitability that lead to an exponential distribution of the instantaneous firing rate of the neuron [13] . The specific shape of the output distribution is justified from an information theoretic perspective , as the exponential distribution has maximum entropy for a fixed mean . This is true for distributions defined on the interval , but , under certain assumptions , can be a good approximation for the case where the interval is bounded , as it happens in our model due to the neuron's refractory period ( see below ) . Optimizing information transmission under the constraint of a fixed mean is equivalent to minimizing the Kullback-Leibler divergence between the neuron's firing rate distribution and that of an exponential with mean :with and denoting the entropy and the expected value . Note that the above expression assumes that the instantaneous firing rate of the neuron is proportional to , that is that . When taking into account the refractory period of the neuron , which imposes an upper-bound on the output firing rate , the maximum entropy distribution for a specific mean is a truncated exponential [43] . The deviation between the optimal exponential for the infinite and the bounded case depends on the values of and , but it is small in cases in which . Hence , our approximation is valid as long as the instantaneous firing rate is significantly lower than , that is when the mean firing rate of the neuron is small . In our case , we restrict . If not otherwise stated , all simulations have . Note also that the values considered here are in the range of firing rates reported for V1 neurons [44] . Computing the gradient of for , and , and using stochastic gradient descent , the optimization process translates into the following update rules [42]:Here , is a small learning rate . Here , the instantaneous firing rate is assumed to be directly accessible for learning . Alternatively , it could be estimated based on the recent spike history . Additionally , as a control , we have considered a simplified rule , which adjusts a single transfer function parameter in order to maintain the mean firing rate of the neuron to a constant value . More specifically , a low-pass-filtered version of the neuron firing rate is used to estimate the current mean firing rate of the neuron where is the Dirac function and is the time of firing of the post-synaptic neuron and . Based on this estimate , the value of the parameter is adjusted as Here , is the goal mean firing rate , as before and is a learning rate , set such that , for a fixed Gaussian input distribution , convergence is reached as fast as for our IP rule described before ( ) . The STDP rule implemented here considers only nearest-neighbor interactions between spikes [24] . The change in weights is determined by:where is the amplitude of the STDP change for potentiation and depression , respectively ( default values and ) , are the time scales for potentiation and depression ( , ; for learning spike-spike correlations ) [19] , and is the time difference between the firing of the pre- and post-synaptic neuron . For the lateral inhibitory connections , the STDP learning is faster , namely . In all cases , weights are always positive and clipped to zero if they become negative . This STDP implementation is particularly interesting as it can be shown that , under the assumption of uncorrelated or weakly correlated pre- and post-synaptic Poisson spike trains , it induces weight changes similar to a BCM rule , namely [24]:where and are the firing rates of the pre- and post-synaptic neuron , respectively . For the above expression , the fixed BCM threshold can be computed as:which is positive when potentiation dominates depression on the short time scale , while , overall , synaptic weakening is larger than potentiation: In some experiments we also consider the classical case of additive all-to-all STDP [26] , which acts as simple Hebbian learning , the induced change in weight being proportional to the product of the pre- and post-synaptic firing rates ( see [24] for comparison of different STDP implementations ) . The parameters used in this case are: , and the same time constants as for the nearest neighbor case . Additionally , the simple triplets STDP model used as an alternative BCM-like STDP implementation is described in Text S4 . As in approaches which directly maximize kurtosis or similar measures [16] , [30] , [40] , the weight vector is normalized: , with , with weights being always positive . This value is arbitrary , as it represents a scaling factor of the total current , which can be compensated for by IP . It was selected in order to keep the final parameters close to those in [23] . Additionally , for the natural image patches the normalization was done independently for the on- and off- populations , using the same value for in each case . In a neural population , the same normalization is applied for the lateral inhibitory connections . As before , weights do not change sign and are constrained by the norm: , with . Currently , the normalization is achieved by dividing each weight by , after the presentation of each sample . Biologically , this operation would be implemented by a synaptic scaling mechanism , which multiplicatively scales the synaptic weights to preserve the average input drive received by the neuron [20] . In all experiments , excitatory weights were initialized at random from the uniform distribution and normalized as described before . The transfer function was initialized to the parameters in [23] ( , , ) . Unless otherwise specified , all model parameters had the default values defined in the corresponding sections above . For all spike-based experiments , each sample was presented for a time interval , followed by the weight normalization . For the experiments involving the rate-based model and a two-dimensional input , each sample was presented for one time step and the learning rates for IP and Hebbian learning were and , respectively . In this case , the weight normalization procedure can influence the final solution . Namely , positive weights with constant norm always yield a weight vector in the first quadrant , but this limitation can be removed by a different normalization , which keeps the norm of the vector constant ( ) . For the demixing problem , the input was generated as described for the rate-based scenario above . After the rectification , the firing rates of the input on the on- and off- channels were scaled by a factor of 20 , to speed up learning . After convergence , the total weight of each channel was estimated as the sum of individual weights corresponding to that input . The resulting four-dimensional weight vector was projected back to the original two-dimensional input space using: , with a sign given by that of the channel with maximum weight ( positive for , negative otherwise ) . This procedure results by a minimum error projection of the weight vector onto the subspace defined by the constraint , see Text S1 for details . For all variants of the bars problem , the input vector was normalized to , with defining the norm , as in [45] . Inputs were encoded using firing rates with mean , where is the frequency of a background pixel and gives the maximum input frequency , corresponding to a sample containing a single bar in the original bars problem . When using the correlation-based encoding , all inputs had the same mean firing rate ( ) . Inputs corresponding to pixels in the background were uncorrelated , while inputs belonging to bars were all pairwise correlated , with a correlation coefficient . Poisson processes with such correlation structure can be generated in a computationally efficient fashion by using dichotomous Gaussian distributions [46] . When learning Gabor receptive fields , images from the van Hateren database [31] were convolved with a difference-of-gaussians filter with center and surround widths of and pixels , respectively . Random patches of size were selected from various positions in the images . Patches having very low contrast were discarded . The individual input patches were normalized to zero mean and unit variance , similar to the processing in [45] . The rectified values of the resulting image were mapped into a firing frequency for an on- and off-input population ( ) and , as before , samples were presented for a duration . For a neuronal population , input-related parameters were as for the single component , but with , to speed up learning . The initial parameters of the neuron transfer function were uniformly distributed around the default values mentioned above , with variance 0 . 1 , 5 , and 0 . 2 for , , and , respectively . Additionally , the inhibitory weights were initialized at random , with no self-connections , and normalized as described before . The mutual information ( MI ) , estimated within a window of 1000 s , was computed as , with denoting the entropy ( see [45] ) , applied for the average firing rate of the neurons for each input sample .
|
How the brain learns to encode and represent sensory information has been a longstanding question in neuroscience . Computational theories predict that sensory neurons should reduce redundancies between their responses to a given stimulus set in order to maximize the amount of information they can encode . Specifically , a powerful set of learning algorithms called Independent Component Analysis ( ICA ) and related models , such as sparse coding , have emerged as a standard for learning efficient codes for sensory information . These algorithms have been able to successfully explain several aspects of sensory representations in the brain , such as the shape of receptive fields of neurons in primary visual cortex . Unfortunately , it remains unclear how networks of spiking neurons can implement this function and , even more difficult , how they can learn to do so using known forms of neuronal plasticity . This paper solves this problem by presenting a model of a network of spiking neurons that performs ICA-like learning in a biologically plausible fashion , by combining three different forms of neuronal plasticity . We demonstrate the model's effectiveness on several standard sensory learning problems . Our results highlight the importance of studying the interaction of different forms of neuronal plasticity for understanding learning processes in the brain .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"neuroscience",
"neuroscience/theoretical",
"neuroscience",
"neuroscience/sensory",
"systems",
"neuroscience/neural",
"homeostasis"
] |
2010
|
Independent Component Analysis in Spiking Neurons
|
A Global Programme to Eliminate Lymphatic Filariasis was launched in 2000 , with mass drug administration ( MDA ) as the core strategy of the programme . After completing 13 years of operations through 2012 and with MDA in place in 55 of 73 endemic countries , the impact of the MDA programme on microfilaraemia , hydrocele and lymphedema is in need of being assessed . During 2000–2012 , the MDA programme made remarkable achievements – a total of 6 . 37 billion treatments were offered and an estimated 4 . 45 billion treatments were consumed by the population living in endemic areas . Using a model based on empirical observations of the effects of treatment on clinical manifestations , it is estimated that 96 . 71 million LF cases , including 79 . 20 million microfilaria carriers , 18 . 73 million hydrocele cases and a minimum of 5 . 49 million lymphedema cases have been prevented or cured during this period . Consequently , the global prevalence of LF is calculated to have fallen by 59% , from 3 . 55% to 1 . 47% . The fall was highest for microfilaraemia prevalence ( 68% ) , followed by 49% in hydrocele prevalence and 25% in lymphedema prevalence . It is estimated that , currently , i . e . after 13 years of the MDA programme , there are still an estimated 67 . 88 million LF cases that include 36 . 45 million microfilaria carriers , 19 . 43 million hydrocele cases and 16 . 68 million lymphedema cases . The MDA programme has resulted in significant reduction of the LF burden . Extension of MDA to all at-risk countries and to all regions within those countries where MDA has not yet reached 100% geographic coverage is imperative to further reduce the number of microfilaraemia and chronic disease cases and to reach the global target of interrupting transmission of LF by 2020 .
Lymphatic filariasis ( LF ) is a disease of the poor that is prevalent in 73 tropical and sub-tropical countries . LF is caused by three species of filarial worms – Wuchereria bancrofti , Brugia malayi and B . timori – and is transmitted by multiple species of mosquitoes . The disease is expressed in a variety of clinical manifestations , the most common being hydrocele and chronic lymphedema/elephantiasis of the legs or arms . People affected by the disease suffer from disability , stigma and associated social and economic consequences . Marginalized people , particularly those living in areas with poor sanitation and housing conditions are more vulnerable and more affected by the disease . Estimates made in 1996 indicated that 119 million people were infected with LF at that time , 43 million of them having the clinical manifestations ( principally lymphedema and hydrocele ) of chronic LF disease [1] . Earlier severe resource constraints and lack of operationally feasible strategies in the endemic countries left a significant proportion of the LF endemic population living unprotected and exposed to the risk of LF infection . Despite a long-standing and gloomy outlook for these individuals , the situation turned around dramatically in the 1990s for 2 principal reasons: 1 ) advances made in point-of-care diagnostics and 2 ) the finding of the long-term effectiveness of anti-filarial drugs given in single doses that permitted development of the strategy of annual two-drug , single-dose mass drug administration ( MDA ) to control/eliminate LF [2] , [3] . As LF had already been postulated to be an eradicable disease [4] and with the success experienced in LF elimination activities in China [5] and elsewhere , the World Health Assembly ( WHA ) in May 1997 formulated resolution WHA 50 . 29 urging all endemic countries to increase their efforts and determination to control and eliminate LF . In response , the WHO was able to launch the Global Programme to Eliminate LF ( GPELF ) in the year 2000 , largely because the manufacturers of albendazole ( ALB ) and ivermectin , two of the principal drugs used in the GPELF MDAs , donated these drugs for as long as needed to eliminate LF [3] . The principal strategy of the programme has been two-fold: 1 ) to implement MDA programmes in all endemic areas to achieve total interruption of transmission and ( 2 ) to provide effective morbidity management in order to alleviate the suffering in people already affected by filarial disease . The GPELF targets elimination of LF , at least as a public health problem , by the year 2020 [6] . The programme to implement MDAs targeting LF ( GPELF ) completed 13 years of operations in 2012 [7] . With its ambitious goal to eliminate LF by the year 2020 , it is essential that progress toward this goal be assessed repeatedly in order to set benchmarks to guide future programmatic planning . How to define and assess this progress remains a challenge , but two strategies have been suggested . The first is to measure reduction in the burden of LF disease ( i . e . , hydrocele , lymphedema , microfilaraemia and associated subclinical disease ) over the past 13 years – i . e . , a clinical perspective; the second is to measure reduction in the risk of acquiring infection for populations living in ( formerly ) endemic areas – i . e . , an epidemiologic perspective . In the present report we have pursued the first alternative – to model the decreased burden of LF ( defined for the purposes of our calculations as hydrocele , lymphedema , and microfilaraemia ) in order to assess the progress towards LF elimination from inception of the MDA programme through 2012 ( i . e . , during GPELF's first 13 years ) . In a parallel study , others have recently modeled the programme's progress from the alternative , risk-of-infection viewpoint ( Hooper et al . , submitted ) .
The GPELF aims to provide MDA ( using ALB+either ivermectin or diethylcarbamazine [DEC] ) to entire endemic populations at yearly intervals for 4–6 years . Such a programme , if implemented effectively ( i . e . treating at least 65% of the total population during each MDA ) , is expected to interrupt transmission and eliminate LF [8] . Because the status of MDA activities in all of the 73 endemic countries at the time of this analysis ( through 2012 ) ranged from no MDA at all in some countries to full completion of the MDAs in others , for the present study each country was evaluated separately . First , programme impact was determined for each endemic country; then , the burden of LF remaining in each of the five endemic WHO regions – Southeast Asia ( SEAR ) , Africa ( AFR ) , Western Pacific ( WPR ) , Eastern Mediterranean ( EMR ) and America ( AMR ) - was calculated by summing the remaining LF burden for all the endemic countries within each region . Calculating progress of the MDA programme under GPELF – whether by burden or risk estimates – is affected by a number of important specific factors , namely; ( 1 ) the number of countries that have successfully completed implementing the MDA programme , ( 2 ) the number of countries currently implementing the programme and the geographical coverage or proportion of the endemic population targeted so far in each country , ( 3 ) the treatment coverage of the population targeted for MDA in each country , and ( 4 ) the duration of the programme ( i . e . , the number of rounds of MDA implemented ) in each country . For the present analysis , all of these data have been sourced from the WHO PC data bank [9] . There are 3 essential steps to assessing the decrease of LF burden since 2000: first , the establishment of the LF base-line burden ( in 2000 ) ; then , estimation of the MDA impact for countries or IUs where MDAs have taken place during 2000–2012; and , finally , estimation of current burden for countries or IUs where no MDA has taken place . Treatment of LF has been shown to be especially effective and beneficial in children . Prevalence and intensity of childhood infections are relatively low [34] , [35] , and MDA is particularly effective in clearing them [14] , [17] , [18] , [36] . Assessment carried out after two rounds of MDA suggests that the treatment is able to clear infection in 0–5 year age children [14] , [18]; children of 1–10 year age were shown to become free from infection after 2–4 rounds of MDA [18] , [20]; and , further , single dose treatment can reverse lymphatic pathology in children [36] . Also , since the MDA exerts an impact on transmission from the first treatment round itself , it offers excellent protection to newborns from acquiring LF [14] , [15] , [17] , [18] , [20] , [37] . Therefore , for all these reasons the present analysis has considered that the children of 0–5 years in the communities that received one or more MDAs will be free from microfilaraemia and disease . In addition , the children of 0–10 year age in the communities with TI of ≥3 ( equivalent to receiving about four rounds of MDA ) were considered free from microfilaraemia and disease . Therefore , the impact of the MDAs on LF burden has been treated separately for children and adults .
GPELF had a modest start – only 14 of the 81 countries then identified as endemic were able to develop and implement MDA programmes in 2000 , the first year of operations , and the target population was 3 . 2 million . Nevertheless , the programme scaled up progressively , so that by 2005 , national programmes were in place in 42 countries with a target population of 610 million [38] . During the subsequent years , further progress has been made . In 2011 , 9 countries with a previous history of low prevalence were re-evaluated and declared non-endemic , leaving 73 countries with a combined endemic population of 1 , 459 million . By 2013 , 13 of the 73 endemic countries had completed the MDA phase of the programme and entered into the post-MDA surveillance phase , 42 countries were implementing the programme , but 18 countries still had no programme in place . These 18 countries – 15 of them in the Africa region - account for about 10% of the global endemic population of 1 , 459 million still living in 73 endemic countries [9] . The status of the programme in terms of number of treatments offered and consumed , as of 2012 in different regions , is summarized in Table 2 . Of the 1 , 459 million endemic population , 975 million individuals ( 67% ) have been targeted by 2012 . The 975 million population has been offered a total of 6 . 37 billion treatments during 2000–2012 . The distribution of treatments is noticeably uneven among the two major endemic regions , Africa and South-East Asia . Whereas Africa has 32% of the endemic population , it accounts for only 13% of the total treatments offered , while South-east Asia is home to 62% of the endemic population but accounts for 82% of the treatments offered ( Table 3 ) . India alone , with 42% of the endemic population accounts for 71% of the total global treatments offered to date . Of the total 6 . 37 billion treatments provided , 4 . 45 billion or 70% of treatments were reported as consumed by the endemic populations . In addition to the 18 countries that had not yet started the programme by 2012 , there were also several regionally major endemic countries that had initially launched their programmes but then progressed slowly , principally because of logistic difficulties , funding challenges , lack of political support , civil strife , or , in the case of many Central African countries , the coexistence of loaisis , a contraindication for treating LF with the standard MDA drug regimens [39] . These large countries ( including Nigeria , Tanzania , Kenya , Sudan , Papua New Guinea and Indonesia ) have an endemic population of 398 million and account for 27% of the global endemic population . ( Many of these countries have accelerated their programmes significantly since that time ) .
Prior to the GPELF , efforts to control LF met with little success , largely because of the lack of feasible and affordable strategies . Even most of the countries that initiated control programmes in the 1950s could make only marginal progress because of the relatively low priority for LF control and lack of feasible , scalable control strategies . The advent of preventive chemotherapy-based annual MDA programmes and the launching of GPELF provided great stimulus toward the control and elimination of LF and its very significant health and socio-economic consequences . Single dose treatment was shown to be very effective against LF infection [2] , and mass administration of such single dose treatment was shown to be both broadly feasible [43] and comparatively inexpensive [44] , [45] . Availability of donated drugs [46] and the implementation support by international organizations and aid agencies [3] , [47] provided further impetus to launch the MDA programme . These factors have enabled as many as 55 countries to undertake national MDA programmes targeting LF elimination . In these countries , an unprecedented 6 . 37 billion treatments were made available during 2000–12 period [9] , making the preventive chemotherapy for LF elimination one of the largest ever public health interventions . The scale of the programme also highlights not only the positive response of endemic countries to accept the challenge of implementing interventions that are ‘simple’ and feasible but also the ability of these countries – some of them among the least resourced – to implement these very large-scale public health programmes successfully . Given all of this implementation success , it is now essential that the disease-specific health impact of these programmes be assessed as well . While there are , indeed , many important clinical consequences of LF infection ( including renal pathology [48] , acute episodic ADL [41] , [42] , [49] and others [50] , because the manifestations most frequently measured are microfilaraemia , hydrocele and lymphedema/elephantiasis , it is these that we have tracked in modeling GPELF's impact on the burden of LF disease . LF infection in individuals goes through different phases , beginning with pre-patent infection , then progressing to microfilaraemia , acute manifestations and chronic disease . The anti-filarial drug regimens used in the GPELF – ALB+either DEC or ivermectin – exhibit excellent microfilaricidal effect even in single doses at both the individual and community level [12]–[21] . Hence , as expected , thirteen years of an MDA programme that delivered 6 . 37 billion treatments with an intake of 4 . 45 billion treatments ( Table 2 ) , has prevented or cured an estimated 79 . 20 million microfilaraemia cases in the endemic countries . Currently , as projected in this study , there are still an estimated 36 . 45 million Mf cases , a figure that is still high but that would have been an astounding 115 . 65 million cases , had there not been an MDA programme under GPELF ( Table 4 ) . This also means that the consequences of microfilaraemia , which include LF progression to chronic disease in a proportion of those 79 . 20 million people , were averted as well ( see below ) . The direct effects of treatment with anti-filarial drugs are less remarkable against chronic disease manifestations than on microfilaraemia . However , several studies have shown that treatment does , indeed , have significant impact on chronic disease manifestations , ranging from reversal of early disease signs and symptoms to actual reversal of some of the chronic lesions . The presence of adult worms alone is sufficient to cause hydrocele [50] and reduction in adult worm burden is understandably able to lead to reduction in hydrocele prevalence . The anti-filarial drugs used in the MDA programme - albendazole plus ivermectin , as well as DEC alone or with ALB - exhibit at least partial adulticidal effect , thereby reducing the adult worm burden [51] , [52] and hydrocele prevalence in treated individuals [24]–[28] . When the relationship between treatment doses and the reduction in hydrocele prevalence ( Fig . 2 ) was extrapolated to the MDA programme , a reduction of 18 . 73 million hydrocele cases was projected ( Table 4 ) - reflecting both the prevention of new hydrocele cases , particularly in the younger population , and the cure of hydrocele in a proportion of those older , already affected individuals . Relatively fewer studies have examined the impact of single- or repeated , annual single-dose treatment on lymphedema and elephantiasis . In Indonesia and Tahiti very high reduction i . e . 68% to 80% in lymphedema prevalence was observed after 82 mostly weekly doses and 12 monthly doses respectively [24] , [30] . However , the impact of typical annual MDA was critically evaluated only in two studies , one each in India and Papua New Guinea . The reductions were 14% after 7 rounds of MDA in the Indian study using DEC alone [29] , and 20% after 4 rounds of MDA , using DEC alone in Papua New Guinea [13] . Taking various studies into account , we assumed conservatively that in communities with TI of 3 and above , which is equivalent to nearly four rounds of MDA , a 14% reduction in lymphedema prevalence is achieved . This conservative approach was adopted not only to avoid overestimation of the programme impact but also because most of the MDA implementing countries have not yet established robust national morbidity management programmes , whose benefits on disease-improvement will be substantial from controlling the bacterial superinfection of affected limbs that is essential to the progression of elephantiasis [50] . Our analysis suggests that , even despite this conservative modeling approach , an estimated 5 . 49 million lymphedema cases were prevented or cured by the MDA programme in its first 13 years ( Table 4 ) . While those born during and after transmission has been interrupted will have no risk of lymphedema , from a practical standpoint it will still be essential to institute morbidity management programmes in order to achieve significant relief for those already affected . The estimated disease-specific impact of 13 years of the GPELF ( Table 4 ) has been calculated on the basis only of microfilaremia , hydrocele and lymphedema/elephantiasis , but it is clear that other very significant effects on reducing LF burden have been achieved as well . For example , 79 . 2 million cases of microfilaremia were projected to have been averted by the Programme ( see above ) , and since nearly 50% of Mf carriers show renal abnormalities which resolve with treatment [48] , several million Mf carriers can be recognized to have benefited from resolution of such renal abnormalities as well . Also , since the transmission of LF is generally proportional to the number of Mf carriers and the intensity of microfilaraemia in communities [53] , such a significant reduction in the number of Mf carriers also means considerable decrease in transmission of LF in the treated communities; and , of course , transmission reduction and its ultimate interruption determine the elimination of LF , the principal objective of the MDA programmes . Similarly , the projected reduction in chronic LF cases – 18 . 73 million hydrocele cases and 5 . 49 million lymphedema cases– is estimated to have averted 39 million acute ADL episodes in endemic areas . This is expected to result in significant relief to the infected population , as ADL , though transient , inflicts severe suffering , makes affected people bed ridden [41] , [42] , [54]–[56] and requires recuperation from these episodes often extending for weeks at a time . In an earlier study [57] , it was estimated that eight years of MDA , under which >1 . 9 billion treatments were delivered , prevented 7 . 4 million cases of hydrocele and 4 . 3 million cases of lymphedema . While these estimates on the number of hydrocele cases prevented are similar to the estimates in the present study , there is less agreement on the number of lymphedema cases prevented . The estimated 5 . 49 million lymphedema cases prevented in this study , after 13 years of MDA and delivery of 6 . 37 billion treatments , was lower , likely because of both the different strategies for calculating the effects and the conservative approach adopted in assessing the impact of MDA on lymphedema . The estimated 5 . 49 million lymphedema cases prevented in this study was a minimum number , and the actual reduction may be much higher . Of the various factors influencing the outcome of MDA programmes , treatment coverage is particularly important [8] . In this study , the impact of MDA was assessed using the reported treatment coverage – i . e . the treatment coverage reported by the country level programme managers and compiled in WHO's PC data bank [9] . There are , however , a number of reports suggesting that the programme-reported treatment coverage in the South-east Asia region , particularly in India , may be higher than the actual treatment coverage in the communities . For example , while programme-reported treatment coverage in India was generally in the range of 58% to 90% , various independent studies showed treatment coverage that varied widely and ranged from <20% to >90% in different parts of the country [58]–[74] . The data from these published studies give rise to an average ‘evaluated’ treatment coverage rate of 51 . 0% , less than the 71 . 33% average reported national coverage [9] . Since the TI used to calculate programme impact in our model incorporates programme coverage , it is necessary to understand the effect of this difference between reported and evaluated coverage . For India , the TI based on reported coverage was 5 . 27 , but only 4 . 21 when based on ‘evaluated’ coverage – a difference of 20% . Interestingly , however , when those different TI's were applied to the model ( Figs . 1 & 2 ) , the effect was minimal , because for TI's >4 , little or no additional benefit was achieved on the 3 parameters measured ( microfilaraemia , hydrocele , lymphedema/elephantiasis ) . In other words , the initial rounds of MDA will exert greater impact on these manifestations compared to later rounds , a finding already reported empirically and shown in various studies [12] , [13] , [15] , [17]–[20] . However , if the treatment coverage rate is high , a higher TI can be achieved in the early rounds of the programme , and fewer rounds of MDA may be required to maximize both impact and cost-effectiveness . It is possible that preventive chemotherapy as well as other interventions implemented against other vector-borne diseases have added to the impact of LF MDA and caused further reduction in LF burden in some countries . Principal among these other interventions are the ivemectin distribution under the African Programme for Onchocrciasis Control ( APOC ) and the malaria control measures of insecticide treated nets ( ITN ) and indoor residual spraying ( IRS ) . Currently , ivermectin is distributedfor onchocerciasis control in as many as 26 countries in Africa , covering nearly 130 million population [75] . Most of the 26 countries are co-endemic for LF also and while less than half of this LF-endemic population is under specific treatment as part of the GPELF , many are likely receiving benefit from the ivermectin being used for onchocerciasis control , as has been demonstrated specifically in a number of countries in West Africa [76]–[80] . Similarly , the malaria control measures have been shown to reduce LF transmission considerably and remain promising adjuncts to the MDA of the GPELF activities [81]–[83] . While these coincident intervention measures have , and will continue to have , positive impact on the LF elimination efforts , quantification of their impact remains a daunting challenge . The reduction in LF burden achieved during the GPELF's first 13 years is almost certainly higher than shown through our analyses both because of the additional , on-going intervention measures and because of our conservative approach to estimating the impact on chronic disease . Though , there can be little question that impressive gains in decreasing LF burden have been achieved as a result of 13 years of MDA in the GPELF , still , however , a considerable burden of LF remains – estimated at 36 . 45 million Mf cases , 16 . 68 million cases of lymphedema and 19 . 43 million cases of hydrocele ( Table 4 ) . Extension of MDA to all at-risk countries and to all regions within those countries where MDA has not yet started is absolutely necessary to reduce the number of microfilaraemia cases and transmission . Such an extension of MDA will also reduce a proportion of hydrocele and lymphedema cases , but the burden of LF disease needs also to be approached directly . Techniques for effective morbidity management – both medical and surgical – are available but not nearly so widely implemented as they could or should be . The present model's calculations take into consideration only those burden-reducing benefits coming pari passu with MDA implementation . When appropriate morbidity management strategies are finally introduced and accelerated , the burden of LF disease will fall even more dramatically ( and the model can be adapted accordingly ) .
|
The mass drug administration ( MDA ) programme to eliminate lymphatic filariasis ( LF ) was initiated in 2000 . By the end of 2012 , the programme was in place in 55 endemic countries . During these first 13 years ( 2000–2012 ) of programme implementation , 6 . 37 billion annual single dose anti-filarial treatments were offered and 4 . 45 billion doses were consumed by the target populations . This massive programme is estimated to have prevented or cured 96 . 71 million LF cases that include 79 . 20 million microfilaria carriers , 18 . 73 million hydrocele cases and a minimum of 5 . 49 million lymphedema cases , a 59% reduction of initial LF levels . It is further estimated that , currently , i . e . after 13 years of the MDA programme , 67 . 88 million LF cases remain , including 36 . 45 million microfilaria carriers , 19 . 43 million hydrocele cases and 16 . 68 million lymphedema cases . Progressive reduction in this burden is possible as the programme extends to the endemic countries and regions within endemic countries that have not yet been covered by the MDA programme , and if the morbidity management component of the programme can be effectively implemented .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"helminth",
"infections",
"medicine",
"and",
"health",
"sciences",
"filariasis",
"neglected",
"tropical",
"diseases",
"tropical",
"diseases",
"parasitic",
"diseases",
"lymphatic",
"filariasis"
] |
2014
|
Progress and Impact of 13 Years of the Global Programme to Eliminate Lymphatic Filariasis on Reducing the Burden of Filarial Disease
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Bacterial Sec7-domain-containing proteins ( RalF ) are known only from species of Legionella and Rickettsia , which have facultative and obligate intracellular lifestyles , respectively . L . pneumophila RalF , a type IV secretion system ( T4SS ) effector , is a guanine nucleotide exchange factor ( GEF ) of ADP-ribosylation factors ( Arfs ) , activating and recruiting host Arf1 to the Legionella-containing vacuole . In contrast , previous in vitro studies showed R . prowazekii ( Typhus Group ) RalF is a functional Arf-GEF that localizes to the host plasma membrane and interacts with the actin cytoskeleton via a unique C-terminal domain . As RalF is differentially encoded across Rickettsia species ( e . g . , pseudogenized in all Spotted Fever Group species ) , it may function in lineage-specific biology and pathogenicity . Herein , we demonstrate RalF of R . typhi ( Typhus Group ) interacts with the Rickettsia T4SS coupling protein ( RvhD4 ) via its proximal C-terminal sequence . RalF is expressed early during infection , with its inactivation via antibody blocking significantly reducing R . typhi host cell invasion . For R . typhi and R . felis ( Transitional Group ) , RalF ectopic expression revealed subcellular localization with the host plasma membrane and actin cytoskeleton . Remarkably , R . bellii ( Ancestral Group ) RalF showed perinuclear localization reminiscent of ectopically expressed Legionella RalF , for which it shares several structural features . For R . typhi , RalF co-localization with Arf6 and PI ( 4 , 5 ) P2 at entry foci on the host plasma membrane was determined to be critical for invasion . Thus , we propose recruitment of PI ( 4 , 5 ) P2 at entry foci , mediated by RalF activation of Arf6 , initiates actin remodeling and ultimately facilitates bacterial invasion . Collectively , our characterization of RalF as an invasin suggests that , despite carrying a similar Arf-GEF unknown from other bacteria , different intracellular lifestyles across Rickettsia and Legionella species have driven divergent roles for RalF during infection . Furthermore , our identification of lineage-specific Arf-GEF utilization across some rickettsial species illustrates different pathogenicity factors that define diverse agents of rickettsial diseases .
Bacteria invading eukaryotic cells employ diverse strategies for successful entry , intracellular colonization and intercellular spread [1 , 2] . Whether facultative or obligate , intracellular species must either modify the phagocytic vacuole for survival or lyse the phagosome and live freely within the host cytoplasm ( or invade other cellular organelles ) [3–6] . Either strategy is delicately underpinned by bacterial secretion of effectors , which have a myriad of characterized functions: e . g . , engaging host signaling pathways , rearranging the host cytoskeleton , polymerizing host actin , subverting host vesicular traffic , etc . [7–9] . It is well established that divergent effectors from distantly-related intracellular species can operate in similar processes [10]; e . g . , actin nucleators from species of Shigella , Listeria and Rickettsia [11 , 12] and phospholipases from species of Pseudomonas and Legionella [13 , 14] . Conversely , the ability for highly similar effectors from distantly-related species to function differently in host cells is a phenomenon that is poorly known , probably reflective of effector repertoires being highly specific to bacterial genera [15–17] . Species of Rickettsia ( Alphaproteobacteria: Rickettsiales ) are Gram-negative obligate intracellular parasites of a wide range of eukaryotic species [18] . Rickettsiae bind to host cells and induce phagocytosis [19 , 20] , with internalized bacteria released into the cytosol upon rapid escape from the phagocytic vacuole . Bacteria spread intercellularly upon death and lysis of host cells , though some species move intercellularly prior to host cell lysis via host actin polymerization [21–23] . Several surface proteins characterized for adhesion and/or entry of host cells ( Sca5 , Adr1 , Adr2 ) [24–28] and activation of cytoskeletal vinculin ( Sca4 ) [29] are conserved across sequenced Rickettsia genomes , as are several enzymes implicated in phagosomal lysis ( TlyC , PLD , Pat1 ) [30–33] . In contrast , other characterized adhesins ( Sca0 , Sca1 , Sca2 ) [34–38] , proteins involved in Arp2/3-dependent ( RickA ) [39 , 40] and -independent ( Sca2 ) [41 , 42] host actin polymerization , and another phospholipase ( Pat2 ) [43 , 44] are sporadically encoded across rickettsial lineages . This suggests that , despite superficially similar infection strategies , diverse Rickettsia species employ distinct molecular mechanisms for successful colonization of host cells [45] . One such protein that is differentially encoded across Rickettsia genomes is a highly similar counterpart to the RalF protein of Legionella spp . Collectively , these proteins contain a Sec7-domain , which in eukaryotes functions as a guanine nucleotide exchange factor ( GEF ) of ADP-ribosylation factors ( Arfs ) [46] . Remarkably , bacterial Sec7-domain containing proteins are unknown from other bacteria [47] . Legionella RalF ( RalFL ) is a secreted effector , with its proximal C-terminal sequence mediating secretion through the dot/icm type IV secretion system ( T4SS ) [48] . RalFL activates and recruits host Arf1 to the Legionella-containing vacuole ( LCV ) , which is a modification of the phagosome [49] . The structure of RalFL contains two distinct domains: an N-terminal Sec7 domain ( S7D ) and a C-terminal Sec7-capping domain ( SCD ) that regulates active site access to Arfs [50] . The S7D and SCD across RalFL and Rickettsia RalF ( RalFR ) share ~45% aa identity , though an extended variable region flanks the SCD of RalFR proteins at the C-terminus [51] . A comparative study of RalFL and RalFR determined similar GEF activities for both proteins , yet divergent subcellular localization patterns driven primarily by intrinsic characteristics of the SCD [52] . The RalFL SCD positions the protein at the endoplasmic reticulum for interception of host secretory vesicles , while the RalFR SCD targets the protein to the host plasma membrane . Furthermore , a proline-rich region within the extended variable region of RalFR interacts with components of the host actin cytoskeleton . Subsequently , membrane sensor regions were identified within the SCDs of RalFL and RalFR , with differential enrichments in aromatic and positively charged residues determining divergent lipid substrates that regulate Arf-GEF activities [53] . Collectively , these studies suggest that these distinguishing features ( divergent SCD sensor regions , RalFR-specific cytoskeletal-binding domain ) mediate the spatial regulation of RalF activity in two diverse intracellular species with very different lifestyles . Despite tremendous insight on the possible function of RalFR during rickettsial host cell infection , important questions are left unanswered . As previous studies were performed in vitro [52 , 53] , it still remains unknown if those Rickettsia species that carry ralF genes actually express RalFR during infection , and if so , at what time point . Furthermore , as GEFs confer the spatial regulation of different Arf classes at discrete cellular locales [54–57] , the Arf ( s ) specificity of RalFR needs to be determined in light of the different subcellular localization of the protein compared to Legionella spp . Our work presented here addresses these unknowns by demonstrating RalF expression by R . typhi early during host cell invasion . Across several Rickettsia species , we identified the domain requirements for positioning RalF at host membranes , and for R . typhi , determined that RalF co-localization with Arf6 and PI ( 4 , 5 ) P2 at entry foci was critical for invasion . Altogether , our work identifies Arf-GEF utilization as a lineage-specific invasion mechanism , illuminating the variable strategies that drive Rickettsia infection of host cells .
As predicted Arf-GEFs , we anticipated RalFR proteins to be secreted extracellularly into the host cell . Prior to invasion , L . pneumophila utilizes its dot/icm I-T4SS to translocate RalFL into host cells [48] . Like RalFL , R . typhi RalF ( RalFRt ) lacks a predicted N-terminal Sec secretion signal [58] , trans-membrane spanning regions [59] and a β-barrel structure [60] , suggesting its secretion via a Sec-independent pathway , possibly the Rickettsiales vir homolog ( rvh ) T4SS [61] . Accordingly , in order to determine if RalFRt interacts with the rvh T4SS , we performed a bacterial two-hybrid assay with full length RalFRt ( RalFRtFL ) and RvhD4 , the rvh T4SS coupling protein . T4SS coupling proteins ( VirD4 family ) are ATPases that function as “gatekeepers” to regulate substrate entry into the T4SS channel [62 , 63] . Co-transformation of bait ( encoding RvhD4 ) and prey ( encoding RalFRtFL ) plasmids in BacterioMatch II reporter electrocompetent cells resulted in bacterial growth on selective media ( Fig 1A ) , indicating RalFRtFL and RvhD4 interact , and thus implicating RalFRt as an rvh T4SS effector . Secretion of RalFL is dependent on hydrophobic residues within its C-terminal tail [48] , while many other T4SS protein substrates have enrichments of positively charged residues at their C-termini that are important for secretion [64–66] . Accordingly , we evaluated RalFRt for the presence of a T4SS signal sequence ( T4S ) within its C-terminus . A T4S RalFRt truncation ( RalFRtΔT4S ) was generated and tested for its ability to bind RvhD4 via the bacterial two-hybrid assay ( Fig 1A ) . The percent growth of colony forming units ( CFUs ) of reporter cells harboring recombinant plasmids on dual selective screening medium was calculated relative to percent growth of CFUs obtained on non-selective His dropout medium by drop plate method for counting . An approximately 77% decrease in CFUs on dual selective media was observed with RalFRtΔT4S compared to RalFRtFL , indicating that the RalF C-terminus is important for interacting with RvhD4 ( Fig 1B ) . The ATPase activity of T4SS coupling proteins is essential for substrate translocation [67] . To confirm functionality of RvhD4 , recombinant RvhD4 was assayed for ATPase activity . RvhD4 was found to release inorganic phosphate ( Pi ) from ATP in a concentration dependent manner compared to a rickettsial protein that lacks predicted ATPase activity ( RT0600 ) ( Fig 1C and 1D ) . This indicates Rickettsia RvhD4 is a functional ATPase that likely regulates protein secretion through the rvh T4SS . The interaction of RalFRt with machinery of the rvh T4SS implies extracellular secretion . Our prior report that characterized the R . typhi surface proteome demonstrated that RalFRt is expressed and surface exposed [68] . To further confirm RalFRt secretion , purified R . typhi was treated with proteinase K , on the premise that surface exposed protein would be degraded with proteinase K treatment while subsurface proteins would be protected . Protease treatment caused a dose-dependent degradation of RalFRt with respect to the R . typhi cytoplasmic control protein , elongation factor Ts ( EF-Ts , Fig 1E ) . To determine when RalFRt is expressed during R . typhi infection , a polyclonal antibody against RalFRt was generated , qualified ( S1 Fig ) and used for immunofluorescence assays ( Fig 1F ) . During early infection of host cells ( 10 min ) , RalFRt expression is high and diminishes as internalization progresses ( 30 min ) . Given RalFRt expression during early infection , we assessed its role during R . typhi invasion of host cells . When R . typhi was pre-treated with the anti-RalFRt polyclonal antibody , the average number of R . typhi per host cell decreased by 52% from an average of 10 to 4 . 8 bacteria per host cell ( Fig 1G ) , indicating a role for RalF during host cell invasion . To rule out possible steric hindrance induced by the Fc portion of the anti-RalFRt antibody inhibiting rickettsial-host cell interactions that promote entry , R . typhi was pre-absorbed with anti-RalFRt Fab fragments . The average number of R . typhi per host cell was significantly decreased by 45% from 10 to 5 . 5 bacteria per host cell ( Fig 1G ) further confirming the involvement of RalF in host cell invasion . Utilizing over 60 Rickettsia genome sequences , phylogenomics analyses were carried out to provide further insight on the role of RalF in rickettsial biology and pathogenesis . While a key factor in R . typhi infection of host cells , RalF-mediated invasion is not a strategy employed by all Rickettsia species , as evident by ralF pseudogenization in all species of Spotted Fever Group ( SFG ) rickettsiae , as well as two other species ( R . canadensis and R . helvetica ) [45] . Still , the remaining species , including R . bellii and all species within the Typhus Group ( TG ) and Transitional Group ( TRG ) rickettsiae , contain genes encoding RalFR proteins that are highly conserved within the S7D and SCD as compared to RalFL ( Fig 2 ) . Specifically , and in agreement with previous studies [52 , 53] , all RalFL and RalFR proteins contain a highly conserved Sec7 active site within the S7D ( S2A and S2B Fig ) , with RalFR proteins having an enrichment of positively charged residues in the lipid sensor region of the SCD relative to RalFL proteins ( S3C Fig ) . Thus , based on these characteristics , all RalFR proteins are predicted to spatially regulate their Arf-GEF activities at the host plasma membrane , where concentrated negatively charged phospholipids attract the RalFR SCD [53] . Relative to RalFL , the major distinguishing factor of RalFR proteins is the presence of a variable sequence with Pro-rich region ( VPR ) within the C-terminal domain ( Fig 2 ) . Pro-rich regions are a common characteristic of proteins that target the actin cytoskeleton [70] , and are typically present in Arf-GEFs recruited to cytoskeletal/plasma membrane junctions [71 , 72] . Across RalFR proteins , the VPR is flanked by the SCD and T4S and is extraordinarily variable in sequence length and number of Pro residues across RalFR proteins ( Fig 2B ) . Remarkably , many SFG rickettsiae species , e . g . R . montanensis , contain putative ORFs encoding complete VPRs . Alignment of these ORFs with VPRs from full-length RalFR proteins illustrates that a gene encoding RalFR was present in the Rickettsia ancestor , with pseudogenization purging the complete Arf-GEF from most Rickettsia genomes ( S4A Fig ) . This conclusion is supported by genome synteny analysis across ralFR loci , which indicates a conserved position for ralF flanking the maeB gene in all sequenced Rickettsia genomes ( S5A Fig ) . Thus , RalFL and RalFR proteins diversified early upon their establishment in ancestral Legionella and Rickettsia genomes , with the retention of VPRs within full-length RalFR proteins implying an important function . In light of the variability across the VPR of RalFR proteins , we determined the C-terminal domain ( CTD ) requirements for subcellular localization across RalFR proteins from several species ( R . typhi , R . felis , R . montanensis and R . bellii ) ( Fig 3 ) . The SCD- and VPR-mediated targeting to the host plasma membrane and actin cytoskeleton , respectively , for RalF of R . prowazekii ( RalFRp ) was used as a reference [52 , 53] . R . typhi and R . felis full-length RalF ( RalFFL ) proteins primarily had diffuse staining within the cytoplasm with some plasma membrane localization . However , RalFCTD ( SCD-VPR-T4S ) localized strongly to the plasma membrane and disrupted actin stress fibers . Additionally , R . typhi and R . felis RalFCTD induced membrane ruffling and microvilli-like protrusions suggesting that the CTD plays a role in cytoskeletal rearrangements , similar to the known Arf6-GEF , EFA6 [71 , 72] . Furthermore , RalFVPR ( VPR-T4S ) , as well as the full-length VPR-containing ORF of R . montanensis , did not uniformly localize to the host plasma membrane , but instead were found strongly associated with intact actin stress fibers . Collectively , these results indicate that R . typhi and R . felis RalF proteins are similar to RalFRp , with both the SCD and VPR required to spatially regulate Arf-GEF activities at plasma membrane/actin cytoskeletal junctions . Remarkably , RalFFL and RalFCTD of R . bellii did not target the plasma membrane , yet instead showed perinuclear localization reminiscent of ectopically expressed RalFL . As R . bellii RalFVPR associated with intact actin stress fibers , these data collectively indicate that the SCD alone is sufficient to localize RalFRb to the host cytoplasm . Visualization of the SCD sequence alignment across all RalFL and RalFR proteins revealed that RalFRb lacks three separate insertions within the SCD that are conserved in all other RalFR proteins ( S3B Fig ) . Thus , from a structural perspective , the SCD of RalFRb is more similar to RalFL proteins than RalFR proteins , which could explain why the SCD of R . bellii localizes to the perinuclear region of the cytoplasm . This is consistent with R . bellii sharing more genomic attributes with Legionella spp . [73] , as well as being able to grow in various amoeba species unlike most other Rickettsia spp . ( see Discussion ) . RalF membrane localization was further confirmed using two independent approaches . First , membrane fractionation of HeLa cells transfected with RalF-expressing plasmids revealed that all RalFCTD proteins were predominately enriched in the membrane fraction , with RalFFL and RalFVPR proteins having less membrane enrichment ( Fig 3 and S6 Fig ) . Second , RalF transfected cells were stained with Alexa Fluor 594 wheat germ agglutinin to detect plasma membrane or probed with anti-PDI ( endoplasmic reticulum ) or anti-GM130 ( Golgi apparatus ) antibodies ( Fig 4 and S7 Fig ) , with the Pearson’s correlation coefficients calculated to measure co-localization with the respective membrane markers ( S8 Fig ) . RalFCTD of R . typhi , R . felis , R . montanensis indicate localization to the plasma membrane , while R . bellii RalFCTD localized to the endoplasmic reticulum membrane recapitulating results observed with labeling host cell actin ( Fig 3 ) . Collectively , these data demonstrate the affinities of RalFR proteins for host membranes , identifying the SCD as the major determinant for membrane localization , combined with the targeting of actin cytoskeleton by the VPR ( Table 1 ) . Finally , for R . typhi , we monitored the subcellular localization of its RalFCTD construct lacking the T4S ( RalFRtCTDΔT4S ) . We observed indistinguishable localization patterns between RalFRtCTD and RalFRtCTDΔT4S ( S4C Fig ) , suggesting that the T4S has no effect on localization or stress fiber disruption . In conjunction with results above ( Fig 1A and 1B ) , these data bolster the role of the T4S of RalFR proteins as an rvh T4SS translocation signal . Previous studies showed the SCD of RalFRp has affinities for negatively-charged phospholipids; i . e . , phosphatidylinositol 4 , 5-bisphosphate ( PI ( 4 , 5 ) P2 ) and phosphatidylinositol 3 , 4 , 5-trisphosphate ( PI ( 3 , 4 , 5 ) P3 ) [52 , 53] . Given the enrichment of PI ( 4 , 5 ) P2 at host membranes during early stages of phagocytosis [74] , we evaluated the role of PI ( 4 , 5 ) P2 in RalFR localization . As a baseline , we utilized the standard phospholipase C ( PLC ) -mediated catalyzation of PI ( 4 , 5 ) P2 within the IP3/DAG pathway of host cells [75] . Specifically , in the presence of ionomycin and Ca2+ , PI ( 4 , 5 ) P2 is hydrolyzed to inositol 1 , 4 , 5-trisphosphate and diacylglycerol via PLC isozymes that regularly deplete the plasma membrane of PI ( 4 , 5 ) P2 following its role as a substrate in many signaling pathways [76] . To test PI ( 4 , 5 ) P2-dependent localization of RalFRt to the plasma membrane , HeLa cells ectopically expressing RalFRtCTD were treated with ionomycin and Ca2+ , with the distribution pattern of RalFRtCTD monitored by immunofluorescence . With ionomycin and Ca2+ treatment , RalFRtCTD becomes cytosolic compared to plasma membrane localization in the presence of ionomycin alone ( Fig 5A ) . Upon treatment with EGTA , which chelates Ca2+ , PI ( 4 , 5 ) P2 accumulates and RalFRtCTD returns to the plasma membrane . HeLa cells expressing GFP-C1-PLCδ-PH , a biosensor of PI ( 4 , 5 ) P2 , were used as a positive control to demonstrate the hydrolysis of PI ( 4 , 5 ) P2 in the presence of ionomycin and Ca2+ . Additionally , RalFRbCTD subcellular localization was shown to be unaffected by PI ( 4 , 5 ) P2 hydrolysis , consistent with its perinuclear distribution in host cells . Collectively , these data indicate that PI ( 4 , 5 ) P2 enrichment at the host plasma membrane is a requirement for efficient recruitment of RalFRt , and probably also RalFRf , given its similar subcellular localization pattern . Phosphatidylinositols enriched at the host plasma membrane often play a critical role in bacterial internalization [74] . Given that RalFRt is expressed early ( Fig 1F ) and required ( Fig 1G ) for host invasion , and its localization to the host plasma membrane requires PI ( 4 , 5 ) P2 enrichment ( Fig 5A ) , we sought to determine if PI ( 4 , 5 ) P2 is recruited by RalFRt during R . typhi infection . PI ( 4 , 5 ) P2 localization during R . typhi invasion was analyzed using immunofluorescence microscopy with GFP-C1-PLCδ-PH as a biosensor of PI ( 4 , 5 ) P2 localization . During early infection ( i . e . 5 and 10 min post infection ) , PI ( 4 , 5 ) P2 was highly localized to pseudopodia at the R . typhi entry foci ( Fig 5B ) . As internalization progressed , R . typhi was surrounded by a vacuole with diminished PI ( 4 , 5 ) P2 localization . Once R . typhi detached from the membrane , it was no longer associated with PI ( 4 , 5 ) P2 . Furthermore , detection of RalFRt during the infection process revealed co-localization of PI ( 4 , 5 ) P2 and RalFRt during early infection ( Fig 5C ) . In agreement with RalFRt early expression , which diminished at later stages of infection ( Fig 1F ) , PI ( 4 , 5 ) P2 recruitment decreased as infection progressed . Finally , we evaluated whether or not the recruitment of PI ( 4 , 5 ) P2 to R . typhi entry foci is critical for R . typhi infection . Pretreatment of HeLa cells with ionomycin and Ca2+ to deplete PI ( 4 , 5 ) P2 from the membrane prior to infection resulted in a significant decrease in R . typhi infection ( Fig 5D ) , strengthening the evidence that PI ( 4 , 5 ) P2 is a target molecule involved in RalFRt-associated host cell invasion . The Arf-GEF activity of RalFL is activated upon membrane binding , with Arf1 the preferred substrate [49 , 52] . Arf1 is predominantly localized to the Golgi apparatus and plays a role in intra-Golgi transport [77] . Given the association of RalFRt with the plasma membrane , we hypothesized that it might instead recruit Arf6 , which is predominantly localized to the plasma membrane where it is involved in endocytosis , endosomal recycling and exocytosis of secretory granules [78–81] . Using immunofluorescence , RalFRtFL was found to recruit Arf6 but neither Arf5 ( Fig 6A ) nor Arf1 ( S9 Fig ) to the plasma membrane . Arf5 localizes primarily to the endoplasmic reticulum/Golgi intermediate compartment and the cis-Golgi , where it regulates endoplasmic reticulum to Golgi transport; therefore , Arf5 was used as a negative control [82] . Interestingly , RalFRbFL was similarly found to co-localize with Arf6 but not Arf5 or Arf1 in the perinuclear space . To further confirm a RalFRtFL and Arf6 interaction , a protein pull-down assay was performed . Using rHis-RalFRtFL as bait and mRFP-Arf5 or mRFP-Arf6 as the prey , we confirmed that RalFRtFL interacted with Arf6 and not Arf5 ( Fig 6B ) . Activation of Arf6 at the plasma membrane drives the recruitment of phospholipase D and phosphatidylinositol 4-phosphate 5-kinase ( PIP5K ) , which ultimately results in actin remodeling [83 , 84] . To determine if Arf6 is recruited during R . typhi entry , we used immunofluorescence microscopy to monitor Arf6 localization . As early as 10 min post infection , Arf6 was recruited to the plasma membrane at R . typhi entry foci , while Arf5 remained cytoplasmic ( Fig 6C ) . Given that RalFRt localizes with Arf6 at plasma membrane ( Fig 6A ) and recruits Arf6 at the R . typhi entry foci ( Fig 6C ) , we predicted that knockdown of Arf6 would decrease R . typhi infection . Indeed , siRNA-mediated Arf6 knockdown significantly decreased the number of R . typhi per cell , while Arf5 knockdown had no significant effect on R . typhi infection ( Fig 6D and 6E ) . These results indicate that RalFRt recruits Arf6 at the plasma membrane during early infection , with spatially regulated Arf-GEF activity required for host cell invasion .
Bacteria invading eukaryotic cells employ diverse strategies to subvert the host cellular actin cytoskeleton , allowing for internalization into normally non-phagocytic host cells [85] . For some bacterial species , surface proteins bind host cell receptors and trigger an “outside-in” signaling cascade , which induces cytoskeletal rearrangements and recruits the endocytic machinery to entry foci [86] . Such receptor-mediated induction of bacterial uptake is a strategy employed by Listeria monocytogenes , which utilizes two adhesins ( InlA and InlB ) to bind host proteins ( E-cadherin , receptor gC1qR , proteoglycans ) and activate the tyrosine kinase receptor Met [87] . Invasive species of Yersinia also employ two adhesins ( invasin and YadA ) to bind a subset of β1-integrin host receptors , facilitating invasion that is dependent on signaling from the Rho GTPase Rac1 and activation of the actin nucleating complex Arp2/3 [88 , 89] . Alternatively , other bacterial species translocate effectors into host cells to initiate actin remodeling and facilitate bacterial uptake . For example , Salmonella typhimurium utilizes its type III secretion system to inject host cells with the effector SopE , which stimulates GDP/GTP nucleotide exchange on Rho GTPases Rac1 and Cdc42 , resulting in membrane ruffling and actin cytoskeleton rearrangement [90] . While a receptor-mediated process has been previously characterized for R . conorii invasion of mammalian cells ( discussed below ) , to date no secreted effectors for any Rickettsia species have been characterized for their role in inducing uptake into host cells . While most species of the order Rickettsiales encode the rvh T4SS [91] , effectors have only been identified for some species of the family Anaplasmataceae . For Anaplasma phagocytophilum , rvh effectors are translocated to the mitochondria ( Ats-1 ) and nucleus ( AnkA ) to inhibit etoposide-induced apoptosis and down-regulate host defense genes , respectively [92–94] . AM185 , AM470 , AM705 ( AnkA ) , and AM1141 have been identified as putative rvh T4SS effectors of Anaplasma marginale using a heterologous T4SS ( L . pneumophila dot/icm ) , yet none have been characterized for their roles in invasion [95] . Ehrlichia chaffeensis utilizes the rvh T4SS to translocate the effector ECH0825 into host mitochondria , resulting in inhibition of Bax-induced apoptosis [96] . Herein , we identified RalF as the first rvh T4SS effector for species in the family Rickettsiaceae . We provide evidence that R . typhi RalF interacts with RvhD4 , the rvh T4SS coupling protein that presumably recognizes effectors and regulates their translocation similar to VirD4 proteins of other P-type T4SSs . Treatment of purified R . typhi with proteinase K degraded surface exposed RalF , providing further evidence that RalF is secreted . Furthermore , using immunofluorescence we show that RalFRt is expressed early during host cell invasion . Because RalF is expressed early during invasion , we hypothesized that RalF is critical for invasion , which was confirmed using antibody pretreatment assays . Prior studies comparing the subcellular localization of ectopic RalFL and RalFRp determined that , despite strong conservation in the S7D and SCD across these proteins , cryptic signatures within the SCD targeted these proteins to different host membranes [52 , 53] . RalFRp localization to the plasma membrane , mediated by elevated positively charged residues within the lipid sensor of the SCD , was anticipated to be true for other RalFR proteins , given the strong sequence conservation within the SCD across RalFR homologs . Furthermore , despite extensive variation within the VPR across RalFR proteins , the presence of proline-rich regions in all proteins suggested that this region likely encodes a conserved motif that facilitates interaction with the host cytoskeleton , as was shown for RalFRp [52 , 53] . Indeed , our co-localization assays confirmed that , for RalF of R . typhi and R . felis , the SCD mediates interaction with the host plasma membrane , with the VPR facilitating interaction with the host cytoskeleton . In contrast , the perinuclear localization of RalF of R . bellii , reminiscent of the localization of ectopic expressed RalFL proteins at the host secretory network , was unexpected . The VPR of RalFRb is similar in length to VPRs of RalF proteins from R . felis , R . akari and R . australis , with all of these proteins predicted to encode a coiled-coil motif typical of some eukaryotic Arf-GEFs; e . g . , EFA6 [71] . While containing an extraordinary number of Pro residues , the VPR of RalFRb nonetheless targets the host cytoskeleton , suggesting that other characteristics of the protein mediate its localization to the cytoplasm . Indeed , in silico analyses revealed three conserved insertions within the SCD of RalFR proteins that are absent from RalFRb . Furthermore , relative to all RalF proteins , the S7D of RalFRb contains an odd insertion as well as a slightly less hydrophobic active site ( S2 Fig ) , the significance of which is unknown . It is tempting to speculate that the perinuclear localization of RalFRb reflects a unique cytosolic lifestyle of R . bellii , an ancestral lineage with a different genomic repertoire relative to other Rickettsia species [51] and the unique ability to grow and survive in several species of amoeba [73] . As R . bellii has been observed invading nuclei of mammalian cells in vitro [73] , RalF may play a role in this process , though other Rickettsia species that lack RalF also are known to invade host cell nuclei [97] . Notwithstanding , the SCD-driven perinuclear localization of RalFRb might thus be considered the retention of an ancestral role for RalFR proteins in targeting host vesicular trafficking , similar to RalFL proteins . Collectively , our detailed dissection of the domain requirements for subcellular localization strongly implies differential utilization of Arf-GEF activities for those species of Rickettsia that encode RalF . RalFRb aside , the subcellular localization of other RalFR proteins to the plasma membrane suggested Arf6 might be their preferred host target , given the predominant localization of Arf6 to the plasma membrane [98] and a previous study showing that RalFRp can catalyze nucleotide exchange on Arf6 [52] . Arf6 activation by some intracellular pathogens ( e . g . , species of Salmonella , Yersinia and Chlamydia ) is known to induce actin remodeling and mediate bacterial invasion via unique pathways . Salmonella enterica activates Arf6 to recruit the Arf-GEF ARNO , which in turn activates Arf1 to enable WASP family veroprolin homolog ( WAVE ) regulatory complex-dependent actin assembly [99] . Arf6 activation by species of Yersinia and Chlamydia leads to activated PIP5K , which converts PI ( 4 ) P to PI ( 4 , 5 ) P2 at the plasma membrane [100 , 101] . As PI ( 4 , 5 ) P2 enrichment at the host plasma membrane modulates many actin-binding proteins , including α-actinin , talin , vinculin , gelsolin , and the WASP-Arp2/3 complex [102–107] , effector-driven accumulation of this phosphatidylinositide can be considered a strategy for induction of phagocytosis . Given that R . typhi secretes RalF early during host cell invasion , we hypothesized that this Arf-GEF recruits Arf6 to entry foci , precipitating the enrichment of PI ( 4 , 5 ) P2 at the plasma membrane to facilitate bacterial invasion . Indeed , our in vitro and in vivo results confirm that Arf6 co-localizes with RalF and R . typhi at entry foci . Additionally , during R . typhi infection , PI ( 4 , 5 ) P2 noticeably accumulated in the membranes of pseudopodia , with a decreased concentration at the base of the phagocytic cup as internalization progressed . Furthermore , the role of PI ( 4 , 5 ) P2 in bacterial internalization was bolstered by the significant reduction in R . typhi invasion upon PI ( 4 , 5 ) P2 hydrolysis . Thus , an increase in PI ( 4 , 5 ) P2 induced by rickettsial RalF activation of Arf6 is predicted to initiate actin remodeling and ultimately facilitate bacterial invasion ( Fig 7 ) . Remarkably , this function for RalFR is markedly different than RalFL , which is utilized by L . pneumophila to recruit Arf1 to the LCV [49] . Unlike species of Legionella , Rickettsia species do not reside in vacuoles but rather lyse the phagosome and replicate within the host cytoplasm . Thus , despite carrying a similar Arf-GEF that is unknown from any other bacteria , different intracellular lifestyles across species of Rickettsia and Legionella have driven divergent roles for RalF during bacterial infection . Currently , the predominant knowledge of rickettsia entry and invasion of host cells is based on studies of species from SFG rickettsiae , whereby the surface antigen Sca5 binds host receptor Ku70 to activate a signaling cascade leading to Arp2/3 activation and ultimately actin polymerization , membrane rearrangement and bacterial invasion [26 , 108 , 109] . The conservation of Sca5 across all Rickettsia species implies that this receptor-mediated mechanism for entry is likely conserved ( Fig 8 ) [45] . However , depletion of host Rho family GTPases and nucleation-promoting factors that activate Arp2/3 has only a modest effect on rickettsial invasion , suggesting there are other bacterial or host proteins that activate Arp2/3 during infection [108] . Most species of SFG rickettsiae encode an Arp2/3 activating protein , RickA , which could potentially play this role , although its secretion during infection has yet to be demonstrated . Interestingly , genes encoding RickA are absent from species of TG rickettsiae ( R . typhi and R . prowazekii ) ; thus , if bacterial Arp2/3 activators are a requirement for invasion , factors other than RickA must be utilized for species of TG rickettsiae . Accordingly , we propose that RalF plays a role in host actin rearrangement and bacterial invasion . Aside from the Sca5-Ku70 interaction and subsequent downstream signaling cascade , other rickettsial adhesins have been characterized for facilitating host cell invasion ( Fig 8 ) . However , the lack of conservation of these adhesins ( e . g . , Sca0 and Sca2 ) across diverse Rickettsia species implies the existence of multiple mechanisms for rickettsial host cell invasion [45] . It is also probable that each species likely encodes redundancy for factors that facilitate entry , and that some factors may selectively operate for invasion of specific cells ( arthropod versus mammalian ) throughout the complex rickettsial lifecycle . Thus , it is probable that lineage-specific factors are employed by different species of Rickettsia to successfully invade and colonize diverse eukaryotic cells . Our identification of lineage-specific Arf-GEF utilization across diverse rickettsial species exemplifies this , and illuminates previously unappreciated mechanisms for host cell invasion and infection .
Vero76 ( African green monkey kidney , ATCC: CRL-1587 ) , HEK293T and HeLa ( ATCC: CCL-2 ) cells were maintained in minimal Dulbecco’s Modified Eagle’s Medium ( DMEM with 4 . 5 gram/liter glucose and 480 L-glutamine; Mediatech , Inc . ) supplemented with 10% heat inactivated fetal bovine serum ( FBS ) at 37°C with 5% CO2 . R . typhi strain Wilmington ( ATCC: VR-144 ) was propagated in Vero76 cells grown in DMEM supplemented with 5% heat inactivated fetal bovine serum at 34°C with 5% CO2 . Rickettsiae were partially purified as previously described [111] . Infections with R . typhi were performed 18–24 hrs post transfection with a multiplicity of infection ( MOI ) of ~100:1 . For antibody pretreatment experiments , partially purified R . typhi was incubated with 20 μg Melon Gel IgG ( Thermo Scientific ) purified rabbit pre-immune serum or anti-RalFRt polyclonal antibody or 20 μg purified rabbit pre-immune serum or anti-RalFRt Fab fragments for 30 min prior to infection . Fab fragments were purified using the Fab Purification Kit ( Thermo Scientific ) according to manufacture’s protocol . The expression and purification of recombinant proteins were performed as previously described [111] . Codon optimized ( Life Technologies ) R . typhi rvhD4 ( RT0284 ) was cloned into pTrcHis2-TOPO vector under the control of the trc promoter ( Life Technologies ) . Full-length R . typhi ralF was cloned into pEXP5-NT/TOPO ( Life Technologies ) and transformed into E . coli strain bl21-codonplus ( de3 ) -ril ( Stratagene ) . Primers used for cloning can be found in S1 Table . The expression of recombinant proteins was induced with 1 mM IPTG and recombinant proteins were purified by affinity chromatography under native conditions using nickel-nitrilotriacetic acid resin ( Ni-NTA ) superflow columns ( Qiagen ) according to manufacturer’s instructions . Polyclonal antibody was generated in rabbit using recombinant RalFRtFL ( Alpha Diagnostic Intl . Inc ) . R . typhi gene sequences ( RT0362 , GenBank accession no . YP_067323 ) encoding full-length RalF ( RalFRtFL ) and the rvh T4SS signal truncation ( RalFRtΔT4S ) were cloned into the pTRG “prey” plasmid ( BacterioMatch II two-hybrid system; Stratagene ) . A codon optimized ( Life Technologies ) R . typhi rvhD4 gene ( RT0284 , YP_067246 ) was cloned into the pBT “bait” plasmid . Primers used for cloning can be found in S1 Table . The bait ( pBT-RvhD4 ) and prey ( pTRG-RalFRtFL or pTRG-RalFRtΔT4S ) plasmids ( 100ng each ) were co-transformed into BacterioMatch II reporter electrocompetent cells according to the manufacturer’s instruction ( GenePulser Xcell , BioRad ) . The percent growth of CFUs of reporter cells harboring recombinant plasmids on dual selective screening medium were calculated relative to CFUs obtained on non-selective His dropout medium by a drop plate method for counting CFUs [112] . RvhD4 ATPase activity was monitored using a Quantichrom ATPase/GTPase assay kit ( Bioassay Systems ) , according to the manufacturer’s instructions and as described previously [113] . Briefly , 200–12 . 5 ng/well of purified recombinant RvhD4 protein was incubated in the presence of 1 mM ATP for 30 min at 37°C . Generated free phosphate was quantified by measuring absorbance at OD 620 nm . All of the samples were measured in triplicate wells , and data are given as averages ± S . D . of three independent experiments . R . typhi was purified from heavily infected Vero76 cells . Briefly , infected cells were scrapped into media and spun at 12 , 000 x g for 10 min at 4°C . Cells were resuspended in ice cold PBS , pH 7 . 2 containing MgCl2 ( PBS-Mg ) and sonicated for 10 sec on ice using output 6 of a Sonic Dismembrator ( Fisher Scientific ) . The lysate was filtered through a 5 . 0 μm filter ( Millipore ) . The filtrate containing R . typhi was layered onto a 20% sucrose cushion at a 1:1 ratio and centrifuged at 16 , 000 x g for 15 min at 4°C to pellet R . typhi . R . typhi was resuspended in PBS-Mg and again purified with a 20% sucrose cushion . Purified R . typhi was treated with 400 μg/mL or 800 μg/mL Proteinase K ( Sigma-Aldrich ) for 1 hr at room temperature in PBS-Mg buffer as previously described [114] . Following incubation , Halt Protease and Phosphatase Inhibitor Cocktail ( Thermo Scientific ) was added to the reaction , and bacteria centrifuged at 16 , 000 x g for 10 min at 4°C . R . typhi were washed with PBS-Mg and resuspended in PBS-Mg and NuPAGE LDS sample buffer and reducing reagent ( Life Technologies ) . Lysates were separated on a NuPAGE Bis-Tris SDS-gel ( Life Technologies ) and immunoblotted with rabbit anti-RalF or anti-EF-Ts as the R . typhi cytoplasmic marker [43 , 115] . Densitometry was performed using ImageJ ( NIH ) and RalF intensity was normalized to EF-Ts . Using RalFRt as a query , BLASTP searches were performed against the NCBI ‘Rickettsia’ database ( taxid:780 ) . Full length RalFR homologs were aligned with MUSCLE v3 . 6 [116] using default parameters . Initial domain characterization of RalFR proteins followed that previously described for R . prowazekii [52] . Using Phyre v . 2 . 0 [69] , RalFRt was modeled to the crystal structures of Legionella pneumophila RalF ( PDB 1XSZ , 4C7P ) [50 , 53] to confirm the boundaries of the Sec7 domain ( S7D ) and Sec7-capping domain ( SCD ) . The S7D and SCD of Rickettsia and Legionella RalF homologs were aligned with MUSCLE , superimposing the secondary structure of RalFL over the alignment . The divergent C-terminal domain ( CTD ) of RalFR proteins was further described based on distinct characteristics , i . e . a sequence of variable length that includes a Pro-rich tract , as well as a putative secretion signal sequence within the terminal 40 aa . Additional Rickettsia proteins that lack the S7D and SCD , mostly from SFG rickettsiae , were utilized to characterize this region . All full length and partial RalFR homologs were used to assess the synteny of the ralF locus across select Rickettsia genomes . For these genomes , gene neighborhood models were constructed using the Kyoto Encyclopedia of Genes and Genomes ( KEGG ) database [117] , with manual adjustment to gene annotations . Additional bioinformatics/phylogenomics methodologies are described in S2–S5 Figs . Genomic DNA from R . bellii str . OSU 85–1299 , R . felis str . Pedreira , R . montanensis str . M5/6 , and R . typhi str . Wilmington was purified using DNeasy Blood and Tissue Kit ( Qiagen ) . RalF constructs were amplified as EcoRI/BamHI fragments using primers in S1 Table , with the exception of RalFRbFL , which was cloned using Clontech InFusion technology . Amplicons were cloned into the pGEMT-Easy vector ( Promega ) and confirmed by sequencing ( The Biopolymer/Genomics Core Facility , University of Maryland School of Medicine ) . Plasmids were digested with EcoRI and BamHI , with ralF fragments subcloned into the pEYFP-C1 vector ( Clontech ) . All plasmids were transformed into Mix & Go Competent Cells—Strain Zymo 5α ( Zymo Research ) . Plasmids pCDNA3-mRFP-Arf1 , pCDNA3-mRFP-Arf5 and pCDNA3-mRFP-Arf6 were generous gifts from Prof . Vassilis Koronakis ( University of Cambridge , UK ) . GFP-C1-PLCδ-PH ( Addgene plasmid # 21179 ) was kindly gifted by Tobias Meyer [118] . All plasmids were purified using PerfectPrep EndoFree Plasmid Maxi Kit ( 5 Prime ) . For transfections , HeLa cells seeded in 8-well chamber slides were transfected with 200ng plasmid per well using Xfect ( Clontech ) and HEK293T cells in T-75 flasks were transfected with 10μg plasmid using Lipofectamine 2000 ( Life Technologies ) according to manufactures’ protocols . Twenty-four hours post transfection or at indicated times post infection , cells were fixed with 4% PFA for 10 min at room temperature . Cells were washed three times with PBS and permeabilized in Blocking Buffer ( 0 . 2% saponin , 5% FBS in PBS ) for 30 min . Primary antibodies mouse anti-PDI ( clone RL90 , BD Transduction Laboratories , diluted 1:200 ) , mouse anti-GM130 ( clone 610822 , BD Transduction Laboratories , diluted 1:200 ) , rat anti–R . typhi serum ( 1:500 ) , rabbit anti-RalFRt ( 1:100 ) , and rabbit anti-GFP ( Life Technologies , diluted 1:1000 ) were diluted in blocking buffer and incubated with cells for 1 h . Cells were then washed with PBS and incubated with Alexa Fluor 594 or Alexa Fluor 488 secondary antibodies ( Life Technologies ) diluted 1:2000 in Blocking Buffer for 1 h or 30 min . Finally , cells were washed three times with PBS and mounted using ProLong Gold Anti-Fade mounting media with DAPI ( Life Technologies ) . Actin was stained with Alexa Fluor 594 phalloidin ( Life Technologies ) and the plasma membrane stained with Alexa Fluor 594 wheat germ agglutinin ( WGA , Life Technologies ) according to manufacturer’s protocol . For confocal microscopy , cells were viewed under a Zeiss LSM 510 Meta Confocal Microscope ( University of Maryland Baltimore Confocal Core Facility ) . For conventional fluorescence microscopy a Nikon Eclipse E600 fluorescent microscope with a Q Imaging Retiga 2000R camera was used to capture images with QCapture Pro software . Images were processed using ImageJ software ( NIH ) . Co-localization analysis was performed using the CoLoc2 plugin in the ImageJ software program [119] . The Pearson’s correlation coefficient was calculated for 5–10 cells per condition from two independent experiments to measure the strength of association between each RalF protein and the cell organelle ( i . e . , plasma membrane , endoplasmic reticulum , or Golgi apparatus ) . Two-sided Student’s t-tests were performed to determine statistical significance for co-localization coefficients compared to control eYFP . Cellular fractionation was completed as previously described [52] . Briefly , at 24 hrs post transfection , HEK293T cells were washed once with PBS and collected in 500 μL homogenization buffer ( 150 mM KCl , 20 mM HEPES pH 7 . 4 , 2 mM EDTA ) containing protease inhibitors and passed 30 times through a 27G-needle . The lysate was centrifuged at 2000 x g for 5 min at 4°C to remove the nuclear fraction . The supernatant was subsequently centrifuged at 100 , 000 x g for 1 h at 4°C to pellet the membrane fraction . The supernatant was removed ( cytoplasmic fraction ) and the pellet ( membrane fraction ) was resuspended in 80 μL of homogenization buffer . Twenty micrograms of cytoplasmic and membrane fractions were separated by SDS-PAGE and blotted with anti-GFP rabbit serum ( Life Technologies ) . Rabbit anti-calnexin [clone ab13505] and mouse anti-GAPDH [clone 6C5] antibodies ( Abcam ) were used as markers of the membrane and cytosol fractions , respectively . Transfected HeLa cells were washed with PBS and incubated in 100 μL of either phosphate buffered saline ( PBS ) or Krebs-Ringer solution ( 120 mM NaCl , 4 . 7 mM KCl , 1 . 1 mM CaCl2 , 0 . 7 mM MgSO4 , 10 mM glucose , 10 mM Na-HEPES , pH 7 . 4 ) . Ionomycin ( Sigma Aldrich ) was added to a final concentration of 5 μM and cells were incubated for 10 min . EGTA was added to a final concentration of 2 mM and cells were incubated for 10 min . Cells were then infected with R . typhi ( described above ) or fixed and stained as described above . RalFRt was cloned into the pTrcHisA vector ( Life Technologies , see S1 Table for primer sequences ) and transformed into Top10 E . coli cells ( Life Technologies ) . Protein expression was induced with 1 mM IPTG overnight at 30°C . E . coli were lysed using Pierce Lysis Buffer in the presence of HALT Protease Inhibitors ( Thermo Scientific ) and imidazole added to a final concentration of 10 mM . Lysates were sonicated three times for 20 sec each using setting 6 of a Sonic Dismembranator ( Fisher Scientific ) . mRFP-Arf5 and –Arf6 were expressed in HEK293T cells as described above . HEK293T cells were lysed using Pierce Lysis Buffer in the presence of HALT Protease Inhibitors ( Thermo Scientific ) and imidazole added to a final concentration of 10 mM . Pull-down assays were performed using the Pierce Pull-Down PolyHis Protein:Protein Interaction kit according to manufacture’s protocol . Briefly , HisPur Cobalt Resin was incubated with rHis-RalFRt E . coli lysate or buffer alone for 1 hr . The resin was washed 5 times and then incubated with either mRFP-Arf5 or -Arf6 HEK293T lysate for 2 hr . Resin was again washed 5 times and bound proteins eluted with 290 mM imidazole elution buffer . Eluted proteins and 10% of the input protein were analyzed by protein immunoblot using the primary antibodies rabbit anti-RalFRt , rabbit anti-Arf5 ( 1:1000 , Thermo Scientific , PA5-31432 ) and rabbit anti-Arf6 ( 1:1000 , Thermo Scientific , PA1-093 ) and the secondary antibody HRP anti-rabbit IgG ( 1:2000 , BioLegend , clone 6B9G9 ) . Negative and MISSION siRNAs against human Arf5 ( SASI_Hs01_00024789 ) and Arf6 ( SASI_Hs02_0033275 ) were obtained from Sigma Aldrich . All siRNA knockdowns were performed in HeLa cells using Lipofectamine 2000 ( Life Technologies ) . Cells were used 24 hrs post transfection . Knockdowns were verified by western blot analysis using 1:1000 dilution of primary antibodies rabbit anti-Arf5 or anti-Arf6 ( Thermo Scientific ) . As a loading control , membranes were re-probed with rabbit anti-GAPDH antibody ( 1:1000 , Abcam ) . Graphs show the mean ± SD of three independent experiments; 100 cells were counted for each condition in every experiment . Statistical analyses were performed using two-tailed equal variance Student’s t-test .
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Phylogenomics analysis indicates divergent mechanisms for host cell invasion across diverse species of obligate intracellular Rickettsia . For instance , only some Rickettsia species carry RalF , the rare bacterial Arf-GEF effector utilized by Legionella pneumophila to facilitate fusion of ER-derived membranes with its host-derived vacuole . For R . prowazekii ( Typhus Group , TG ) , prior in vitro studies suggested the Arf-GEF activity of RalF , which is absent from Spotted Fever Group species , might be spatially regulated at the host plasma membrane . Herein , we demonstrate RalF of R . typhi ( TG ) and R . felis ( Transitional Group ) localizes to the host plasma membrane , yet R . bellii ( Ancestral Group ) RalF shows perinuclear localization reminiscent of RalF-mediated recruitment of Arf1 by L . pneumophila to its vacuole . For R . typhi , RalF expression occurs early during infection , with RalF inactivation significantly reducing host cell invasion . Furthermore , RalF co-localization with Arf6 and the phosphoinositide PI ( 4 , 5 ) P2 at the host plasma membrane was determined to be critical for R . typhi invasion . Thus , our work illustrates that different intracellular lifestyles across species of Rickettsia and Legionella have driven divergent roles for RalF during host cell infection . Collectively , we identify lineage-specific Arf-GEF utilization across diverse rickettsial species , previously unappreciated mechanisms for host cell invasion and infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Which Way In? The RalF Arf-GEF Orchestrates Rickettsia Host Cell Invasion
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While pleiotropic adaptive mutations are thought to be central for evolution , little is known on the downstream molecular effects allowing adaptation to complex ecologically relevant environments . Here we show that Escherichia coli MG1655 adapts rapidly to the intestine of germ-free mice by single point mutations in EnvZ/OmpR two-component signal transduction system , which controls more than 100 genes . The selective advantage conferred by the mutations that modulate EnvZ/OmpR activities was the result of their independent and additive effects on flagellin expression and permeability . These results obtained in vivo thus suggest that global regulators may have evolved to coordinate activities that need to be fine-tuned simultaneously during adaptation to complex environments and that mutations in such regulators permit adjustment of the boundaries of physiological adaptation when switching between two very distinct environments .
Bacterial populations are powerful model to explore the mechanisms of evolution . Several in vivo experiments have pointed to the possible important role of pleiotropic adaptive mutations , but their molecular basis remain in most of cases largely elusive [1–3] . Here we have used gnotobiotic mice that offer a simplified and controlled albeit ecologically relevant experimental environment model to analyse the adaptation of E . coli MG1655 to the gut , as E . coli is usually the first colonizer of the mammalian newborn germ-free intestine [4 , 5] . Taking advantage that this laboratory strain is entirely sequenced and easily accessible to genetic manipulations , we could design a study that allowed deciphering the beneficial effects of pleiotropic mutations during intestinal colonisation . The mammalian intestine is a privileged physiological site to study how coevolution between hosts and the trillions of bacteria present in the microbiota has shaped the genome of each partner and promoted the development of mutualistic interactions . Genetic adaptation to the host over the millions years of coevolution has translated into physiological regulatory pathways that are rapidly mobilized in response to intestinal colonization [6–9] . In the microbiota , the contrast between the considerable number of species , more than a thousand , and the small number of bacterial divisions [10] , indicates that coevolution has selected bacterial genera possessing the genetic gear to adapt to the host environment , a notion supported by recent evidence that gut habitats in different host species dictate distinctive structures of intestinal bacterial communities [11] . Yet , the intestine is a complex and highly dynamic ecosystem composed of a large diversity of niches that vary in space and time , where bacteria face a permanent adaptive challenge . Furthermore , intestinal bacteria must be able to hurdle between their hosts across the exterior environment and for certain such as E . coli to switch between two entirely distinct natural environments . Gnotobiotic animals that offer a simplified albeit relevant model to study reciprocal mechanisms of adaptation between bacteria and their hosts , within a few days , the host can only adapt via physiological changes , whereas bacteria can adapt both by gene regulations and adaptive mutations . Indeed , we have previously demonstrated that adaptive mutations are central for efficient intestinal colonization by E . coli MG1655 [12] . Here we show that adaptation of this strain of E . coli during intestinal colonization entails rapid and parallel evolution in the EnvZ/OmpR two-components transduction system [13] . The gain of fitness provided by the diverse mutations selected in this global regulator during in vivo colonization results mainly from two distinct and measurable effects on motility and permeability that are both reduced in the mutant strains selected in the gut environment . These findings suggest that evolutionary pressures can put a diverse set of physiological functions facilitating adaptation under the control of one global regulator , and that mutations permit to adjust the scale of the physiological regulation controlled by this regulator in a given environment .
We have shown that adaptive mutations play a critical role in the success of the E . coli MG1655 strain in colonizing of the mouse gut [12] . A possible clue to the nature of the mutation ( s ) selected during colonization ensued from our subsequent observation of bacteria with a reduced motility phenotype in the feces of all gnotobiotic mice colonized with the wild type MG1655 strain ( WT ) ( Figure 1A ) . The colonies displayed a new small and granular morphotype ( SG ) distinct from the large and smooth morphotype ( LS ) of the WT inoculated strain ( Figure S1 ) . SG colonies forming bacteria , undetected in the initial inocula , appeared in the feces within two days , and reached a prevalence of 90% within seven days ( Figure 1B ) . Their phenotype remained stable when grown in vitro over many generations , indicating that it was heritable and may result from the rapid in vivo selection of mutation ( s ) . In order to identify the potential mutations responsible for the SG morphotype , a clone forming SG colonies ( SG1 ) isolated from mouse feces two days post-colonization , was transformed with a genomic DNA plasmid library generated from the parental WT strain . All plasmids that restored the ancestral WT LS morphotype carried the ompB locus , coding for the membrane sensor EnvZ and the transcriptional regulator OmpR of a two-component signal transduction system central to the osmolarity-dependent regulation of genetic expression [13] . A chloramphenicol resistance gene ( cat ) , inserted downstream the ompB locus in the chromosome of the WT ancestral and the SG1 strains , co-transduced with a 95% frequency with the morphotype ( LS or SG ) , indicating that in the SG1 strain , the DNA region surrounding cat was responsible for the SG morphotype . This region was sequenced for one SG and one LS clone harvested from the feces of each of the 8 independent mice inoculated with either MG1655 or an MG1655 E . coli strain carrying a yellow fluorescent protein ( YFP ) as reporter of fliC expression ( MG1655pfliC-YFP ) ( see below ) . While no mutation was detected in LS clones , all SG clones displayed a different missense point mutation , seven located in envZ , and one in ompR ( Table1 ) . The independent systematic and rapid selection of mutations in the same genes under identical experimental conditions is evidence for a strong selective advantage of the mutants during gut colonization [1] . To confirm and estimate the relative fitness of the SG1 mutant versus the ancestral strain in the mouse gut , we performed in vivo competition experiments between strains isogenic except for the point mutation present in the envZ gene of the SG1 strain ( SG1 mutation ) and the inducible fluorescent marker ( RFP vs . GFP ) . Prior experiments have indicated that these inducible markers do not induce any selection bias [14] . The ratio of mutant ( GFP ) to WT ( RFP ) colonies was defined after culture of the feces and ex vivo induction of the fluorescent marker . Competition experiments using initial ratios of mutant to WT strain of 1:1 , 1:100 and 1:1 , 000 indicated that the SG1 mutation confers a considerable fitness gain ( Figure 1C ) . With the assumption that the mean generation time for E . coli in the gut is 60 minutes [15] , the selective advantage of the SG1 mutation was estimated to be 24% when the mutant to WT strain ratio remained under 1:10 ( Table S1 ) . These data explained how adaptive mutations in envZ , that are likely to happen at a frequency below 10−7 , can be very rapidly selected upon colonisation with the WT strain . The selective advantage of the SG1 mutation decreased to approximately 10% when the ratio of mutant to WT strain increased over 1:10 , indicating that the selective advantage conferred by the mutation is frequence-dependent , consistent with the observation that the WT strain is not entirely displaced in the mono-colonization experiment ( Figure 1B ) . Importantly , the selected mutants did not exhibit the same motility phenotype as null mutations , since strains deleted for envZ , ompR or both kept the wild type LS morphotype ( Figure S1 ) . The membrane receptor kinase-phosphatase EnvZ forms a two-component pair with its cognate response regulator , OmpR , that enable cells to sense external changes of osmolarity [13] . The native receptor exists in two active but opposed signalling states , the OmpR kinase-dominant state and the OmpR-P phosphatase-dominant state . The balance between the two states determines the level of intracellular OmpR-P , which in turn determines the level of transcription of the many target genes [13] . One important bacterial function controlled by OmpR is motility , as OmpR regulates transcription of the flhDC operon , the master regulator of flagellar biosynthesis [16] . Several mutations identical to those selected in vivo during colonization were previously shown , by in vitro mutational analysis of EnvZ activities , to switch on the EnvZ kinase-dominant state [17 , 18] ( Figure 2 ) , resulting in increased levels of phospho-OmpR and repression of the flhDC operon [16] . Consistent with repression of flagellin expression in all SG mutants , no flagellin could be detected in cell lysates or supernatants obtained from stationary phase cultures , while the ancestral WT strain and the LS colonies ( that kept the wild-type motility phenotype after mouse colonization ) synthesised large amounts of flagellin in the same in vitro conditions ( Figure 3B ) . We have previously shown that the WT ancestral E . coli strain induces a potent NF-κB-dependent inflammatory response in intestinal epithelial cells that hinges on the interaction of flagellin with Toll receptor 5 [19] . Consistent with impaired flagellin expression , culture supernatants of SG strains in stationary conditions , failed to induce any inflammatory signal in monolayers of epithelial cells ( Figures 3A and S2 ) . These in vitro observations showing repression of flagellin synthesis in SG mutants were thus compatible with the observed defective motility morphotype . This morphotype was however clearly distinct from the pin point morphotype of the ΔfliC strain lacking the gene encoding flagellin , the primary flagellar subunit ( Figure S1 ) . In order to confirm that flagellin was downregulated by SG mutants in vivo in the intestine , germ-free mice were inoculated with an MG1655 E . coli strain carrying a yellow fluorescent protein ( YFP ) as reporter of fliC expression . The bacterial fluorescence in the feces was monitored in the feces by flow cytometry . Fluorescence decreased rapidly in mice inoculated with the WT strain , demonstrating in vivo down modulation of flagellin ( Figures 4 and S3 ) . Fluorescence monitoring after plating confirmed this result . Thus , in mice inoculated with the WT strain , the fraction of fluorescent colonies decreased to an average of 10% within 8 days , consistent with the selection of SG mutants described above ( Figure 4B ) . Furthermore , all bacteria forming non-fluorescent colonies tested on motility plate exhibited an SG morphotype , while those forming fluorescent colonies retained the LS morphotype ( Figure 4B ) . As OmpR/EnvZ controls many activities , we looked for other effects of the selected mutants . The characteristic motility phenotype of the SG selected mutants could be a result of an enhanced aggregation of bacteria to each other via the production of curli fibres encoded by the csgBA operon whose expression is regulated by the OmpR regulated csgD gene [20] . However , in contrast to the previously described ompR mutant of E . coli K12 that promotes biofilm formation via the derepression of the csgA gene [21] , none of the SG mutants exhibited changes in csgA gene expression and their biofilm formation was reduced compared to the WT strain ( data not shown ) . Another essential function of the two-component system envZ/ompR is to modulate membrane transport and permeability in response to medium osmolarity [22] . In particular , OmpR affects the reciprocal transcription of the small pore OmpC and large pore OmpF porins [23] , the two E . coli porins that are thought to play a central role in the adaptation of E . coli to the hyperosmotic conditions of the intestine [24] . Consistent with mutations that switch on the OmpR kinase-dominant state of EnvZ , selected SG mutants had decreased ompF and increased ompC mRNA and membrane protein levels compared to the WT ancestral strain ( Table 1 , Figure 3C ) , i . e . a reduced permeability phenotype [23] . Membrane permeability is central for both stress protection and nutritional competence [25] . It has been postulated that reduced permeability would be favourable in the environmental conditions of the gut , consisting of high osmolarity , low oxygen pressure and the presence of bile salts [24] . Indeed , all SG mutants grew much better than the ancestor in medium containing bile salts , the ancestor being entirely displaced within 7 hours of growth ( data not shown ) . Transcriptome analysis has pointed to the potential role of the two-component EnvZ/OmpR system in the regulation of multiple genes , including genes involved in transport across membranes and cell metabolism [22] , which may perhaps promote intestinal adaptation of E . coli . We therefore assessed the importance of flagellin repression and/or porins regulation on the parallel selection of envZ-ompR mutations . To analyse the role of flagellin in the selection of SG mutants , germ-free mice were inoculated with either the WT or the ΔfliC strain carrying a fluorescent protein ( YFP ) as reporter of fliC expression . Flow cytometry analysis of the feces showed that in situ fluorescence decreased faster and more extensively in mice inoculated with the WT than with the ΔfliC strain ( Figures 4A and S3 ) , a result confirmed by fluorescence monitoring after plating ( Figure 4B ) . Thus , in mice inoculated with the ΔfliC strain , the fraction of fluorescent colonies had decreased to only 50% on day 8 as compared to 10% in mice inoculated with the WT strain and the kinetics of selection was slower ( Figure 4B ) . Altogether , these results point to a strong impact of flagellin on the selection of EnvZ mutations . However , mutations downregulating fliC expression could still be selected despite the absence of flagellin , presumably because of the pleiotropic effect of these mutations . Sequencing the ompB locus in non-fluorescent clones harvested from 4 mice inoculated with the ΔfliC strain revealed missense point mutations ( Table 1 ) . Three were located in envZ , including one identical to a mutation found in a clone isolated from a mouse inoculated with the WT strain . The fourth one was located in the same codon of ompR as the mutation identified in a clone derived from the WT strain ( Table 1 ) . These results show that the adaptive advantage conveyed by selected mutations is only partially flagellin-dependent , suggesting that selected mutations provide further advantage resulting from the modulation of other genes controlled by OmpR . One likely candidate was the large porin encoding gene ompF . Indeed we have observed that this gene expression is downmodulated by the selected envZ-ompR mutations , resulting in a reduced permeability phenotype known to be associated with increased resistance to bile salts [26] , as observed for SG mutants . To assess the role of OmpF in the selection of EnvZ mutations , mice were inoculated with a ΔompF mutant that expresses OmpC but no OmpF protein ( Figure 3C ) and carries the YFP reporter of fliC expression . Although the impact of OmpF deletion alone was not as strong as the one of flagellin , selection of non fluorescent mutants studied in the feces after plating was significantly less efficient than in mice colonized with the WT E . coli strain ( Figure 5 ) . In one out of five studied mice , all non-fluorescent mutants exhibited an SG phenotype in soft agar plates . In two other mice , the non-fluorescent colonies had a totally nonmotile ( NM ) pinpoint phenotype comparable to the ΔfliC-engineered strain ( Figure S1 ) . In the last two mice , both SG and NM morphotypes were observed . Sequencing the ompB locus revealed a missense mutation in envZ in all SG clones tested ( Table 1 ) . In contrast , NM clones forming pin-point colonies had a normal envZ sequence but contain large deletions from 1 . 5 to 12 kb between the otsA and cheB loci , encompassing the flhDC operon and thereby precluding any expression of the whole flagellum operons ( Figure 6 ) . Interestingly , all deletions had occurred immediately upstream of an Insertion Sequence ( IS1 ) located just upstream the flhDC operon , and probably reflecting an imprecise excision of the IS [27] . The deleted genes , that all belong to the chemotaxis/motility pathway , failed to be amplified by PCR ( data not shown ) , showing that they were indeed lost rather than inserted ectopically . These results show that in mutants with reduced permeability , the major fitness gain results from repression of gene ( s ) controlled by FlhDC , probably flagellar genes and in particular the fliC gene encoding flagellin . To confirm this hypothesis , mice were inoculated with double ΔfliC ΔompF mutants carrying the YFP reporter of fliC expression and expressing the fluorescent CFP protein under the control of a constitutive promoter . Strikingly , combining deletions of porins and flagellin had additive effects and almost entirely abolished the in vivo selection of EnvZ/OmpR mutants ( Figure 5 ) . At day 11 post-inoculum , only 9% of clones were YFP-negative . None had mutation in the ompB locus , a deletion in the flhDC region or a mutation in the pfliC-YFP construct . These YFP-negative clones were all CFP positive and remained CFP positive during the 100 days of observation . Since YFP and CFP were expressed at the same level in the inoculated strain , the hypothesis that YFP expression was costly for the bacteria and eliminated by mutations is unlikely . Therefore , our results show that the selective pleiotropic advantage conferred EnvZ/OmpR mutation predominantly results from a combined effect of modulation of fliC expression and membrane permeability , but does not exclude minor additional effect ( s ) of ( an ) other as yet uncharacterized gene ( s ) under the control of EnvZ/OmpR .
Due to their high growth rate and large population size , microbes have a remarkable capacity to evolve and diversify by generation and spread of mutations that improve their fitness in a given environment [1] . We have previously observed that within a few days a mutant strain with a high mutation rate increased in frequency to the expense of the parental commensal E . coli MG1655 strain during gut colonization . In contrast , the mutator strain lost the competition against a clone collected from the feces of mice colonized for 40 days with the parental commensal E . coli MG1655 [12] . These results suggested that adaptive mutations enable bacteria to rapidly and efficiently cope with the drastic environmental changes encountered during gut colonization . Our novel results identify the central role of the EnvZ/OmpR regulon in the physiological adaptation of E . coli MG1655 to the gut environment , and show that adaptive mutations in this two-component system provide an additional gear to adjust precisely the scale of the physiological regulation controlled by this regulator to the gut environment . Furthermore our results provide the molecular basis of the beneficial effects of the pleiotropic mutations in EnvZ/OmpR in adaptation of E . coli MG1655 to the mouse gut . Mutations in the envZ/ompR locus were systematically detected in 90% of bacteria harvested from independent mice feces within a week of colonization with WT E . coli MG1655 . Except for one mutation in its cognate transcription factor OmpR , all mutations were found in the membrane sensor EnvZ . The major fitness gain conferred by these mutations was confirmed by in vivo competitions between the ancestor WT strain and an isogenic mutant strain harboring the prototype SG1 envZ mutation . The emergence of distinct point mutations at the same two-component locus in bacterial populations evolving in different colonized mice suggested a comparable impact on the physiological effects mediating the fitness gain due to these mutations . Indeed all mutations resulted in profound repression of flagellin expression and modulation of OmpF versus OmpC porin expression yielding a reduced permeability phenotype . This phenotype is typical of mutations that switch the phosphatase/kinase membrane sensor EnvZ toward a OmpR kinase-dominant state . Indeed several of the missense mutations selected during in vivo colonisation were previously identified by in vitro mutational analysis as turning on this functional state [17 , 18] . Mutations selected during colonization were not restricted to the catalytic domains of EnvZ , but were also found in the periplasmic sensor and cytoplasmic linker domains , highlighting the participation of all of the protein's domains in the control of gene regulation ( Figure 2 ) . Interestingly in mice colonized with the ΔfliC mutant , where adaptive mutants were mainly selected on their reduced permeability phenotype , mutations were still exclusively found in the EnvZ/OmpR system , a result that underscores the prominent role of the EnvZ/ompR system in the regulation of membrane permeability of E . coli MG1655 during intestinal colonization . Notably , colonization with the WT E . coli did not select for mutations inactivating genes specifically controlling motility or permeability . Yet , selection of mutants with deletion of flhD/C operon was observed during colonization by the ΔompF strain , a result reminiscent of observations in streptomycin-treated mice [28 , 29] . Clonal interference [30] thus likely prevents the selection of mutations affecting only one function , presumably associated with smaller selective value than the pleiotropic mutations in envZ/ompR modulating simultaneously functions as different as permeability and motility . Indeed , using reporter mutant bacteria carrying a fluorescent protein under the control of the fliC promoter , we could clearly demonstrate that the selective advantage conveyed by mutations in envZ/ompR resulted from their pleiotropic and additive effects on the repression of flagellin production and OmpF porin expression . The almost complete abolition of adaptive selection of envZ/ompR mutations in mice colonized with a double mutant E . coli strain that lacks both fliC and ompF , underscores the major contribution of the pathways controlled by envZ and ompR in the intestinal adaptation of E . coli . The precise elucidation of the selective forces is beyond the scope of this study , but likely scenarios are briefly discussed below . Flagellin downregulation could be selected for via its pro-inflammatory role [19 , 31–35] , via its direct energetic cost [28 , 36] , or via still non-identified mechanisms . The fitness gain conveyed by reduced permeability was suggested by in vitro analysis indicating that , similar to ΔompF mutants , all ompR/envZ mutants grew much better in medium containing high concentrations of bile salts , a major stress factor for bacteria in the intestinal lumen . Interestingly , it has been reported that the concentration of biliary salts in the intestinal lumen decreases upon colonization [37 , 38] . A lower concentration of biliary salts in mice treated by streptomycin which empties the enterobacteriae niche but does not deplete completely the intestinal flora , might explain the predominant selection of mutants in the flhD/C operon in this mouse model [28 , 29] . In E . coli , stress protection comes at the cost of nutritional competence through the regulation of membrane permeability [39] . In the gut rich environment , bacterial nutrient intake is likely sufficient even if permeability is restrained , so that the growth rate is not significantly affected [25] . Yet , the extent of physiological regulation allowed by wild type EnvZ/OmpR might not be optimal to respond to our experimental mice gut conditions . Thanks to adaptive mutations in EnvZ/OmpR , the trade-off between self-preservation and nutritional competence ( SPANC balance ) might easily be switched to either better resistance or faster growth [25] . To mutate may thus represent a complementary genetic gear to adjust precisely the scale of physiological regulation controlled by a global regulator when switching between complex environments . Notably , the selective advantage conferred by the envZ mutations was frequency dependent , consistent with the observation that in mice colonized with the WT strain , the mutation invades rapidly and massively the population , but does not go to fixation , as a minor part of the population kept the original colony morphotype ( and genotype for envZ-ompR ) . These results suggest a mechanism causing the coexistence of ancestral and evolved form , perhaps because the ancestral phenotype confers some advantage to colonize a specific niche . Work is in progress to address this issue . Experiments with microbial populations have been largely used to gain insight into the mechanics of evolution and have pointed to the possible important role of pleiotropic adaptive mutations [1] . Thus , finding mutations in regulatory genes is a recurrent observation both in natural populations and during in vitro experimental evolution , that led to postulate that mutations affecting regulators are more likely to promote adaptation and evolution than those improving a single enzymatic step [1 , 25 , 40] . Our results obtained in an in vivo model of bacterial evolution supports this hypothesis . As mutations in global regulators affect the regulation of many genes , they must be pleiotropic and are thus expected to result in the expression not only of beneficial but also of detrimental traits . The molecular mechanisms responsible for the selection of such pleiotropic mutations have therefore remained largely elusive in most systems . A recent study in a simple ecological in vitro model [41] , has shown that adaptive mutations allow P . fluorescens to occupy a novel ecological niche at the air-liquid interface [42] . All selected strains had pleiotropic loss-of-functions mutations in one gene encoding a putative methyl-esterase in the wsp operon [2 , 3] . Drawing analogy with the che operon of E . coli that encodes proteins homologous to the wsp operon , the authors suggested that this protein acts in concert with a putative methyl-transferase to adjust the activity of a kinase . The mutations may thus destroy the capacity of the pathway to fluctuate between activity states , producing instead a steady state output allowing niche specialization . Our results , combined with previous biochemical works [17] , provide direct evidence that a distinct scenario promotes the in vivo adaptation of an E . coli MG1655 to the gut of germ-free mice . In the case of EnvZ/ompR , the two opposed enzymatic activities are exerted by the cytoplasmic domain of EnvZ and are modulated in response to signals sensed by the external domain of the protein . Mutations in EnvZ , that directly affect the balance between two activities , are selected because of their independent and additive effects on genes controlling flagellin expression and membrane permeability . Dissecting the fitness gain due to these independent pathways allowed us to demonstrate that the EnvZ/OmpR global regulator orchestrates the physiological adaptation of E . coli MG1655 to the gut environment . More generally , the observation that the EnvZ/OmpR system gathers under its control genes central to promote intestinal colonization leads us to suggest that global regulators may have arisen during evolution to optimize the coordination of genes that collaborate to adapt to a given niche . Mutations in such global regulators may provide a complementary genetic tool that allows bacteria to extend the scale of the physiological regulation and promotes their rapid adaptation when confronted to very specific environments .
All strains were derived from the commensal flagellated E . coli K12 MG1655 sequenced strain [43] . The MG1655 ΔfliC E . coli isogenic mutant has been described [19] . To construct the reporter WT pfliC-YFP strain used to monitor in vivo activity of fliC promoter , sequence encoding the fluorescent protein YFP++ [44] was cloned downstream the upstream region of the fliC gene ( pfliC: from nucleotides −230 to +5 relative to the translation start ) . The fragment ( pfliC YFP , T1T2 and cat ) was flanked by 40 nucleotides sequences homologous respectively to the 5′ and 3′ of the IS2 and IS30 insertion sequences interrupting the ybdA E . coli gene and by KpnI and SphI restriction sites and cloned in p5Y , a pUC-18-derived plasmid . After plasmid amplification , the fragment was inserted into the ybdA gene of the MG1655 E . coli chromosome replacing the IS sequences following method already described [45] . MG1655 ΔfliC pfliC-YFP was constructed by P1 phage co-transduction of the pfliC-YFP-v+ and the cat alleles from MG1655 pfliC-YFP into MG1655 ΔfliC strain . The MG1655 ompB-cat and SG1 ompB-cat E . coli strains ( used to assess the link between the ompB locus and the motility phenotype ) were constructed by inserting the FRT flanked cat gene of the pKD3 plasmid [45] between the envZ and pck genes as described [45] , using PCR primers that contained a 40 bases-5′ end extension centered on the translation stops of the envZ or pck gene . Insertion of the PCR product was monitored using primers respectively identical or complementary to the nucleotides 1562 to 1582 of pck and 1238 to 1258 of the EnvZ gene . These strains kept the motility phenotype of the MG1655 and SG1 strains respectively . The MG1655 ptet-GFP ompBSG1-cat and MG1655 ptet-RFP ompB-cat E . coli strains ( used to measure the relative fitness of the SG1 strain in vivo ) were constructed by introducing by P1 phage co-transduction of the ompB region from the SG1 ompB-cat strain and the cat allele into the MG1655 ptet-GFP and the MG1655 ptet-RFP strains respectively ( described in [14] ) . The MG1655 ptet-GFP ompBSG1-cat strain was selected among granulous transductants ( SG morphotype ) in motility agar whereas the MG1655 ptet-RFP ompB-cat was selected among transductants that kept the WT motility phenotype ( LS morphotype ) . The ΔompF , ΔompC , ΔompR , ΔenvZ , and ΔompB strains were constructed by replacing the ompF , ompC , ompR , envZ and envZ and ompR open reading frame respectively from start to stop codon by the FRT flanked cat gene of the pKD3 in the E . coli MG1655 strain following method already described [45] . The MG1655 ΔompF pfliC-YFP strain was constructed by P1 phage co-transduction of the ΔompF and the cat alleles from MG1655 ΔompF into MG1655 pfliC-YFP p2rrnB-CFP strain . The MG1655 ΔfliC ΔompF pfliC-YFP strain was constructed by P1 phage co-transduction of the ΔompF and the cat alleles from MG1655 ΔompF into MG1655 ΔfliC pfliC-YFP p2rrnB-CFP strain . To construct the reporter p2rrnB-CFP , sequence encoding the fluorescent protein CFP++ was cloned upstream of the promoter p2 of the rrnB operon ( p2rrnB: from nucleotides 152 to 94 relative to the translation start of the rrsB gene ) . The fragment ( prrnB-cfp , T1T2 and cat ) was flanked by 40 nucleotides sequences homologous respectively to the 5′ and 3′ of the IntC ( IntS ) E . coli gene and by KpnI and PacI restriction sites and cloned in a pUC-18-derived plasmid . After plasmid amplification , the fragment was inserted into the IntC gene of the MG1655 E . coli chromosome following method already described [45] . Genomic DNA from E . coli MG1655 strain was prepared with the Wizard Genomic DNA Preparation kit ( Promega , Charbonnières , France ) and partially digested with the Sau3AI restriction enzyme . Fragments ranging from 2 to 6 kb were eluted from agarose gel ( Gel extraction kit , Promega ) , and cloned into BamHI-digested and dephosphorylated pACYC184 plasmid . The purified ligation reaction was used to electro-transform DH5-α E . coli . Transformants were selected on LB plates containing chloramphenicol . Ligation efficiency was 95% and average size of genomic inserts 3 Kb . Plasmids were extracted from about 1 . 5 × 104 pooled colonies ( Miniprep kit , Promega ) . The SG1 clone was transformed with the genomic library and transformants were selected on motility plates supplemented with chloramphenicol . The clones with a wild type motility phenotype ( LS ) were isolated and the E . coli MG1655-derived locus carried by the transforming plasmids was determined by sequencing with primers flanking the cloning site . Sequencing of the ompB locus ( from the greB translation stop to the pck translation stop ) and pfliC-YFP construction of the MG1655 strain and of the clones isolated from mouse feces was carried out on purified PCR amplification products using standard procedures in the Institut Cochin sequence facilities . The following primers were used to define the size of the deletions in MG1655 ΔompF pfliC-YFP non motile ( NM ) mutants: otsAup ( 5′-GTGCAACTCAGGCATCATGG-3′ ) either in association with CheBdwn ( 5′-CGTATGGTGGAAAAGTCATCC-3′ ) for clones NM2 and NM4 , with CheAdwn ( 5′-cgctgaagccaaaagttcctgc-3′ ) for the clone NM1 and with ArgSdwn ( 5′-CTAACGGCATGATGGGAGTTG-3′ ) for clone NM3 . Bacterial motility was monitored in soft agar plates ( 4 . 5 g/L agar in Luria broth medium ( LB ) ) at 30 °C for 24 h . Enumeration of fluorescent bacteria was made on solid LB agar plates ( 15 g/L ) after a 48-h incubation at 37 °C using a lighting system ( LT-9500–220 Illumatool , Lightools Research ) . YFP fluorescence was detected in colonies using 470-nm excitation wavelengths and 530-nm reading filters . Fluorescence detection in feces was performed on dilutions of freshly passed feces using a BD-LSR flow cytometer ( Becton Dickinson ) . Data were analyzed with Cell Quest software ( Becton Dickinson ) . Strains were grown in LB for 16 h , and population sizes were determined by plating appropriate dilutions of the culture on LB plates . 50 μL of a 1 × 104 fold dilution of the pre-culture of the mutant and of the reference parental strain were inoculated in 5 mL of LB and LB supplemented with bile salts ( Bile salts N°3 , Difco ) at 5% ( M/W ) and incubated at 37 °C under agitation . Mutant and parental population sizes were determined after 7h30 of culture by counting SG and LS populations on motility plates ( for SG1 and SG2 against MG1655 competitions ) , or fluorescent and non-fluorescent populations as described above . Conventional and germ-free C3H/HeN mice were bred at the INRA facilities . Germ-free and gnotobiotic mice were reared in isolators ( Ingenia ) in individual cages and fed ad libitum on a commercial diet sterilized by gamma irradiation ( 40 kGy ) and supplied with autoclaved ( 20 min , 120 °C ) tap water . For colonization experiments , 8–12-week-old germ-free mice were inoculated per os with 104 bacteria from the chosen strain in 0 . 5 mL 10−2 M MgSO4 . Colonization was monitored by bacterial counts in individual freshly harvested fecal samples as described [12] . For in vivo bacterial competition , MG1655 ptet-GFP ompBSG1-cat ( containing the envZ SG1 I281S mutant allele ) and MG1655 ptet-RFP ompB-cat E . coli ( containing the envZ wild type allele ) were grown in LB for 16 h and mixed at the 1:1 , 1:100 , 1:1 , 000 SG to WT ratios . 0 . 5 mL of a 1 × 104 fold dilution in 10−2M MgSO4 of these mix were used for mouse colonization . Mutant and WT population sizes were determined every 12 h by counting Red and Green fluorescent CFU on plates containing anhydrotetracycline ( 50 μM Acros ) during 5 days following colonization . The maximal relative fitness was estimated by fitting an exponential curve to the evolution of the SG/WT ratio between 12 and 36 hours following colonization with the initial ratios 1:100 and 1:1 , 000 . All procedures were carried out in accordance with the European guidelines for the care and use of laboratory animals . Stimulation of monolayers of the human IEC line HT29-19A with live bacteria , preparation of epithelial cell nuclear extracts , electrophoretic mobility shift assay ( EMSA ) , determination of CCL-20 mRNA level by real-time quantitative PCR after a 6-h stimulation and determination of IL-8 concentrations in epithelial cell supernatants by enzyme-linked immunosorbent assay ( ELISA ) ( Duoset kits , R&D Systems ) were all performed as previously described [19] . Total RNA was extracted from 5 ml of stationnary phase culture ( at 37 °C , with agitation ) using the RNeasy kit ( Qiagen ) , according to the manufacturer's instructions . RNA was treated with four units of the Turbo DNA-free ( Ambion ) for 1h at 37 °C . RNA was quantified by measuring the optical density at 260 nm and checked for degradation by an agarose gel electrophoresis . The cDNA synthesis was performed using 2 μg RNA with random hexamers ( 12 . 5 ng/ml ) and the Superscript II RNAse H− kit 5 ( invitrogen ) according to the manufacturer's instructions . The real-time PCR experiments were performed using the SYBRgreen PCR Master Mix ( Applied Biosystems ) to quantify the expression level of the ompC and ompF genes . The rpoD gene was chosen as a reference gene for data normalization . The primers RpoD1RT ( 5′-GTAGTCGGTGTTCATATCGA-3′ ) , RpoD1FT ( 5′-CGTCTGATCATGAAGCTCT-3′ ) , OmpC2RT ( 5′-GTCAGTGTTACGGTAGGT-3′ ) , OmpC2FT ( 5′-CGACTACGGTCGTAACTA-3′ ) , OmpF2RT ( 5′-CCTGTATGCAGTATCACCA-3′ ) and OmpF2FT ( 5′-CCAGGGTAACAACTCTGAA-3′ ) were designed by the Primer Express software ( Applied Biosystems ) . Amplification and detection of the specific products were carried out with the 7300 Real Time PCR System ( Applied Biosystems ) . Data analysis was performed with the 7300 System Software . For each target gene , the average Ct value was calculated from triplicate reactions for RNA samples . The difference between Ct of the target gene and Ct of the endogenous reference gene ( rpoD ) was defined as the ΔCt . The ΔΔCt value described the difference between the ΔCt of the wild type strain and the mutant strain . The difference in expression was calculated as 2ΔΔCt , and a twofold difference was considered as significant . Bacterial proteins were obtained from culture supernatants precipitated by 10% trichloroacetic acid and from bacterial pellets sonicated in PBS containing an anti-protease cocktail ( Roche Diagnostics ) and 1% Triton X100 ( Sigma ) . Twenty μL of 25-fold concentrated bacterial supernatants or 20 μg of total proteins from bacterial lysates were electrophoresed on 10% SDS-PAGE gels and transferred onto PVDF membranes ( Amersham Biosciences , Saclay , France ) . Membranes blocked with 5% nonfat dry milk in 20 mM Tris pH 7 . 5 , 150 mM NaCl , and 0 . 05% Tween-20 , were incubated overnight with a 1:2 , 000 dilution of monoclonal antibody 15D8 against E . coli flagellin ( Bioveris Europe ) , and then for 1 h with a 1:8 , 000 dilution of HRP-conjugated goat anti-mouse immunoglobulins ( Amersham Biosciences ) . HRP was revealed with ECL-Plus light ( Amersham Biosciences ) using a luminescent image analyzer LAS-1 , 000plus ( Fujifilm ) . Cultures ( 20 ml ) grown at 37 °C with agitation were harverested and washed in 20 mM sodium phosphate buffer , pH 7 . 4 . The pellet were suspended and sonicated in 10 mM Hepes buffer , pH 7 . 4 ( Vibra-cell , Bioblock Scientific ) . Sarkosyl was added to a final concentration of 0 . 5% and the detergent extraction was carried out at room temperature for 1 hour . The unbroken cells were removed by centrifugation at 3 , 000 rpm for 10 min , and the outer membrane fraction was obtained by an ultracentrifugation at 40 , 000 rpm for 1 hour . The outer membrane proteins were suspended in 10 mM Hepes and quantified by Bradford Method ( Biorad ) . Samples were analyzed by SDS-polyacrylamide gel electrophoresis containing 8M urea as described previously [46] . Gels were transferred onto PVDF membranes at 200 mAmp for 50 minutes . Membranes blocked with 5% nonfat dry milk in 20 mM Tris pH 7 . 5 , 150 mM NaCl , and 0 . 05% Tween-20 , were incubated overnight with a 1/1 , 000 dilution of an rabit anti-OmpC/F ( gift from Roland Lloubès , CNRS UPR 9027 , Institut de Biologie Structurale et Microbiologie , Marseille ) , and then for 1 h with horseradish peroxidase conjugated anti-rabbit immunoglobulins ( Cell Signaling Technology ) .
|
The mammalian intestine is a privileged physiological site to study how coevolution between hosts and the trillions of bacteria present in the microbiota has shaped the genome of each partner and promoted the development of mutualistic interactions . Herein we have used germ-free mice , a simplified albeit ecologically relevant system , to analyse intestinal adaptation of a model bacterial strain , Escherichia coli MG1655 . Our results show that single point mutations in the ompB master regulator confer a striking selective adaptive advantage . OmpB comprises EnvZ , a transmembrane sensor with a dual kinase/phosphatase activity , and OmpR , a transcription factor controlling more than 100 target genes . In response to environmental changes , EnvZ modulates the phosphorylation and thereby the transcriptional activity of OmpR . We further show that the selective advantage conferred by OmpB mutations is related to their additive and independent effects on genes regulating permeability and flagellin expression , two major set of genes controlled by OmpR . These results suggest that global regulators may have evolved to coordinate physiological activities necessary for adaptation to complex environments and that mutations offer a complementary genetic mechanism to adjust the scale of the physiological regulation controlled by these regulators in distinct environments .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"ecology",
"immunology",
"microbiology",
"evolutionary",
"biology",
"eubacteria",
"mus",
"(mouse)"
] |
2008
|
Dissecting the Genetic Components of Adaptation of Escherichia coli to the Mouse Gut
|
We present a new computational model of speech motor control: the Feedback-Aware Control of Tasks in Speech or FACTS model . FACTS employs a hierarchical state feedback control architecture to control simulated vocal tract and produce intelligible speech . The model includes higher-level control of speech tasks and lower-level control of speech articulators . The task controller is modeled as a dynamical system governing the creation of desired constrictions in the vocal tract , after Task Dynamics . Both the task and articulatory controllers rely on an internal estimate of the current state of the vocal tract to generate motor commands . This estimate is derived , based on efference copy of applied controls , from a forward model that predicts both the next vocal tract state as well as expected auditory and somatosensory feedback . A comparison between predicted feedback and actual feedback is then used to update the internal state prediction . FACTS is able to qualitatively replicate many characteristics of the human speech system: the model is robust to noise in both the sensory and motor pathways , is relatively unaffected by a loss of auditory feedback but is more significantly impacted by the loss of somatosensory feedback , and responds appropriately to externally-imposed alterations of auditory and somatosensory feedback . The model also replicates previously hypothesized trade-offs between reliance on auditory and somatosensory feedback and shows for the first time how this relationship may be mediated by acuity in each sensory domain . These results have important implications for our understanding of the speech motor control system in humans .
A schematic control diagram of the FACTS model is shown in Fig 1 . Modules that build on Task Dynamics are shown in blue , and the articulatory state estimation process ( or observer ) is shown in red . Following Task Dynamics , speech tasks in the FACTS model are hypothesized to be desired constrictions in the vocal tract ( e . g . , close the lips for a [b] ) . Each of these speech tasks , or gestures , can be specified in terms of it’s constriction location ( where in the vocal tract the constriction is formed ) and it’s constriction degree ( how narrow the constriction is ) . We model each gesture as a separate critically-damped second-order system [32] . Interestingly , similar dynamical behavior has been seen at a neural population level during the planning and execution of reaching movements in non-human primates [38 , 39] and recently in human speech movements [40] , suggesting that a dynamical systems model of task-level control may be an appropriate first approximation to the neural activity that controls movement production . However , the architecture of the model would also allow for tasks in other control spaces , such as auditory targets ( c . f . [13 , 19] ) , though an appropriate task feedback control law for such targets would need to be developed ( consistent with engineering control theory , we refer to the term “controller” as a “control law” ) . To what extent , if any , incorporation of auditory targets would impact or alter the results presented here is not immediately clear . This is a promising avenue for future research , as it may provide a way to bridge existing models which posit either constriction- or sensory-based targets . We leave such explorations for future work , but note here that the results presented here may apply only to the current formulation of FACTS with constriction-based targets . FACTS uses as the Haskins Configurable Articulatory Synthesizer ( or CASY ) [41–43] as the model of the vocal tract plant being controlled . The relevant parameters of the CASY model required to move the tongue body to produce a vowel ( and which fully describe the articulatory space for the majority of the simulations in this paper ) are the Jaw Angle ( JA , angle of the jaw relative to the temporomandibular joint ) , Condyle Angle ( CA , the angle of the center of the tongue relative to the jaw , measured at the temporomandibular joint ) , and the Condyle Length ( CL , distance of the center of the tongue from the temporomandibular joint along the Condyle Angle ) . The CASY model is shown in Fig 2 . The model begins by receiving the output from a linguistic planning module . Currently , this is implemented as a gestural score in the framework of Articulatory Phonology [33 , 34] . These gestural scores list the control parameters ( e . g . , target constriction degree , constriction location , damping , etc . ) for each gesture in a desired utterance as well as each gesture’s onset and offset times . For example , the word “mod” ( [mad] ) has four gestures: simultaneous activation of a gesture driving closure at the lips for [m] , a gesture driving an opening of the velum for nasalization of [m] , and a gesture driving a wide opening between the tongue and pharyngeal wall for the vowel [a] . These are followed by a gesture driving closure between the tongue tip and hard palate for [d] ( Fig 3 ) . The task state feedback control law takes these gestural scores as input and generates a task-level command based on the current state of the ongoing constriction tasks . In this way , the task-level commands are dependent on the current task-level state . For example , if the lips are already closed during production of a /b/ , a very different command needs to be generated than if the lips are far apart . These task-level commands are converted into motor commands that can drive changes in the positions of the speech articulators by the articulatory state feedback control law , using information about the current articulatory state of the vocal tract . The motor commands generate changes in the model vocal tract articulators ( or plant ) , which are then used to generate an acoustic signal . The articulatory state estimator ( sometimes called an observer in other control models ) combines a copy of the outgoing motor command ( or efference copy ) with auditory and somatosensory feedback to generate an internal estimate of the articulatory state of the plant . First , the efference copy of the motor command is used ( in combination with the previous aritculatory state estimate ) to generate a prediction of the articulatory state . This is then used by a forward model ( learned here via LWPR ) to generate auditory and somatosensory predictions , which are compared to incoming sensory signals to generate sensory errors . Subsequently , these sensory errors are used to correct the state prediction to generate the final state estimate . The final articulatory state estimate is used by the articulatory state feedback control law to generate the next motor command , as well as being passed to the task state estimator to estimate the current task state , or values ( positions ) and first derivatives ( velocities ) of the speech tasks ( note the Task State was called the Vocal Tract State in earlier presentations of the model [44 , 45] ) . Finally , this estimated task-level state is passed to the task state feedback control law to generate the next task-level command . A more detailed mathematical description of the model can be found in the methods .
Fig 4 visualizes a three dimensional subspace of the learned mapping from the 10-dimensional articulatory state space to the 3-dimensional space of formant frequencies ( F1—F3 ) . Specifically , we look at the mapping from the tongue condyle length and condyle angle to the first ( see Fig 4A–4C ) and second formants ( see Fig 4D–4F ) , projected onto each two-dimensional plane . We also plot normalized histograms of the number of receptive fields that cover each region of the space ( represented as a heatmap in Fig 4A and 4D and with a thick blue line in the other subplots ) . In each figure , the size of the circles is proportional to the absolute value of the error between the actual and predicted formant values . Overall , the fit of the model results in an average error magnitude of 4 . 2 Hz ( std . , 9 . 1 Hz ) for F1 and 6 . 6 Hz ( std . , 19 . 1 Hz ) for F2 . For comparison , the range of the data was 310–681 Hz for F1 and 930–2197 Hz for F2 . Fit error increases in regions of the space that are relatively sparsely covered by receptive fields . In addition , the higher frequency of smaller circles at the margins of the distribution ( and therefore the edges of the articulatory space ) suggest that we may need fewer receptive fields to cover these regions . Of course , this means that we do see some bigger circles in these regions where the functional mapping is not adequately represented by a small number of fields . Also note that we are only plotting the number of receptive fields that are employed to cover a given region of articulatory space , and this is not indicative of how much weight they carry in representing that region of space . How does the presence or absence of sensory feedback affect the speech motor control system ? While there is no direct evidence to date on the effects of total loss of sensory information in human speech , some evidence comes from when sensory feedback from a single modality is attenuated or eliminated . Notably , the effects of removing auditory and somatosensory feedback differ . In terms of auditory feedback , speech production is relatively unaffected by it’s absence: speech is generally unaffected when auditory feedback is masked by loud masking noise [7 , 8] . However , alterations to somatosensory feedback have larger effects: blocking oral tactile sensation through afferent nerve injections or oral anesthesia leads to substantial imprecision in speech articulation [46 , 47] . Fig 5 presents simulations from the FACTS model testing the ability of the model to replicate the effects of removing sensory feedback seen in human speech . All simulations modeled the vowel sequence [ǝ a i] . 100 simulations were run for each of four conditions: normal feedback ( 5B ) , somatosensory feedback only ( 5C ) , auditory feedback only ( 5D ) , and no sensory feedback ( 5E ) . For clarity , only the trajectory of the tongue body in the CASY articulatory model is shown for each simulation . In the normal feedback condition ( Fig 5B ) , the tongue lowers from [ǝ] to [a] , then raises and fronts from [a] to [i] . Note that there is some variability across simulation runs due to the noise in the motor and sensory systems . This variability is also found in human behavior and the ability of the state feedback control architecture to replicate this variability is a strength of this approach [25] . The effect of removing auditory feedback ( Fig 5C ) leads to a significant , though small , increase in the variability of the tongue body movement as measured by the tongue location at the movement endpoint ( Fig 5I ) , though this effect was not seen in measures of Condyle Angle or Condyle Length variability ( Fig 5G and 5H ) . Interestingly , while variablity increased , prediction error slightly decreased in this condition ( Fig 5F ) . Overall , these results are consistent with experimental results that demonstrate that speech is essentially unaffected , in the short term , by the loss of auditory information ( though auditory feedback is important for pitch and amplitude regulation [48] as well as to maintain articulatory accuracy in the long term [48–50] ) . Removing somatosensory feedback while maintaining auditory feedback ( Fig 5B ) leads to an increase in both variability across simulation runs as well as an increase in prediction error ( Fig 5F–5I ) . This result is broadly consistent with the fact that reduction of tactile sensation via oral anaesthetic or nerve block leads to imprecise articulation for both consonants and vowels [47 , 51] ( though the acoustic effects of this imprecision may be less perceptible for vowels [47] ) . However , a caveat must be made that our current model does not include tactile sensation , only proprioceptive information . Unfortunately , it is impossible to block proprioceptive information from the tongue , as that afferent information is likely carried along the same nerve ( hypoglossal nerve ) as the efferent motor commands [52] . It is difficult to prove , then , exactly how a complete loss of proprioception would affect speech . Nonetheless , the current model results are consistent with studies that how shown severe dyskinesia in reaching movements after elimination of proprioception in non-human primates ( see [53] for a review ) and in human patients with severe proprioceptive deficits [54] . In summary , although the FACTS model currently includes only proprioceptive sensory information rather than both proprioceptive and tactile signals , these simulation results are consistent with a critical role for the somatosensory system in maintaining the fine accuracy of the speech motor control system . While removal of only auditory feedback lead to only small increases in variability ( in both FACTS simulations and human speech ) , our simulations show speech in the complete absence of sensory feedback ( Fig 5E ) shows much larger variability than the absence of either auditory or somatosensory feedback alone . This is consistent with human behvaior [51] , and occurs because without sensory feedback there is no way to detect and correct for the noise inherent in the motor system ( shown by the large prediction errors and increased articulatory variability in Fig 5F ) . The effects of changing the noise levels in the system can be see in Fig 5J and 5K . For these simulations , only one type of feedback was used at a time: somatosensory ( cyan ) or auditory ( purple ) . Noise levels ( shown on the x axis ) reflect both the sensory system noise and the internal estimate of that noise , which were set to be equal . Each data point reflects 100 stable simulations . Data for the acoustic-only simulations are not shown for noise levels below 1e-5 as the model became highly unstable in these conditions to due inaccurate articulatory state estimates ( the number of unstable or divergent simulations is shown in Fig 5J ) . For the somatosensory system , the prediction error and articulatory variability ( shown here for the Condyle Angle ) decrease as the noise decreases . However , for the auditory system , both prediction error and articulatory variability increase as the noise decreases . Because of the Kalman gain , decreased noise in a sensory or predictive signal leads not only to a more accurate signal , but also to a greater reliance on that signal compared to the internal state prediction . When the system relies more on the somatosensory signal , this results in a more accurate state estimate as the somatosensory signal directly reflects the state of the plant . When the system relies more on the auditory signal , however , this results in a less accurate state estimate as the auditory signal only indirectly reflects the state of the plant as a result of the nonlinear , many-to-one articulatory-to-acoustic mapping of the vocal tract . Thus , relying principally on the auditory signal to estimate the state of the speech articulators leads to inaccuracies in the final estimate and , subsequently , high trial-to-trial variability in movements generated from these estimates . In sum , FACTS is able to replicate the variability seen in human speech , as well as qualitatively match the effects of both auditory and somatosensory masking on speech accuracy . While the variability of human speech in the absence of proprioceptive feedback remains untested , the FACTS simulation results make a strong prediction that could be empirically tested in future work if some manner of blocking or altering proprioceptive signals could be devised . When a downward mechanical load is applied to the jaw during the production of a consonant , speakers respond by increasing the movements of the other speech articulators in a task-specific manner to achieve full closure of the vocal tract [3 , 4 , 31] . For example , when the jaw is perturbed during production of a bilabial stops /b/ or /p/ , the upper lip moves downward to a greater extent than normal to compensate for the lower jaw position . This upper lip lowering is not found for jaw perturbations during /f/ or /z/ , indicating it is specific to sounds produced using the upper lip . Conversely , tongue muscle activity is larger following jaw perturbation for /z/ , which involves a constriction made with the tongue tip , but not for /b/ , for which the tongue is not actively involved . The ability to sense and compensate for mechanical perturbations relies on the somatosensory system . We tested the ability of FACTS to reproduce the task-specific compensatory responses to jaw load application seen in human speakers by applying a small downward acceleration to the jaw ( Jaw Angle parameter in CASY ) starting midway through a consonant closure for stops produced with the lips ( /b/ ) and tongue tip ( /d/ ) . The perturbation continued to the end of the word . As shown in Fig 6A , the model produces greater lowering of the upper lip ( as well as greater raising of the lower lip ) when the jaw is fixed during production of /b/ , but not during /d/ , mirroring the observed response in human speech . In addition to the task-specific response to mechanical perturbations , speakers will also adjust their speech in response to auditory perturbations [55] . For example , when the first vowel formant ( F1 ) is artificially shifted upwards , speakers produce within-utterance compensatory responses by lowering their produced F1 . The magnitude of these responses only partially compensates for the perturbation , unlike the complete responses produced for mechanical perturbations . While the exact reason for this partial compensation is not known , it has been hypothesized to relate to small feedback gains [19] or conflict with the somatosensory feedback system [14] . We explore the cause of this partial compensation below , but focus here on the ability of the model to replicate the observed behavior . To test the ability of the FACTS model to reproduce the observed partial responses to auditory feedback perturbations , we simulated production of a steady-state [ǝ] vowel . After a brief stabilization period , we abruptly introduced a +100 Hz perturbation of F1 by adding 100 Hz to the perceived F1 signal in the auditory processing stage . This introduced a discrepancy between the produced F1 ( shown in black in Fig 6B ) and the perceived F1 ( shown in blue in Fig 6B ) . Upon introduction of the perturbation , the model starts to produce a compensatory lowering of F1 , eventually reaching a steady value below the unperturbed production . This compensation , like the response in human speakers , is only partial ( roughly 20 Hz or 15% of the total perturbation ) . Importantly , FACTS produces compensation for auditory perturbations despite having no auditory targets in the current model . Previously , such compensation has been seen as evidence in favor of the existence of auditory targets for speech [14] . In FACTS , auditory perturbations cause a change in the estimated state of the vocal tract on which the task-level and articulatory-level feedback controllers operate . This causes a change in motor behavior compared to the unperturbed condition , resulting in what appears to be compensation for the auditory perturbation . Our model results thus show that this compensation is possible without explicit auditory goals . Of course , these results do not argue that auditory goals do not exist . Rather , we show that they are not necessary for this particular behavior . The amount of compensation to an auditory perturbation has been found to vary substantially between individuals [55] . One explanation for the inter-individual variability is that the degree of compensation is related to the acuity of the auditory system . Indeed , some studies have found a relationship between magnitude of the compensatory response to auditory perturbation of vowel formants and auditory acuity for vowel formants [56] or other auditory parameters [57] . This point is not uncontroversial , however , as this relationship is not always present and the potential link between somatosensory acuity and response magnitude has not been established [58] . If we assume that acuity is inversely related to the amount of noise in the sensory system , this explanation fits with the UKF implementation of the state estimation procedure in FACTS , where the weight assigned to the auditory error is ultimately related to the estimate of the noise in the auditory system . In Fig 7B , we show that by varying the amount of noise in the auditory system ( along with the internal estimate of that noise ) , we can drive differences in the amount of compensation the model produces to a +100 Hz perturbation of F1 . When we double the auditory noise compared to baseline ( top ) , the compensatory response is reduced . When we halve the auditory noise ( bottom ) , the response increases . Interestingly , the math underlying the UKF suggests that the magnitude of the response to an auditory error should be tied not only to the acuity of the auditory system , but to the acuity of the somatosensory system as well . This is because the weights assigned by the Kalman filter take the full noise covariance of all sensory systems into account . We verified this prediction empirically by running a second set of simulated responses to the same +100 Hz perturbation of F1 , this time maintaining the level of auditory noise constant while varying only the level of somatosensory noise . The results can be seen in Fig 7C and 7D . When the level of somatosensory noise is increased , the response to the auditory perturbation increases . Conversely , when the level of somatosensory noise is reduced , the compensatory response is reduced as well . These results suggest that the compensatory response in human speakers should be related to the acuity of the somatosensory system as well as the auditory system , a hypothesis which we are currently testing experimentally . Broadly , however , these results agree with , and provide a testable hypothesis about the cause of , empirical findings that show a trading relationship across speakers in their response to auditory and somatosensory perturbations [59] .
The proposed FACTS model provides a novel way to understand the speech motor system . The model is an implementation of state feedback control that combines high-level control of speech tasks with a non-linear method for estimating the current articulatory state to drive speech motor behavior . We have shown that the model replicates many important characteristics of human speech motor behavior: the model produces stable articulatory behavior , but with some trial-to-trial variability . This variability increases when somatosensory information is unavailable , but is largely unaffected by the loss of auditory feedback . The model is also able to reproduce task-specific responses to external perturbations . For somatosensory perturbations , when a downward force is applied to the jaw during production of an oral consonant , there is an immediate task-specific compensatory response only in those articulators needed to produce the current task . This is seen in the increased movement of the upper and lower lips to compensate for the jaw perturbation during production of a bilabial /b/ but no alterations in lip movements when the jaw was perturbed during production of a tongue-tip consonant /d/ . The ability of the model to respond to perturbations in a task-specific manner replicates a critical aspect of human speech behavior and is due to the inclusion of the task state feedback control law in the model [35] . For auditory perturbations , we showed that FACTS is able to produce compensatory responses to external perturbations of F1 , even though there is no explicit auditory goal in the model . Rather , the auditory signal is used to inform the observer about the current state of the vocal tract articulators . We additionally showed that FACTS is able to produce the inter-individual variability in the magnitude of this compensatory response as well as the previously observed relationship between the magnitude of this response and auditory acuity . We have also shown that FACTS makes some predictions about the speech motor system that go beyond what has been demonstrated experimentally to date . FACTS predicts that a complete loss of sensory feedback would lead to large increases in articulatory variability beyond those seen in the absence of auditory or somatosensory feedback alone . Additionally , FACTS predicts that the magnitude of compensation for auditory perturbations should be related not only to auditory acuity , but to somatosensory acuity as well . These concrete predictions can be experimentally tested to assess the validity of the FACTS model , testing which is ongoing in our labs . It is important to note here that , while the FACTS model qualitatively replicates the patterns of variability seen in human movements when feedback is selectively blocked , alternative formulations of the model could potentially lead to a different pattern of results . In the current model , somatosensory and auditory feedback are combined to estimate the state of the speech articulators for low-level articulatory control . Given that somatosensory feedback is more directly informative about this state , it is perhaps unsurprising that removing auditory feedback results in smaller changes in production variability than removing somatosensory feedback . However , auditory feedback may be more directly informative about the task-level state , including cases where the task-level goals are articulatory [60] ( as in the current version of the model ) or , more obviously , where the task-level goals are themselves defined in the auditory dimension [19] . Indeed , a recent model for limb control has suggested that task-level sensory feedback ( vision ) is incorporated into a task-level state estimator , rather than being directly integrated with somatosensory feedback in the articulatory controller [61] . A similar use of auditory feedback in the task-level state estimator in FACTS , rather than in the articulatory-level estimator in the current version , may produce different patterns of variability when sensory feedback is blocked . We are currently working on developing such an alternative model to address this issue . The current version of FACTS uses constriction targets as the goals for task-level control . There are a few considerations regarding this modelling choice that warrant some discussion . First , the ultimate goal of speech production in any theory , at an abstract level , must be to communicate a linguistic message through acoustics . Additionally , all speech movements will necessarily have deterministic acoustic consequences . However , this does not imply that auditory goals must be used at the level of control , which is implemented in FACTS based only on constriction targets . Second , the current results should not be taken as arguing against the existence of auditory goals . Indeed , we believe that auditory goals may play an important role in speech production . While we have shown that auditory targets are not necessary for compensation to acoustic perturbations , they may well be necessary to explain other behaviors [14 , 62] . Future work can test the ability of FACTS to explain these behaviors . Lastly , while the architecture of FACTS is compatible with auditory goals at the task level , the results of the current model may depend on the choice of task-level targets . Again , future work is planned to explore this issue . One of the major drawbacks of the current implementation of FACTS is that the model of the plant only requires kinematic control of articulatory positions . While a kinematic approach is relatively widespread in the speech motor control field–including both DIVA and Task Dynamics–there is experimental evidence that the dynamic properties of the articulators , such as gravity and tissue elasticity , need to be accounted for [63–66] . Moreover , speakers will learn to compensate for perturbations of jaw protrusion that are dependent on jaw velocity [59 , 67–69] , indicating that speakers are able to generate motor commands that anticipate and cancel out the effects of those altered articulatory dynamics . While the FACTS model in its current implementation does not replicate this dynamical control of the speech articulators , the overall architecture of the model is compatible with control of dynamics rather than just kinematics [23] . Control of articulatory dynamics would require a dynamic model of the plant and the implementation of a new articulatory-level feedback control law that would output motor commands as forces , rather than ( or potentially in addition to ) articulatory accelerations . Coupled with parallel changes to the articulatory state prediction process , this would allow for FACTS to control a dynamical plant without any changes to the overall architecture of the model . Another limitation of the current FACTS model is that it does not incorporate sensory delays in any way . Sensory delays are non-neglibile in speech ( roughly 30-50 ms for somatosensation and 80-120 ms for audition [19] ) . We are currently exploring methods to incorporate these delays into the model . One potential avenue is to use an extended state representation , where the state ( articulatory and/or task ) is represented as a matrix where each column represents a time sample [70] . Interestingly , this approach has shown that shorter-latency signals are assigned higher weights in the Kalman gain , even when they are inherently more noisy . This suggests another potential reason for why the speech system may rely more on somatosensation for online control than audition , since its latency is much shorter . While a detailed discussion of the neural basis of the computations in FACTS is beyond the scope of the current paper , in order to demonstrate the plausibility of FACTS as a neural model of speech motor control , we briefly touch on potential neural substrates that may underlie a state-feedback control architecture in speech [23 , 24 , 27] . The cerebellum is widely considered to play a critical role as an internal forward model to predict future articulatory and sensory states [26 , 71] . The process of state estimation may occur in the parietal cortex [24] , and indeed inhibitory stimulation of the inferior parietal cortex with transcranial magnetic stimulation impairs sensorimotor learning in speech [72] , consistent with a role in this process . However , state estimation for speech may also ( or alternatively ) reside in the ventral premotor cortex ( vPMC ) for speech , where the premotor cortices are well situated for integrating sensory information ( received from sensory corteces via the arcuate fasiculus and the superior longitudinal fasiculus ) with motor efference copy from primary motor cortex and cerebellum [27] . Another possible role for the vPMC might be in implementing the task state feedback control law [61] . Primary motor cortex ( M1 ) , with its descending control of the vocal tract musculature and bidirectional monosynaptic connections to primary sensory cortex , is the likely location of the articulatory feedback control law , converting task-level commands from vPMC to articulatory motor commands . Importantly , the differential contributions of vPMC and M1 observed in the movement control literature is consistent with the hierarchical division of task and articulatory control into two distinct levels as specified in FACTS . Interestingly , recent work using electrocorticography has shown that areas in M1 code activation of task-specific muscle synergies similar to those proposed in Task Dynamics and FACTS [73] . This suggests that articulatory control may rely on muscle synergies or motor primitives , rather than the control of individual articulators or muscles [74] . We have currently implemented the state estimation process in FACTS as an Unscented Kalman Filter . We intend this to be purely a mathematically tractable approximation of the actual neural computational process . Interestingly , recent work suggests that a related approach to nonlinear Bayesian estimation , the Neural Particle Filter , may provide a more neurobiologically plausible basis for the state estimation process [75] . Our future extensions of FACTS will involve exploring implementing this type of filter . In conclusion , the FACTS model uses a widely accepted domain-general approach to motor control , is able to replicate many important speech behaviors , and makes new predictions that can be experimentally tested . This model pushes forward our knowledge of the human speech motor control system , and we plan to further develop the model to incorporate other aspects of speech motor behavior , such as pitch control and sensorimotor learning , in future work .
We use the following mathematical notation to present the analyses described in this paper . Matrices are represented by bold uppercase letters ( e . g . , X ) , while vectors are represented in italics without any bold case ( either upper or lower case ) . We use the notation XT to denote the matrix transpose of X . Concatenations of vectors are represented using bold lowercase letters ( e . g . , x = [x ẋ]T ) . Scalar quantities are represented without bold and italics . Derivatives and estimates of vectors are represented with dot and tilde superscripts , respectively ( i . e . , ẋ and x ˜ , respectively ) . In FACTS , we represent the state of the vocal tract tasks xt = [xt ẋt]t at time t by a set of constriction task variables xt ( given the current gestural implementation of speech tasks , this is a set of constriction degrees such as lip aperture , tongue tip constriction degree , velic aperture , etc . and constriction locations , such as tongue tip constriction location ) and their velocities ẋt . Given a gestural score generated using a linguistic gestural model [76 , 77] , the task state feedback control law ( equivalent to the Forward Task Dynamics model in [32] ) allows us to generate the dynamical evolution of xt using the following simple second-order critically-damped differential equation: x ¨ t = M - 1 ( - B x ˙ ˜ t - C ( x ˜ t - x 0 ) ) ( 1 ) where x0 is the active task ( or gestural ) goal , M , B , and C are respectively the mass matrix , damping coefficient matrix , and stiffness coefficient matrix of the second-order dynamical system model . Essentially , the output of the task feedback controller , ẍt , can be seen as a desired change ( or command ) in task space . This is passed to the articulatory state feedback control law to generate appropriate motor commands that will move the plant to achieve the desired task-level change . Although the model does include a dynamical formulation of the evolution of speech tasks ( following [32 , 35] ) , this is not intended to model the dynamics of the vocal tract plant itself . Rather , the individual speech tasks are modelled as ( abstract ) dynamical systems . The desired task-level state change generated by the task feedback control law , ẍt , is passed to an articulatory feedback control law . In our implementation of this control law , we use Eq 2 ( after [32] ) to perform an inverse kinematics mapping from the task accelerations ẍt to the model articulator accelerations ät , a process which is also dependent on the current estimate of the articulator positions ãt and velocities a ˙ ˜ t . J ( ã ) is the Jacobian matrix of the forward kinematics model relating changes in articulatory states to changes in task states , J ˙ ( a ˜ , a ˙ ˜ ) is the result of differentiating the elements of J ( ã ) with respect to time , and J ( ã ) * is a weighted Jacobian pseudoinverse of J ( ã ) . a ¨ t = J ( a ˜ t ) * x ¨ t - J ( a ˜ t ) * J ˙ ( a ˜ t , a ˙ ˜ t ) a ˙ ˜ t ( 2 ) In order to generate articulatory movements in CASY , we use Runge-Kutta integration to combine the previous articulatory state of the plant ( [at−1 ȧt−1]T ) with the output of the inverse kinematics computation ( ät−1 , the input to the plant , which we refer to as the motor command ) . This allows us to compute the model articulator positions and velocities for the next time-step ( [at ȧt]T ) , which effectively “moves” the articulatory vocal tract model . Then , a tube-based synthesis model converts the model articulator and constriction task values into the output acoustics ( parameterized by the vector y t a u d ) . In order to model noise in the neural system , zero-mean Gaussian white noise ε is added to the motor command ( ät−1 ) received by the plant as well as to the somatosensory ( y t s o m a t ) and auditory ( y t a u d ) signals passed from the plant to the articulatory state estimator . Currently , noise levels ( standard deviation of Gaussian noise ) are tuned by hand for each of these signals ( see below for details ) . Together , the CASY model and the acoustic synthesis process constitute the plant . The model vocal tract in the current implementation of the FACTS model is the Haskins Configurable Articulatory Synthesizer ( or CASY ) [41–43] . The articulatory state estimator generates an estimate of the articulatory state of the plant needed to generate state-dependent motor commands . The final state estimate ( ât ) generated by the observer is a combination of an articulatory state prediction ( ãt ) generated from an efference copy of outgoing motor commands , combined with information about the state of the plant derived from the somatosensory and auditory systems ( yt ) . This combination of internal prediction and sensory information is accomplished through the use of an Unscented Kalman Filter ( UKF ) [36] , which extends the linear Kalman Filter [28] used in most non-speech motor control models [23 , 25] to nonlinear systems like the speech production system . First , the state prediction is generated using a forward model ( F ) that predicts the evolution of the plant based on an estimate of the previous state of the plant ( ãt−1 ) and an efference copy of the previously issued motor command ( ät−1 ) . Based on this predicted state , another forward model ( H ) generates the predicted sensory output y ^ t = [ y ^ t s o m a t y ^ t a u d ] T ( comprising somatosensory and auditory signals y ^ t s o m a t and y ^ t a u d , respectively ) that would be generated by the plant in the predicted state . Currently , auditory signals are modelled as the first three formant values ( F1-F3; 3 dimensions ) , and somatosensory signals are modelled as the position and velocities of the speech articulators in the CASY model ( 20 dimensions ) . a ^ t= F ( a ˜ t - 1 , a ¨ t - 1 ) ( 3 ) y ^ t= [ H s o m a t ( a ^ t s o m a t ) H a u d ( a ^ t a u d ) ] ( 4 ) These predicted sensory signals are then compared with the incoming signals from the somatosensory ( y t s o m a t ) and auditory ( y t a u d ) systems , generating the sensory prediction error ( comprising both somatosensory and auditory components ) Δ y t = [ Δ y t s o m a t Δ y t a u d ] T: Δ y t a u d= y ^ t a u d - y t a u d ( 5 ) Δ y t s o m a t= y ^ t s o m a t - y t s o m a t ( 6 ) These sensory prediction errors are used to correct the initial articulatory state prediction , giving a final articulatory state estimate ãt: a ˜ t = a ^ t + K t Δ y t ( 7 ) where K t is the Kalman Gain , which effectively specifies the weights given to the sensory signals in informing the final state estimate . Details of how we generate F , H , and K are given in the following sections . Finally , we estimate the vocal tract state estimate at the next time step by passing the articulatory state estimate into a task state estimator , which in our current implementation is a forward kinematics model ( see Eq 2 ) [32] . J ( ã ) , the Jacobian matrix relating changes in articulatory states to changes in task states , is the same as in Eq 2 . x ˜ t= f ( a ˜ t ) ( 17 ) x ˙ ˜ t= J ( a ˜ t ) a ˙ ˜ t ( 18 ) This task state estimate is then passed to the task feedback controller to generate the next task-level command ẍt using Eq 1 . There are a number of tunable parameters in the FACTS model . These include: 1 ) the noise added to ä in the plant , yaud in the auditory system , and ysomat in the somatosensory system; 2 ) the internal estimates of the process ( ä ) and observation y noise; and 3 ) initial values for the process , observation , and state covariance matrices used in the Unscented Kalman Filter . Internal estimates of the process and observation noise were set to be equal to the true noise levels . Noise levels were selected from a range from 1e-1 to 1e-8 , scaled by the norm of each signal ( equivalent to a SNR range of 10 to 1e8 ) , to achieve the following goals: 1 ) stable system behavior in the absence of external perturbations , 2 ) the ability of the model to react to external auditory and somatosensory perturbations , 3 ) and a partial compensation for external auditory perturbations in line with observed human behavior . The final noise values used were 1e-4 for the plant/process noise , 1e-2 for the auditory noise , and 1e-6 for the somatosensory noise . The discrepancy in the values for the noise between the two sensory domains is proportional to the difference in magnitude between the two signals ( 300-3100 Hz for the auditory signal , 0-1 . 2 mm or mm/s for the articulatory position and velocity signals ) . Process and observation covariance matrices were initialized as identity matrices scaled by the process and observation noise , respectively . The state covariance matrix was initialized as an identity matrix scaled by 1e-2 . A relatively wide range of noise values produced similar behavior: the effects of changing the auditory and somatosensory noise levels are discussed in the results section .
|
Speaking is one of the most complex motor tasks humans perform , but it’s neural and computational bases are not well understood . We present a new computational model that generates speech movements by comparing high-level language production goals with an internal estimate of the current state of the vocal tract . This model reproduces many key human behaviors , including making appropriate responses to multiple types of external perturbations to sensory feedback , and makes a number of novel predictions about the speech motor system . These results have implications for our understanding of healthy speech as well as speech impairments caused by neurological disorders . They also suggest that the mechanisms of control are shared between speech and other motor domains .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"somatosensory",
"system",
"acoustics",
"linguistics",
"medicine",
"and",
"health",
"sciences",
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"and",
"technology",
"signal",
"processing",
"social",
"sciences",
"neuroscience",
"control",
"engineering",
"systems",
"science",
"mathematics",
"tongue",
"digestive",
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"sensory",
"physiology",
"computer",
"and",
"information",
"sciences",
"behavior",
"head",
"speech",
"physics",
"psychology",
"speech",
"signal",
"processing",
"mouth",
"anatomy",
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"acoustic",
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] |
2019
|
The FACTS model of speech motor control: Fusing state estimation and task-based control
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Chagas disease is a serious public health problem in Latin America where about ten million individuals show Trypanosoma cruzi infection . Despite significant success in controlling domiciliated triatomines , sylvatic populations frequently infest houses after insecticide treatment which hampers long term control prospects in vast geographical areas where vectorial transmission is endemic . As a key issue , the spatio-temporal dynamics of sylvatic populations is likely influenced by landscape yet evidence showing this effect is rare . The aim of this work is to examine the role of land cover changes in sylvatic triatomine ecology , based on an exhaustive field survey of pathogens , vectors , hosts , and microhabitat characteristics' dynamics . The study was performed in agricultural landscapes of coastal Ecuador as a study model . Over one year , a spatially-randomized sampling design ( 490 collection points ) allowed quantifying triatomine densities in natural , cultivated and domestic habitats . We also assessed infection of the bugs with trypanosomes , documented their microhabitats and potential hosts , and recorded changes in landscape characteristics . In total we collected 886 individuals , mainly represented by nymphal stages of one triatomine species Rhodnius ecuadoriensis . As main results , we found that 1 ) sylvatic triatomines had very high T . cruzi infection rates ( 71% ) and 2 ) densities of T . cruzi-infected sylvatic triatomines varied predictably over time due to changes in land cover and occurrence of associated rodent hosts . We propose a framework for identifying the factors affecting the yearly distribution of sylvatic T . cruzi vectors . Beyond providing key basic information for the control of human habitat colonization by sylvatic vector populations , our framework highlights the importance of both environmental and sociological factors in shaping the spatio-temporal population dynamics of triatomines . A better understanding of the dynamics of such socio-ecological systems is a crucial , yet poorly considered , issue for the long-term control of Chagas disease .
Chagas disease is a vector-borne disease caused by a flagellated protozoan parasite ( Trypanosoma cruzi ) that affects approximately 10 million people in Latin America and the Caribbean region [1] , with an increasing number of cases reported in non-endemic countries [2] . The vectors are blood-sucking reduviid bugs of the subfamily Triatominae , of which 70 of the over 140 Triatominae species described [3] , [4] have been found to be naturally infected with T . cruzi [5] . Originally restricted to sylvatic habitats , Chagas disease began to present a risk to human health as its vectors acquired the ability to colonize and sustain populations in human dwellings , resulting in the domiciliary transmission of T . cruzi [6] . In addition to domiciliated species , there is increasing evidence from several countries ( e . g . , Bolivia [7] , Ecuador [8] , [9] , Brazil [4] , Argentina [10] ) that some sylvatic individuals frequently colonize human habitats and may play a key role in the transmission cycle of T . cruzi . Moreover , recent studies conducted in Ecuador indicate that house infestation , likely originating from sylvatic areas , limits the effectiveness of insecticide-based control interventions [11] . To improve our understanding of the colonization and domiciliation processes , monitoring and understanding the dynamics of sylvatic species/individuals that may colonize anthropogenic habitats has therefore become a cornerstone issue in Chagas disease research field [3] . The temporal and spatial dynamics of vector populations in sylvatic habitats is strongly influenced by the structure of the landscape and its evolution ( either under natural or anthropogenic drivers ) through time [12]–[14] . For example , in the Pantanal region of Brazil , changes in vegetation cover according to variations in multi-year flooding intensity strongly affect the availability of habitats occupied by rodent hosts , resulting in complex trypanosome transmission cycles [15] . Consequently , land cover modifications ( e . g . ranching extension , deforestation ) may affect the role that small mammals play in the transmission cycle of trypanosomes [16] . More generally , anthropogenic and natural habitat modifications increase the contact between wildlife and domestic animals , or vectors and hosts , and modify the epidemiological profiles of transmission cycles , with potential consequences on disease emergence or re-emergence patterns [17] . Moreover , the transmissibility pathways of multiple host parasites , as it is the case for T . cruzi , may change according to any factor affecting the population dynamics of their hosts [16] . Monitoring the sylvatic transmission cycles of these trypanosomatids is therefore necessary to prevent re-emergence of Chagas disease . The objective of this work was to assess whether temporal changes in land cover characteristics may affect the spatial distribution and host association of T . cruzi vectors . The study was performed in agricultural landscapes of coastal Ecuador as a study model . In this country , around 3 . 8 million people are at risk of acquiring Chagas disease and some 200 , 000 individuals are currently infected with the disease , making it a serious public health issue [18] . Over one year , we sampled triatomine individuals in natural ( forest or shrub ) , cultivated and domestic habitats; assessed their infection with trypanosomes; and recorded changes in landscape characteristics . As the distribution of sylvatic triatomine species has been found to be related to the presence of rodent hosts ( mainly mice , rats and squirrels [8] ) themselves influenced by vegetation type and cover , we hypothesized that temporal land cover changes partly related to the crop production cycle ( planting , harvesting , absence of crop ) may affect the presence of rodent hosts and consequently that of associated triatomines .
We obtained informed consent from the head of the household following protocols approved by the institutional review boards of Ohio University and Catholic University of Ecuador ( PUCE ) . Our study was conducted in the rural community of El Bejuco located in Portoviejo County , Manabí Province ( 0°57′37 . 80″S; 80°14′0 . 51″W ) in northwestern Ecuador . This community was chosen for the high triatomine baseline and post-insecticide spraying household infestation [11] and the presence of a landscape composed of both natural and cultivated areas . This community comprised 98 houses with an approximate number of 450 inhabitants . Most houses are constructed with bamboo walls , concrete bricks and timber with roofs made of corrugated metal sheets or Phytelephas aequatorialis Spruce palm leaves [19] . The peridomestic areas contained dogs , chickens , pigs and cows dwelling among firewood piles and trees [11] . Average monthly temperatures range from 18 . 7 to 30 . 8°C with a mean value of 24 . 8°C . The precipitation regime is characterized by two main seasons: 1 ) a rainy season ( total precipitation = 779 mm ) between January and April and 2 ) a dry season ( total precipitations = 26 mm ) between July and October ( data from the WorldClim data set ) . The average relative humidity ranges between 90 and 97% over the year [8] . Our sampling area in the community was defined as a 1000 m×600 m quadrat located along the main road of the village ( Figure 1 ) . This quadrat included the different environments found in the community ( synanthropic [defined as peridomestic and domestic habitats] , cultivated areas [crops] , and natural vegetation [forest or shrub] ) . Sampling was performed on seven visits from June 2009 to June 2010 , with intervals of two months between visits . Two visits ( February and April ) were performed during the rainy season , two ( August and October ) during the dry season , and three ( June and December 2009 , and June 2010 ) during the transition periods . Triatomine sampling in synanthropic environments ( 12 houses located in the sampling area ) was conducted on every visit by a three-person team using standardized protocols during timed manual collections as previously described [20] . If at least one live triatomine was found in a domestic unit ( DU ) , this house was classified as being infested and was sprayed by trained field workers from the Ministry of Health with deltamethrin at a rate of 25 mg a . i per m2 as previously described [11] . Spraying included all structures found in the domicile and peridomicile and were supervised by staff from PUCE . Houses found to be not-infested were not sprayed . Sylvatic populations of triatomines ( defined as populations sampled in both cultivated and natural vegetation ) were sampled following the randomized sampling design developed by Suarez-Davalos et al . [8] . During each visit the coordinates of 70 points were randomly generated within the quadrat using the Spatstat package of R Software ( R Development Core Team 2012 ) . In the case that the distance between two points was <3 m , the whole randomization was rerun ( see [8] for more details ) . For all dates , the minimal distance between each collection point was 10 . 2 m . These coordinates were then transferred to a GPS receiver ( Meridian Platinum , Magellan , San Dimas , United States ) for field sampling . At each point , standard manual searches for triatomines were performed for 30 min by three-person teams in different microhabitats ( nests , burrows , tree holes , and under trunks and rocks ) within a three-meter radius area [21] . When palms were found within the sampling radius , manual searches were conducted by skilled personnel . Briefly , one skilled searcher used a ladder to perform the search from the base of the leaves . Manual searches for triatomines were carried out within the foliage . Any nest found was carefully extracted and dissected on a 2 m2 yellow plastic sheet placed at the base of the palm . Underground mammal burrows were searched by extracting all material found within placed onto a yellow plastic sheet . The total area sampled on each occasion was 1981 m2 . In each microhabitat , we recorded information regarding habitat type ( forest , shrub , or crop; see below ) , occurrence of vertebrate hosts ( identified to species level based on nest occurrence ) , and nest height from ground level . At each date , sampling lasted for 5 days , representing a total sampling effort of 840 person-hours for the whole study . About 50% of the total land cover of the studied community was composed of cultivated areas , mainly corn , papaya , and peanut crops . The rest of the landscape was vegetated with a lowland semideciduous forest composed of thorny plants and trees that lose their leaves once a year ( e . g . , Ceratonia siliqua L . 1858 and Guazuma ulmifolia Lam . 1789 ) [8] . In this region , there is only one harvest of short-cycle maize per year as there is not enough precipitation during the dry season and most farmers do not have irrigation facilities . Maize is generally planted during the rainy season and is harvested during the following transition period ( May–June ) . For the seven sampling periods , each of the 70 sampled points was assigned to a habitat type as follows: 1 ) forest , characterized by a high density of G . ulmifolia tree , 2 ) shrub , characterized by high density of Cordia lutea Lam . and 3 ) crops . While elaborated landscape analyses can be performed using indices describing the landscape based on the composition and disposition of its constituents [22] , we realized that , at our study scale , a simple characterization of land cover modification over the whole year at each of the 490 triatomine sampling points ( 70 sampling points×7 months ) and 12 houses was sufficient to describe the dynamics of this agricultural landscape [23] . Once collected , triatomines were placed in individually labeled plastic containers and transported to the Center for Infectious Disease Research ( PUCE , Quito ) where they were counted and identified to the species and instar level . Species identification was based on morphological criteria [24] , [25] and comparisons with pinned specimens of the PUCE's Entomology Museum ( QCAZ ) . The presence of T . cruzi-like organisms was determined by examination of the feces and intestinal content at ×400 magnification , using a direct light microscope and by PCR using S35/S36 and 121/122 primer sets [26] , [27] . Discrete typing units ( DTU ) were determined as described in Ocaña-Mayorga et al . [28] .
A total of 886 triatomine specimens were collected over the seven sampling dates . Ninety nine percent of all collected specimens were Rhodnius ecuadoriensis Lent & León , 1958 . The remaining five specimens were Panstrongylus howardi Neiva 1911 ( 3 individuals ) collected in a squirrel nest in June 2009 , one , P . geniculatus Latreille 1811 ( 1 individual ) collected in the peridomicile in June 2009 and one P . rufotuberculatus collected in a squirrel nest in December 2009 . Of the 886 specimens , 69% were collected in sylvatic habitats . As a general pattern , we collected a high number of first instar nymphs but few adults of R . ecuadoriensis in both sylvatic and synanthropic habitats . The majority ( 78 . 1% ) of sylvatic triatomines were found in animal nests . These nests were either of squirrel ( Sciurus stramineus Eydoux & Souleyet 1841 , 83 . 1% ) , mouse/rat ( 10 . 9% e . g Sigmodon sp , Proechimys sp , Rhipidomys sp , Mus musculus L . , ) , bird ( 4 . 9% , e . g . , Campylorhynchus fasciatus Swainson 1837 ) or other species ( e . g . , the opossum Didelphis marsupialis L . 1858 , 1 . 1% ) . While triatomines were commonly found in squirrel nests all year round , they were associated with mouse/rat nests mostly during the rainy and transition seasons . Triatomines were not found in an abandoned structure , which was the only bat habitat found within the quadrat . The infestation index ranged from 4 . 3% to 22 . 9% and 0% to 41 . 7% in sylvatic and synanthropic habitats , respectively ( Table 1 ) . The density index was generally lower in sylvatic than synanthropic habitats ( except in April and June 2010 ) while the crowding index greatly varied among dates in both habitats . Colonization indices were always >85% in both habitats ( except in December , April and June in houses ) . As a general pattern , the value of the three first entomological indices tended to be low for the last sampling dates ( February to June 2010 ) . This tendency was consistent with lower triatomine abundances and number of infested points found at the end of the sampling period ( see Figure 2 ) . Overall , half of the 12 sampled houses presented triatomine infestation at least once during the year-long survey . Of those , five houses had multiple infestations at different time points ( Table S1 ) . Overall , triatomine abundance was highly variable among collection points at a given date ( see Figure 2 ) , resulting in the observed aggregated pattern of triatomine spatial distribution ( Figure 3 ) . Interestingly , these “hotspots” of triatomine density were located both nearby ( <50 m ) and relatively far ( >200 m ) from the houses . Infections with Trypanosoma spp were detected by PCR in 90% of the 105 sylvatic triatomines analyzed . Infections with T . cruzi were the most common ( 71% ) followed by infections with T . rangeli ( 15% ) and mixed infections T . cruzi/T . rangeli ( 4 cases , 4% ) . Infection rates were lower for individuals sampled in houses ( 60% , N = 55 ) with a large predominance of T . cruzi infections ( 58% ) , the remaining being infected by T . rangeli . The prevalence of triatomines' infection for each date and habitat is given in Figure 4 . Multivariate analyses ( MANOVA and CVA ) showed that the environmental spaces of T . cruzi-infected triatomines were significantly different among dates ( Wilks' k from MANOVA = 0 . 119; P<0 . 001 ) . The first canonical variate ( axis 1 ) , primarily associated with crop and mice , explained 64 . 7% of the variability among dates and clearly discriminated the environmental spaces from dry ( August–October ) to rainy season ( April; Figure 5 ) . The second canonical variate ( axis 2 , 23 . 7% ) was primarily associated with shrubs and tended to separate the transition season following the dry season ( December ) from the transition season following the rainy season ( June; Figure 5 ) . Note that May–June 2009 experienced unusually low precipitation , which explains the position of its environmental space together with August and October . Path analyses further suggested that rainfall significantly determined the abundance of T . cruzi-infected triatomines via indirect paths involving habitats and rodent hosts ( Figure 6 ) . Rainfall had a significantly positive and negative influence on crop and forest/shrub cover , respectively . In turn , these habitats significantly influence the occurrence of rodent hosts and thereby the abundance of T . cruzi-infected triatomines . Of the five factors included in the GLM analysis ( see Materials and Methods ) three of them , date , habitat , and host , significantly affected the abundance of infected triatomines with ‘habitat’ and ‘date’ showing the highest ΔAIC values ( Table 2 ) . Moreover , the significant ‘date×habitat’ interaction term revealed that changes in habitat structure over the year influenced significantly the abundance of infected triatomines . We also found a significant ‘date×vector’ interaction term which supports that changes in rodent host populations affect the distribution of T . cruzi-infected triatomine through time . Note that similar results were found when performing the analyses with all triatomine data ( infected and non-infected , Table S2 ) .
Our study reports that the species R . ecuadoriensis , the most important Chagas disease vector in coastal Ecuador , has well established T . cruzi-infected sylvatic populations all year round . Although the occurrence of these vectors in Ecuador is well known [8] , [34] , [38] , no detailed data on their temporal dynamics were available . Our findings confirm that the demographic structure of sylvatic R . ecuadoriensis population was dominated by nymphal stages over the year [8] and that aggregations occurred both in sylvatic habitats and closer to homes [8] , [39] . In agricultural landscapes such as coastal Ecuador , the impact of human activities through crop planting and deforestation can extend far beyond the close periphery of households , which may explain the presence of triatomine aggregation areas relatively far from populated areas [40] , [41] . As previously reported by [14] , these results emphasize the importance of sylvatic populations for the transmission cycle of T . cruzi . Currently there are no genetic markers available to conduct population genetic studies that compare populations of R . ecuadoriensis collected in houses and sylvatic environments . However , morphometric analyses using antennae sencilla and wing geometry failed to detect significant differences between these populations [42] . As found in other studies ( e . g . , Mexico [23] , USA [43] ) , triatomines were strongly associated with squirrels which probably represent one of the most important host species [21] , [34] . The relatively large body size of squirrels and the characteristics of their nests ( large , 30 cm diameter , loose construction , and usually located at >5 m from the ground ) could improve food source availability and protection for triatomines [8] . The spatio-temporal dynamics of triatomine bugs in our study area was therefore highly influenced by variations in the occurrence of squirrels over the year and their distribution among the different habitat types ( see below ) . These results confirm a previous study by Gottdenker et al . [12] , [13] who found that changing host community structure following anthropogenic landscape disturbance in Panama may increase vector infection with T . cruzi . These authors further showed the importance of host reproductive rates as an important determinant of vector infection , suggesting that further research on rodent host life history in coastal Ecuador would be needed to improve our knowledge on T . cruzi epidemiology . Several studies have been performed to characterize and correlate sylvatic and synanthropic habitats with triatomine presence/absence using environmental parameters such as climate and topography [44] , [45] , associations with mammal hosts [16] , [46] , birds and palm trees [9] , [47]; ( Grijalva unpublished data ) , or specific land-cover types [48] . As revealed by previous studies from other parts of Latin America [12]–[16] , the spatio-temporal distribution cycle of R . ecuadoriensis in coastal Ecuador comes as a result of a combination of multiple ecological factors . Because climatic conditions of the Ecuadorian Coast are favorable for triatomine development all year round ( all months are moist and warm ) , land cover features represent the key variables that shape the population dynamics of T . cruzi vectors on a local scale [8] . Moreover , in view of the importance of agricultural activities in coastal Ecuador , land cover patterns and dynamics are likely influenced by land use practices of rural communities [11] . Our quantitative results from both the MANOVA-CVA , the path analysis and the GLM analyses ( themselves based on an extensive sampling of 886 triatomine individuals and associated micro-environmental parameters over one year ) strongly suggest that variations in land cover over one year , and subsequent effect on the distribution of rodent hosts , drive R . ecuadoriensis population dynamics in coastal Ecuador . While , for logistical reasons , our sampling was limited to one year in one location , results found are in agreement with other studies performed by our team over the last 10 years in other regions of Ecuador at different periods of the year ( e . g . [8] , [11] , [20] , [34] , [38] ) , reinforcing their general relevance . Based on this accumulated knowledge , we propose a schematic framework identifying the factors affecting the distribution of sylvatic T . cruzi vectors over one year ( Figure 7 ) . During the rainy season ( January–April ) , triatomines are mainly associated with squirrels whose nests are abundant in leafy bushes , hidden from predators . Some triatomines are also found in mouse nests in growing crops . A few months later , crops mature and food availability increases the association of triatomine with mice/rats , which become important hosts for them . During the dry season ( July–October ) triatomines mainly colonize squirrel nests located in trees . As many tree and shrub species lose their leaves at this season , it may be more secure for squirrels to nest high in the trees , generally >5 m , [8] than in shrubs . Finally , during the transition period that follows the dry season , triatomines are only found at low densities in squirrel nests associated with tree and leafing bushes . This season seems to be the most critical for the survival of sylvatic triatomines due to poor resource conditions in term of both habitat and hosts . Overall , land cover changes due to both farming activities and vegetation phenology affect rodent host distribution and , consequently , that of triatomines . Such findings extend to agricultural systems the results of previous studies in forested habitats that have shown that the composition and relative abundance of small mammal fauna involved in the transmission cycle of Chagas disease can be influenced by landscape structure and its changes over the year [16] . Still , causal mechanisms that link triatomine abundance to seasonal environmental changes are poorly understood due to the difficulty in performing large-scale landscape manipulation experiments and evaluating contributions from direct and indirect factors that can have opposing effects on triatomine populations [13] . However , our path analysis helped to stress the importance of indirect effects from field data . The triatomine population studied here clearly responded primarily to local habitat and host availability changes , which were changing over the year due to differences in precipitation . Additional work is needed to fully understand the epidemiological cycle of T . cruzi in changing landscapes . Our path analysis suggests individual hypotheses that can be tested experimentally or further investigated with more detailed observations as each arrow or path identifies a putative causal relationship between the triatomine populations and seasonality-driven environmental aspects . The burden of endemic neglected zoonoses generally falls heavily on rural communities with limited resources . In Ecuador , rural communities with subsistence-farming practices are high-risk areas for acquiring Chagas disease [20] . As control of Chagas disease should rely on the interruption of parasite transmission to domestic hosts [8] , a sound understanding of infection risk factors in both sylvatic and synanthropic vector populations is needed to effectively assist the development of effective prevention programs [49] . In this context , the results of this study have three major implications . First , our study emphasizes the importance of sylvatic triatomine populations as a main component of the transmission cycle of T . cruzi . While insecticide spraying in houses have allowed the control of domestic individuals ( see Figure 2 ) , numerous sylvatic individuals remain in the vicinity of households , which constitute a potential source of vectors for re-colonization [11] . Second , while there is a decline in the number of individuals over time , our results corroborate the previously reported low effectiveness of deltamethrin and suggest a short lasting residual effect of deltamethrin in the environmental conditions of coastal Ecuador . This has been observed in other areas such as the Chaco region [50] . Third , our findings highlight the importance of both environmental and sociological ( farming practices ) factors in shaping the spatio-temporal population dynamics of T . cruzi vectors . We propose that further research on T . cruzi transmission cycles should follow a social-ecological approach ( e . g . using methods developed for the study of socio-ecological systems , such as agent-based models , [51] ) , in which the coupling of human and natural systems would reveal the complex patterns and processes emerging from their interactions [52] . For example , if farming communities of coastal Ecuador would develop irrigation to support cultivation of maize during the dry season , this may have an impact on the sylvatic triatomine cycle through an increase of mouse/rat and squirrel occurrence during the dry and following transition seasons . However , two maize harvests per year would boost farmers' income and probably improve their living conditions , thereby decreasing their vulnerability to Chagas disease [1] and potentially reducing T . cruzi transmission [53] . Indeed , even low cost home improvements that limit areas of vector refuge in nearby houses can be highly effective at keeping infestation low [54] . Understanding such complex effects of land use changes on T . cruzi transmission and overall potential negative and/or positive feedback between farming practices , habitat availability , hosts and vectors would provide crucial , yet poorly considered , information with strong implications for vector surveillance and control .
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Globally , more than 10 million people are infected with Trypanosoma cruzi . The emergence and perpetuation of Chagas disease in some endemic countries , such as Ecuador , depends largely on sylvatic populations of T . cruzi-infected vectors that frequently infest houses after insecticide treatment thereby hampering long-term control prospects in vast geographical areas . Our study describes , for the first time in an agricultural landscape , how the temporal dynamics of sylvatic vector , host , and pathogen populations interact spatially in a farming community of coastal Ecuador . In particular , we found that land cover changes due to both farming activities and vegetation phenology affect rodent host distribution and consequently the relative abundance of vectors involved in the transmission cycle of T . cruzi .
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2014
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Dynamics of Sylvatic Chagas Disease Vectors in Coastal Ecuador Is Driven by Changes in Land Cover
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The sleeping brain exhibits characteristic slow-wave activity which decays over the course of the night . This decay is thought to result from homeostatic synaptic downscaling . Transcranial electrical stimulation can entrain slow-wave oscillations ( SWO ) in the human electro-encephalogram ( EEG ) . A computational model of the underlying mechanism predicts that firing rates are predominantly increased during stimulation . Assuming that synaptic homeostasis is driven by average firing rates , we expected an acceleration of synaptic downscaling during stimulation , which is compensated by a reduced drive after stimulation . We show that 25 minutes of transcranial electrical stimulation , as predicted , reduced the decay of SWO in the remainder of the night . Anatomically accurate simulations of the field intensities on human cortex precisely matched the effect size in different EEG electrodes . Together these results suggest a mechanistic link between electrical stimulation and accelerated synaptic homeostasis in human sleep .
Human sleep is characterized by distinct sleep stages which can be readily identified in the electroencephalogram ( EEG ) . Of particular interest is the activity in the 0 . 5–4 Hz frequency band known as slow-wave activity ( SWA ) . The power of SWA increases following extended waking and decreases in power and spatial coherence throughout the night [1] , [2] . SWA activity is thought to reflect a homeostatic mechanism that regulates sleep [3] . These changes in power have been hypothesized to result from potentiation and downscaling of synaptic connections during wakefulness and sleep respectively [4]–[9] . Homeostatic plasticity refers to a physiological feedback mechanism that regulates average firing rates by altering synaptic strength: high firing rates lead to synaptic depression and low firing rates to potentiation [10] . A link between homeostatic plasticity and sleep homeostasis is supported by the parallels between firing rates and SWA: namely , extended waking results in increased cortical firing rates at the beginning of sleep , and firing rate decays again during sleep [11] . Here we consider slow-wave oscillations ( SWO , 0 . 5–1 Hz ) in the human EEG as a marker for sleep homeostasis and its modulation by transcranial electrical stimulation . We found that a relatively short 25 minutes of stimulation in humans during slow-wave sleep at the beginning of the night had a lasting effect on homeostatic decay of SWO in the hours following stimulation . The effects of transcranial electrical stimulation on brain activity have been the subject of intense investigation in the last decade [12] , [13] . A number of studies show specific enhancement in human cognitive performance including memory , language , computational , and executive function [14]–[17] . The mechanisms leading to the observed cognitive effects of weak electrical stimulation in human behavioral studies remain fundamentally unaddressed . The current mechanistic explanation is limited to the notion of neuronal excitability where function is “increased” or “decreased” by virtue of neuronal polarization with anodal or cathodal stimulation respectively . However , the basic physics of current flow calls this simple notion into question as cortical folding leads to varying polarity across cortex making the origins of polarity specific effects unclear [18] . Furthermore , while acute effects of uniform week electric fields are well characterized , including modulation of firing rates [19] , it is less clear how these acute effects translate into specific long term effects . We hypothesized that stimulation during slow-wave sleep alters neuronal firing rates , which would modulate homeostatic synaptic downscaling and thus alter the homeostatic decay of SWO . A multi-scale computational model makes this hypothesis explicit by linking the macroscopic domains of current flow in the entire head with the microscopic cellular effects of polarization . The model shows that network dynamics of SWA can rectify bi-directional polarization leading to an unidirectional increase of firing rates and synaptic downscaling . A number of predicted effects of stimulation on SWO are subsequently confirmed by the present human EEG sleep data . Specifically , the data confirmed the prediction of diminished SWO decay in the hours after stimulation , and the multi-scale model accurately predicted the effect sizes across multiple scalp electrodes . The ability to accelerate sleep homeostasis may have important practical implications given that SWA is widely considered to be a marker of the restorative power of sleep .
In a study on memory consolidation during sleep [14] Marshall et al . stimulated participants during the first period of slow-wave sleep with slow-oscillating unipolar stimulation ( 0 . 26 mA switched on and off at 0 . 75 Hz ) . Positive ( anodal ) electrodes were placed bilaterally over lateral prefrontal cortex and negative ( cathodal ) electrodes over left and right mastoids . EEG was recorded simultaneously from 11 electrodes ( Figures 1 . A . 1 , 1 . A . 2 ) . To characterize the long term effects of stimulation on slow-wave activity , we computed here for each participant the power-spectrum over the course of the night . Slow-wave activity ( 0 . 5 Hz–4 Hz ) is modulated in time as participants cycle through non-REM and REM sleep stages ( Figure 1 . B . 1 , average over 10 participants ) . Note that the EEG data were aligned based on sleep stages ( see Materials and Methods ) , and sleep-stage cycle-durations are fairly reproducible across subjects [14] , [20] . We estimated decay rates of power and coherence as a linear fit on a logarithmic scale ( dB ) , which corresponds to an exponential decay in time ( example traces in Figure S1 . A–B ) [21]–[23] . In the present data the homeostatic decay of power in the band of slow-wave oscillations ( 0 . 5 Hz–1 Hz ) amounted to −1 . 220 . 18 dB/hour ( mean sem , p-value = 0 . 0001 , N = 10 , Student's t-test , Figure 1 . B . 3 , analysis window of 4 . 5 h marked in black , see Materials and Methods ) . In addition to changes in power , the computational model , which will be presented in the following sections , predicted that the spatial coherence of SWO should also decay . The coherence-spectrum between electrode pairs was computed and averaged across all pairs ( Figure 1 . C . 1 , average over 10 participants ) . In the band of SWO , coherence decays at a rate of −0 . 700 . 12 dB/hour ( mean sem , p-value , N = 10 , Student's t-test , Figure 1 . C . 3 ) . The present measure of spatial coherence is normalized by power . Thus , its decay does not simply capture a decrease in power but reflects instead a break-up of large scale coherent oscillations over distant cortical areas consistent with recent recordings in humans [2] . Our hypothesis on homeostatic plasticity predicted that the decay of SWO should be altered by the transcranial slow-oscillating stimulation administered to participants for 25 minutes ( spectrograms in Figures 1 . B . 2 , 1 . C . 2 ) . Specifically , we expected a reduced rate of decay in both power and spatial coherence in the hours following stimulation . This prediction was confirmed by the present data: the post-stimulation decay rate for power averaged over all electrodes is reduced to −0 . 690 . 18 dB/hour ( N = 10 , paired shuffled statistics , p = 0 . 016 , Figure 1 . B . 3 ) and similarly , the rate of spatial coherence is reduced to −0 . 150 . 12 dB/hour ( N = 10 , p = 0 . 009 , Figure 1 . C . 3 ) . Significant differences in decay rate are found also when analyzing individual electrodes in isolation ( p-values corrected for false discovery rate are between 0 . 013 and 0 . 035 for all electrodes except F7 with p = 0 . 132 ) and the same is true for coherence ( p-values between 0 . 013 and 0 . 031 except T3 with p = 0 . 063 ) . The wider band of SWA ( 0 . 5–4 Hz ) yielded essentially the same results ( p0 . 05 ) . Changes in sleep structure are hard to assess from the average spectrogram in Figures 1 . B-0 . C . Previous analysis already dismissed possible changes in terms of time spent in different sleep stages during the 60 minutes after the stimulation or the whole night , nor were there differences in the number of sleep cycles [14] . In summary , as predicted , the decay of SWA , which is widely considered to be a marker of sleep homeostasis , is reduced in the hours following electrical stimulation . In the following section we make quantitative predictions of this phenomenon by detailing our hypothesis in the form of a multi-scale computational model . We include a finite-element model of the current flow in the brain as well as a network model for slow wave oscillations . To determine the expected effects of stimulation for this specific human experiment we first simulated the current flow in an anatomically accurate model of the head ( Figure 2 . A . 1 , see Materials and Methods ) . Electrodes were placed as in the human experiments and currents were monophasic ( ON/OFF ) . As a result of the typical folding of human cortex , different cortical regions experience electric fields of varying magnitudes and , more importantly , of opposing polarities ( blue and red in Figure 2 . A . 2 ) . Thus , neurons in adjacent cortical areas will experience opposing membrane polarizations ( Figure 2 . A . 3 ) . This finding is not unique to the specific electrode montage [18] . To examine the effect of differing stimulation polarities on SWO we developed a simple network model of UP/DOWN state transitions . Single-compartment excitatory and inhibitory spiking neurons were recursively connected and arranged on a 2D lattice ( 900 neurons , Figure 2 . B . 1 ) . The model reproduces slow-wave oscillations by virtue of an activity-dependent slow recovery variable in a fashion comparable to previous models of SWO [9] , [24]–[26] ( Figure 2 . B . 2 ) . The recovery variable acts to decrease neuronal excitability after periods of high activity ( UP-state ) and recovers after periods of quiescence ( DOWN-state ) . The parameters of the model were chosen to reproduce key features of SWO in humans , such as oscillation frequency and coherence time , and the firing rate of single neurons was adjusted to match animal in vitro data ( Figure 2 . B . 3 , see Materials and Methods ) . Note that network parameters were chosen here to reproduce the irregular slow-wave pattern typical of human EEG data ( i . e . short coherence times , see Materials and Methods ) . These contrast the very regular oscillations often measured in in-vitro preparations [26] , [27] which can be readily reproduced by the present model by increasing the strength of synaptic connections ( see Materials and Methods ) . The effects of weak-field stimulation were implemented as a weak current injection to pyramidal neurons . The specific model of field-to-neuron coupling was validated at multiple frequencies in terms of firing rates , spike timing and entrainment using rat hippocampal slice recordings [19] . The same modeling approach was also used to model acute entrainment of slow waves oscillations in cortical ferret slices [28] . Different areas of the network were subjected to depolarizing or hyperpolarizing fields corresponding to the mixed polarities of the macroscopic field distributions ( Figure 2 . B . 1 ) . We find that when the network is subjected to constant current stimulation , average firing rates during slow-wave oscillations were increased or decreased depending on the predominant stimulation polarity ( Figure 3 . A . 1 ) . However , when stimulation was turned on and off at the same rate as the slow-oscillations ( 0 . 75 Hz ) , firing rate was only increased ( Figure 3 . A . 2 ) . This remarkable rectification of field-effects on firing rate is the result of the entrainment of the slow-wave oscillation to the applied oscillating field as will be explained below . The network model suggests that weak oscillating stimulation can entrain SWO even for very low amplitude fields ( Figure S2 . A ) and that entrainment results from a modulation of the duration of the UP and DOWN state ( Figures S2 . B . 1-S2 . B . 2 ) . Entrainment , as previously reported [14] is confirmed here with the present analysis of EEG data ( Figure S2 . C . 1-C . 2 , Pz electrode , Rayleigh test , 5 trials per 13 subjects considered , p = 0 . 017 ) . Entrainment of UP/DOWN-state transitions for weak applied fields have also been reported in ferret slices [28] and spiking activity was also entrained in in vivo recordings in rat [29] . Neither study reported any long term effects of fields on SWO . For monophasic stimulation , as in the present study , entrainment occurs regardless of polarity , but does so with opposing phase for opposing polarities ( Figure 3 . A . 3 ) . In the case of depolarizing stimulation ( anodal with currents flowing into cortex ) , the ON period of stimulation aligns with the UP-state , while in the case of hyperpolarizing stimulation ( cathodal with currents flowing out of cortex ) , the ON period aligns with the DOWN-state ( Figure 3 . A . 4 ) . The depolarizing field during the UP-state can increase the firing rate of this active state . However , hyperpolarizing fields during the DOWN-state can not reduce firing rate as the network is already quiescent . Thus , while DC stimulation may lead to mixed effects on firing rate across space , applying slow-oscillating ON/OFF stimulation during SWO may rectify the effects of fields leading to an unidirectional increase in firing rate . In vivo animal experiments suggest that synapses undergo downscaling during sleep [5] and that this coincides with a reduction in firing rates [11] . This is consistent with homeostatic synaptic plasticity , which adapts synaptic strength so as to stabilize firing rate to a set level [30] . We implemented here a slow , activity-dependent negative feedback on excitatory synaptic strength . Given the relatively high firing rate of the UP-state , this leads to widespread synaptic downscaling ( green curve in Figure 3 . B . 1 ) , and in turn , to a decrease in the power of slow-wave oscillations in the course of time ( Figure 3 . B . 2 ) . Spatial coherence of slow-wave oscillations also decreased with time ( Figure 3 . B . 3 ) . Both results are consistent in direction and magnitude with the present human EEG data ( Figures 1 . B . 1 and 1 . C . 1 ) . We argued above that slow-oscillating stimulation leads to an acute increase of firing rate , even at the small field intensities expected on human cortex of less than 0 . 5 V/m . In the network model this increased firing rate caused faster synaptic downscaling ( Figure 3 . B . 1 , using a field magnitude of 0 . 31 V/m ) . With this accelerated downscaling during stimulation , at the end of stimulation , firing rates are reduced as compared to the sham condition . Thus , with a diminished drive for downscaling , in the hours after stimulation the rate of SWO decay was correspondingly reduced – in power as well as spatial coherence ( decays in Figures 3 . B . 2–3 . B . 3 and results in Figures 4 . A . 1–4 . A . 2 ) . In the human experiment acceleration during stimulation could not be measured directly because entrainment and stimulation artifact distort the endogenous EEG signal . Instead , we measured the slope of decay after stimulation ( Figures 1 . B . 3 and 1 . C . 3 ) . These measures matched the model predictions shown in Figures 4 . A . 1–4 . A . 2: the difference in the decay for power between the stimulation and sham conditions in the EEG data is dB/hour and dB/hour in the computational model; for spatial coherence the difference in decay rate is dB/hour and dB/hour respectively . To further test the link between stimulation and downscaling , we analyzed the effect size for each of the 11 recording sites . For the human experiment the rate of decay in power was determined for each electrode and averaged across subjects for the sham and stimulation conditions ( Figure 4 . B . 1–4 . B . 2 ) . We ran the model without stimulation using random synaptic weights and selected for each location a set of weights that approximately matched spatially the EEG sham condition in terms of their decay rate ( Figure 4 . B . 3 ) . We then applied stimulation to the model of each “location” using the intensity distribution of fields found in the FEM model in the vicinity of each electrode . We used the field intensity orthogonal to the cortical surface since cell polarization is approximately proportional to the field intensity in the main axis of pyramidal cells [31] . The average value of the electric field chosen was 0 . 93 V/m ( in this case the stimulation is depolarizing or hyperpolarizing for different locations of the network; see Materials and Methods ) . This resulted in a decay rate for each “location” as shown in Figure 4 . B . 4 . The spatial distribution is remarkably similar to the one observed in the human EEG . Indeed , the effect size of stimulation versus sham across electrodes was significantly correlated with the predicted values ( N = 11 electrodes , , p = 0 . 02 , Figure 4 . C ) . In summary , the model not only explained the systematic reduction in decay rate of SWO power after stimulation despite mixed polarity stimulation , but it also predicted the effect size in each location by considering the specific mix of polarities near each electrode .
Slow-wave activity has long been associated with the restorative function of sleep [32] and recovery from wakefulness [5] , [21] . EEG slow-wave oscillations reflect periodic transitions between UP and DOWN states broadly distributed over the cortex [33] and are thought to be involved in plastic mechanisms [34] . The power of SWA has been linked to learning; for instance , practice on a visuomotor task preceding sleep increases SWA and its strength correlates with task performance following sleep [6] , [8] . SWA is also hypothesized to play a crucial role in memory consolidation by virtue of its ability to group the activity of various brain rhythms [35] ( e . g . hippocampal ripples; [36] , [37] and thalamo-cortical spindles [38] . ) A predominant feature of SWA is its decay in the course of the night . Many investigators attribute this decay to homeostatic downscaling of synaptic strength [5] , [6] , [9] . In their view , synaptic connections that became stronger during wakefulness are reduced in magnitude during sleep . Consistent with homeostatic synaptic plasticity , this decrease coincides with a reduction in firing rates [11] . Homeostatic plasticity represents a negative feedback that adapts synaptic strength resulting in a steady level of neuronal activity [10] . Synaptic downscaling during sleep has been postulated to serve a number of important functions , such as maintaining computational efficiency of the brain by increasing the signal-to-noise ratio of synaptically decoded information [35]; allowing maximum storage efficiency while preventing hyperactivity [39]; and maintaining synaptic normalization [40] . The physiological substrate for the scaling of synaptic connections could be explained by considering that the levels of neuromodulators strongly differ from waking to NREM sleep , for example the concentrations of acetylcholine [41] , [42] and norepinephrine [43] are significantly altered . Alternatively , spike-timing dependent plasticity ( STDP ) during neuronal bursts in slow-wave sleep may favor synaptic depression [44] . Downscaling has also been proposed to results from bursts of activity leading to long-term-depression during NREM sleep [45] . Recent studies also point to a possible role of glial cells in determining synaptic scaling . [46] . We previously showed that slow-oscillating transcranial electrical stimulation can modify endogenous slow oscillatory activity on a short term basis [14] . The question for the present work was whether cortical homeostatic mechanisms are influenced by slowly oscillating transcranial stimulation . Anatomically accurate models of current-flow in transcranial stimulation estimate that the electric fields induced at the cortical level for a typical 2 mA stimulation are at most 1 V/m [18] . This may polarize a cell by no more than a fraction of a millivolt [31] , [47] . While these intensities seem very small , there are a number of in vitro and in vivo experiments explaining the basic mechanisms by which such low-amplitude electric fields may nevertheless acutely alter neuronal activity , both at the single cell [48] and at the network level [19] , [49]–[51] . In particular , it has already been shown , both experimentally and using computational models [19] , [28] , that the effects resulting from the modest membrane polarization of isolated neurons are significantly amplified on the network level due to the dynamic nature of network activity . This can result in altered firing rates and altered oscillatory rhythms . For instance , the modulation of gamma activity with theta oscillations in the hippocampus is conceivably entirely due to the small fields generated endogenously in the theta band [19] . Similarly , slow-wave activity can be entrained by very weak endogenous fields in vitro [28] or weak applied currents in vivo [29] . Most importantly , however , there are a multitude of studies in human showing long term plastic effects ( e . g . [13] , [52]–[56] , just to name a few ) . These are often simply described as lasting changes in neuronal excitability [57] . However , the mechanisms by which weak stimulation could modulate/induce plasticity are less well understood . In humans , both enhancing and suppressing effects have been found with either polarity of stimulation . Some studies argue that depolarizing currents enhance glutamatergic or NMDA dependent Hebbian-type plasticity [58] , [59] , while other studies have invoked homeostatic plasticity [60] . Lasting effects on synaptic efficacy have only recently been found in vitro [61] , [62] . These studies demonstrate that very specific conditions on network activity are required in addition to weak-field stimulation in order to observe lasting changes in synaptic efficacy [63] . In the present study we have aimed to provide a detailed explanation of how weak fields , which are capable of modulating network firing rates [19] , may alter ongoing homeostatic plasticity , and how this translates into observable macroscopic effects on EEG slow-wave oscillations . Crucial for our predictions was a network model of slow-wave oscillations that is based on UP/DOWN state transitions . We showed that SWO entrain to weak-field slow-oscillatory stimulation consistent with experiments in vitro [28] and in vivo [29] . We also confirmed entrainment here again on the human EEG data ( Figure S2 . C . 1 ) . The model exhibited entrainment for depolarizing , hyperpolarizing and mixed polarity stimulation ( Figures 3 . A . 3–3 . A . 4 ) . Importantly , we demonstrate how this entrainment rectifies the effects of fields of mixed polarity to result only in increased firing rates ( Figure 3 . A . 2 ) . When combined with homeostatic plasticity , the model reproduced slow-wave decay in power similarly to previous more complex computational models [9] ( Figure 3 . B . 2 ) . Interestingly , the present model also reproduced the recently observed breakup of global coherent oscillations [2] reflected here in declining spatial slow-wave coherence ( Figure 3 . B . 3 ) – a finding that we confirmed also in the human EEG data ( Figure 1 . C . 1 ) . We used a simple negative feedback on firing activity to implement homeostatic plasticity . Specifically , the model predicted that an acute increase in the firing rate results in a faster homeostatic downscaling of synapses . Thus , we predicted a reduced decay of slow-wave decay ( in power and coherence ) in the hours after stimulation ( Figure 3 . B . 2–B . 3 ) . Human SWO subsequent to stimulation were indeed modulated as predicted ( Figure 1 . B . 3–C . 3 ) . The results are further confirmed by the precise agreement of model predictions with the varying effect size observed across electrodes ( Figure 4 . B–4 . C ) . The choice of a target firing rate was made to reproduce the experimentally observed decrease in firing rate during slow-wave sleep as reported in in-vivo experiments [11] . Previous models of SWO implemented a reduction of synaptic strength explicitly [9] or implicitly using STDP [64] . More complex models of plasticity , such as the BCM model [65] are expected to lead to similar predictions . An alternative interpretation of the observed reduction in decay rate after stimulation may be an alteration of sleep stages , e . g . the first slow waves stage was disrupted . However , it is not clear how this hypothesis would lead to different effects at different electrode locations . It is also possible that fields have a direct effect on synaptic strength , but current literature suggests that very specific conditions need to be satisfied for plastic effects to be observed . While we made no direct observation of firing rates nor synaptic strengths , the agreement between the present multi-scale model and the human EEG data does support the hypothesis that field-induced cell polarization results in an increase of firing rate and that this accelerates synaptic downscaling during oscillatory transcranial stimulation .
EEG data was recorded on human subjects from the beginning of the night sleep until wake the next morning in the study described by [14] . Briefly , transcranial stimulation with slow-oscillating currents ( ON/OFF at 0 . 75 Hz with trapezoid waveform ) was performed after subjects had attained stable stage 2 or deeper non-rapid eye movement sleep ( according to [66] ) . Stimulation was repeated altogether 5 times for 5 minutes followed by 1 minute intervals without stimulation ( total of 25 minutes stimulation plus four one-minute intervals ) . Anodal stimulating electrodes were placed bilaterally at F3 and F4 and cathodal electrodes on mastoids M1 and M2 ( 10/20 system , Figure 1 . A . 1 ) . Current intensity on each hemisphere oscillated between 0 . 26 mA ( on ) and 0 . 0 mA ( off ) and was below perception . To assure that stimulation intensities were below perception thresholds we stimulated subjects for 10 seconds ( active and sham ) when subjects where in bed but lights were still on . Immediately after , subjects were asked whether they had felt anything on their head . The subjects responses did not differ between the active stimulation or sham stimulation , indicating that the stimulation was indeed below perception . Note that the stimulation used in the study are significantly lower than the maximum used during transcranial stimulation ( 2 mA , [13] , [55] ) and so well below the current amplitudes considered safe for human studies [67] , [68] . To test further for possible side effects , heart rate was monitored during sleep , i . e . during stimulation and thereafter . No obvious changes in heart rate were observed during the stimulation . The experimental protocol was approved by the ethics committee of the University of Lübeck . For the present analysis EEG data with complete sleep scores included 10 subjects for the sham conditions and 13 subjects with active stimulation . Paired tests were thus limited to 10 subjects . Acute entrainment of EEG to the oscillatory stimulation on this data has been previously reported [14] . However , this previous analysis did not consider the phase of entrainment nor slow-wave spatial coherence , and more importantly , it did not analyze long term decay of SWO in the hours following stimulation . The FEM computations follow a previous study [18] . Briefly , an anatomical MRI with 1 mm resolutions for an adult male was segmented and different tissues ( gray matter , white matter , cerebrospinal fluid , skull , scalp , eye region , muscle , air , and blood vessels ) were assigned conductivity values from the literature . Virtual electrodes were placed as in the human experiment and a finite-element mesh was generated . To compute electric field distribution in the brain the Laplace equations with Neumann boundaries were solved in COMSOL Multiphysics 4 . 2 ( Burlington , MA ) with electrodes drawing 0 . 26 mA . The radial component of the resultant electric field was computed as the dot product of field vectors with a unit vector that is normal to the cortical surface . These radial components were collected in a volume of a 35 mm diameter around each EEG electrode ( Figure 6 . A shows radial fields at mesh points of the FEM within such a volume ) . These values were then sorted ( Figure 6 . B ) and the resulting field profile was applied along one direction of the 2D network lattice ( Figure 6 . C ) . The top and bottom 3 . 12 percentile were exclude and amplitudes scaled to an average of 0 . 93 V/m . The fields computed by the FEM are significantly smaller than what we used in the network simulations . However , there are a number of parameters that may magnify the specific effect size . The polarization of the cell membrane in response to applied fields used here was based on in-vitro experiments in rat [48] . Human cortical cells are larger , which may result in larger membrane polarizations [31] . More importantly , we observed for the present model that the effect of polarization on network firing rate is an increasing function of the number of incoming synaptic connections ( Figure 7 ) . A realistic network architecture with hundreds if not thousands synaptic inputs is thus expected to lead to a larger effect size .
|
Sleep pressure is reflected in the power of slow-wave activity: it is high after extended wakefulness and gradually decays in the course of the night . Transcranial stimulation with slow-oscillating currents can entrain electro-encephalographic slow-wave oscillations ( SWO ) and transiently increase their power . Motivated by the results from a multi-scale computational model , we tested in humans whether 25 minutes of transcranial stimulation attenuates the decay of SWO in the remainder of the night . A Finite-Element Model ( FEM ) is used to estimate the current flow in the brain and a network model of spiking neurons determines the resultant effect on SWO . This multi-scale model predicted increased neuronal firing rates leading to accelerated synaptic downscaling . As a consequence , the decay of SWO power and spatial coherence after stimulation is reduced . In addition to reduced decay rate , the model was also able to successfully predict , in the human experiments , the spatial distribution of the effect across EEG electrodes . These combined experimental and modeling results suggest a mechanism by which electrical stimulation can accelerate synaptic homeostasis and thereby influence a putative process of sleep regulation . The ability to accelerate the homeostatic function of sleep may have important practical implications .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biotechnology",
"bioengineering",
"biomedical",
"engineering",
"neural",
"homeostasis",
"computational",
"neuroscience",
"biology",
"neuroscience",
"engineering"
] |
2013
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Transcranial Electrical Stimulation Accelerates Human Sleep Homeostasis
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Survival of M . tuberculosis in host macrophages requires the eukaryotic-type protein kinase G , PknG , but the underlying mechanism has remained unknown . Here , we show that PknG is an integral component of a novel redox homeostatic system , RHOCS , which includes the ribosomal protein L13 and RenU , a Nudix hydrolase encoded by a gene adjacent to pknG . Studies in M . smegmatis showed that PknG expression is uniquely induced by NADH , which plays a key role in metabolism and redox homeostasis . In vitro , RenU hydrolyses FAD , ADP-ribose and NADH , but not NAD+ . Absence of RHOCS activities in vivo causes NADH and FAD accumulation , and increased susceptibility to oxidative stress . We show that PknG phosphorylates L13 and promotes its cytoplasmic association with RenU , and the phosphorylated L13 accelerates the RenU-catalyzed NADH hydrolysis . Importantly , interruption of RHOCS leads to impaired mycobacterial biofilms and reduced survival of M . tuberculosis in macrophages . Thus , RHOCS represents a checkpoint in the developmental program required for mycobacterial growth in these environments .
A critical determinant defining pathogenicity of Mycobacterium tuberculosis ( Mtb ) is its survival in host macrophages . Upon internalization by the host phagocytic cell , Mtb and related pathogenic mycobacteria block the fusion of their resident phagosome to the destructive lysosome , thereby establishing a niche within the bactericidal macrophage [1 , 2] . This ability of pathogenic mycobacteria requires the eukaryotic-type serine/threonine protein kinase G ( PknG ) [3] . Lack of PknG activity results in rapid delivery of mycobacteria to lysosomes , leading to enhanced killing of the intracellular bacilli by macrophages [3] . Besides its role in the innate survival of Mtb in host cells , PknG provides mycobacterial species with an intrinsic resistance to antibiotics [4] . In the absence of PknG , both pathogenic Mtb and non-pathogenic M . smegmatis display increased susceptibility to multiple antibiotics [4] . These observations suggest that PknG might be required for the persistence of Mtb within hosts , during which the bacillus also becomes highly recalcitrant to antibiotics . Although PknG represents an attractive target for tuberculosis ( TB ) drug development , the molecular mechanism by which this kinase exerts its biological functions remains largely unknown . It was shown that PknG is secreted via the SecA2 secretion system [5] into the macrophages’ cytosol [3] where it is hypothesized to interfere with host signaling pathways controlling phagolysosome synthesis [3] . However , attempts to identify the putative host substrate ( s ) targeted by PknG have thus far been unsuccessful . As a result , the role of PknG in Mtb survival in host macrophages remains ambiguous . In other pathogenic bacteria such as Vibrio cholerae , Escherichia coli , Pseudomonas aeruginosa , Streptococcus sp . , and Haemophilus influenza , host persistence and antibiotic tolerance are tightly correlated with the ability to form biofilms , community-like growth consisting of surface-bound cells that are metabolically and physiologically distinct from planktonic cells [6–9] . In vitro , Mtb and other mycobacterial species can form biofilms , which require iron and mobile mycolate moieties [10–12] . Development of mycobacterial biofilms is also modulated by activities of enzymes of the tricarboxylic acid ( TCA ) cycle , such as 2-oxoglutarate dehydrogenase [11] . Like other bacteria , mycobacterial cells persisting within biofilms display increased antibiotic tolerance , reminiscent of Mtb cells that form during latent TB [11] . However , it has remained largely unknown how the antibiotic-tolerant biofilm of Mtb relates to its pathogenicity , and whether these phenotypic correlations are co-regulated in Mtb and related mycobacteria . Here , we found that in mycobacteria , biofilm growth and host persistence are both regulated by RHOCS , a newly identified redox homeostatic system in which PknG plays a central role . We show that the redox regulatory molecule NADH induces the expression of PknG , which phosphorylates the ribosomal protein L13 at a unique residue , threonine 11 ( T11 ) . The phosphorylation promotes the cytoplasmic association of L13 with RenU , a Nudix hydrolase encoded by a gene adjacent to pknG on mycobacterial chromosomes , and accelerates RenU’s NADH hydrolytic activity . Disruption of the PknG-L13-RenU pathway causes: ( i ) increased oxidative stress susceptibility , ( ii ) accumulation of NADH and FAD during oxidative stress , ( iii ) impaired biofilm growth , and notably , ( iv ) reduced survival of Mtb in host macrophages . These results suggest that biofilm growth and host persistence are both regulated through the PknG-modulated RHOCS , which regulates levels of nucleoside diphosphate derivatives such as NADH and FAD in mycobacteria .
Studies in other bacteria have established the phenotypic relationship between host persistence , antibiotic resistance and biofilm growth [6 , 9] . PknG was previously shown to be required for two of these three phenotypes , namely survival in macrophages and resistance to multiple antibiotics [3 , 4] . In addition , phenotypic characterization of a M . smegmatis ΔpknG mutant revealed profound alterations in surface charge and hydrophobicity of the cell wall ( S1 Table ) [4] , suggesting that PknG might be involved in mycobacterial biofilm growth . Wild type strains of M . smegmatis , M . bovis BCG , and Mtb , together with their derived ΔpknG mutants and complemented strains were assayed for growth in both planktonic cultures and static biofilms ( Figs 1 and S1 ) . Similar to M . bovis BCG [3 , 13] , absence of PknG did not affect planktonic growth of M . smegmatis ( Fig 1A ) . However , the MtbΔpknG displayed a slow growth defect in stationary phase ( Fig 1B ) , as previously reported [14] . These phenotypic variations suggest a complexity of PknG function among mycobacterial species that warrants further investigation . However , in all mycobacterial species investigated , ΔpknG mutants consistently displayed severe retardation in biofilm growth ( Figs 1C–1F and S1 ) . As previously described [10] , wild type cells initially formed clusters emerging onto the surface , which then steadily spread and eventually covered the entire liquid-air interface . This surface invasion was followed by a maturation stage characterized by the formation of typical surface wrinkles ( Figs 1C–1F and S1 ) . By contrast , clusters of ΔpknG cells formed unevenly and failed to cover the entire surface . Many of these cell clusters eventually sank and became submerged in the liquid phase ( Figs 1C–1F and S1 ) . A surface attachment assay also showed insufficient surface dispersal by M . smegmatis ΔpknG ( S2 Fig ) . Biofilm growth of the ΔpknG mutants was completely restored by in trans expression of either intraspecific or interspecific pknG genes ( Fig 1C–1F ) , suggesting that PknG provides similar functions in biofilm growth to all mycobacterial species . To test if the requirement for PknG is due to its kinase activity , biofilm growth of Mtb strains was assayed in the presence or absence of a PknG-specific inhibitor , AX20017 [3 , 15] . Similar to genetic deletions ( Figs 1C–1E and S1 ) , AX20017 completely abolished biofilm growth of both wild type and the complemented strain of Mtb ( Fig 1F ) , whereas it had no effect on planktonic growth in similar growth media [3 , 15] . Collectively , these results show that PknG kinase activity is required for growth of mycobacteria including Mtb in the static condition of surface biofilms . Structural studies revealed a rubredoxin-like domain at the N-terminus of PknG , suggesting a possible involvement of this kinase in redox homeostasis [15] . In fact , our in vitro phosphorylation assays supported the hypothesis that PknG kinase activity may be regulated by the redox state of the mycobacterial cytoplasm ( S3 Fig ) . We studied the role of the pknG locus in mycobacterial redox homeostasis . Interestingly , these studies revealed that pknG and a neighboring gene ( msmeg_0790/rv0413 ) , previously annotated as mutT3 ( Fig 2A ) , were each required for oxidative stress resistance in M . smegmatis and Mtb ( Fig 2B–2C ) . The deduced amino acid sequences encoded by msmeg_0790 and rv0413 show the motif GX5EX7REUXEEXGU ( where U = L , V , I ) , typical of Nudix ( Nucleoside diphosphate linked moiety X ) hydrolases [16] . Nudix hydrolases are low molecular weight ( MW ) “housecleaning” phosphohydrolases that provide control over cellular levels of deleterious metabolic intermediates [16] . The proteins encoded by msmeg_0790 and rv0413 had been wrongly annotated as MutT3 because they were thought to be anti-mutators , prototypical Nudix hydrolases that degrade and prevent misincorporation of 8-oxo-guanosine triphosphate into nucleic acids . However , recent studies showed that msmeg_0790 and rv0413 are not involved in anti-mutation activity [17] . Wild type M . smegmatis and Mtb , their derived MsΔpknG and MtbΔpknG mutants , and Δmsmeg_0790 or Δrv0413 mutants , respectively , were challenged with oxidative stress triggered by H2O2 ( Fig 2B–2C , left panels ) or diamide ( Fig 2B–2C , right panels ) . In both M . smegmatis ( Fig 2B ) and Mtb ( Fig 2C ) backgrounds , addition of H2O2 or diamide completely stopped the growth of the mutants , whereas the wild type strains continued to grow . These results suggest that both pknG and msmeg_0790/rv0413 are involved in a redox regulatory mechanism that protects mycobacteria from oxidative stress . In light of the fact that this protein does not function as an anti-mutator , and the findings described in this paper , we propose to rename this Nudix hydrolase as RenU ( for Redox Nudix hydrolase ) . To test whether RenU is indeed a hydrolase , and to further characterize its enzymatic activity , the recombinant M . smegmatis RenU was purified to homogeneity . Size exclusion chromatographic analysis showed that RenU was monomeric in solution ( S4 Fig ) . Next , its enzymatic activity was determined using a coupled enzyme colorimetric assay described in the Extended Experimental Procedures . Substrate specificity was investigated with a panel of several different nucleoside diphosphate derivatives ( NDPX ) and nucleoside triphosphates ( NTP ) . RenU did exhibit Nudix hydrolase activity with a substrate preference for NDPXs . Among the substrates tested , the highest activities were observed with ADP-ribose , FAD , and NADH ( Figs 3A left panel , and S5 ) . By contrast , the enzyme displayed much lower activities towards NTPs including ATP , 7 , 8-dihydroneopterin triphosphate ( DHNTP ) ( Fig 3A left panel ) , dGTP , dCTP , dUTP , or other NDPXs such as CoA , GDP-D-mannose , NADP , ADP-ADP , and CDP-choline ( S5 Fig ) . Importantly , mutations in glutamate residues of the Nudix box ( E74 , E77 , and E78 , see S2 Table ) , which are expected to coordinate the magnesium required for the activities of Nudix hydrolases , completely abolished the enzymatic activity of RenU . The mutated protein , RenUDEAD , displayed no activity towards the preferred substrates exhibited by wild type RenU ( Fig 3A , right panel ) . Michaelis-Menten analysis revealed that , in vitro , ADP-ribose and FAD were better substrates than NADH , as evidenced by its higher kcat/Km value ( Figs 3B and S6 ) . However , previous studies with Nudix hydrolases predict that the substrate preference of RenU might be defined in vivo through its interactions with other proteins [18] . In fact , analysis of cellular levels and PknG induction experiments ( see below ) suggest that NADH is the physiologically relevant substrate of RenU in vivo . Interestingly , while RenU readily hydrolyzed NADH , the reduced form of nicotinamide adenine dinucleotide , it did not show significant catalytic activity towards the oxidized form , NAD+ ( Fig 3C ) . To determine whether the Nudix hydrolase activity of RenU is required for mycobacterial biofilm growth , MsΔrenU and MtbΔrenU mutants , their parental wild types , and the mutants complemented with either RenU or RenUDEAD , were tested in biofilm growth assays . As shown in Fig 3D–3F , the ΔrenU mutants were as defective as the ΔpknG mutants in biofilm growth . Whereas in trans expression of RenU partially restored biofilm growth , expression of the RenUDEAD form failed to rescue the biofilm in both the ΔrenU mutants ( Fig 3E–3F ) , confirming the requirement for this Nudix hydrolase activity in mycobacterial biofilm growth . These observations , together with their cognate chromosomal localization , further suggest that PknG and RenU participate in the same pathway required for mycobacterial biofilm growth . To investigate how PknG and RenU interact , we first tested if PknG phosphorylates RenU . The encoding genes were cloned for expression in M . smegmatis or E . coli as 6xHistidine- ( 6H ) tagged proteins . Purified RenU . 6H preparations were subjected to in vitro kinase assays using radioactive [γ-P32]-ATP as the phosphate donor . Whereas the M . smegmatis-derived RenU . 6H displayed a protein species phosphorylated by PknG , the E . coli-derived equivalent did not show phosphorylation ( Fig 4A ) . This was unlikely due to contaminated phosphatases because addition of phosphatase inhibitors ( PI ) did not reverse the phosphorylation pattern ( Fig 4A ) . The MW of the phosphorylated protein species found in the M . smegmatis-purified RenU . 6H appeared ~5 kDa smaller than RenU . 6H , as revealed by Coomassie Blue stained gels ( Fig 4A and 4E , lane 8 ) . In addition , corresponding fractions obtained during the purification of a control cell lysate ( from a M . smegmatis strain carrying only the expression plasmid without the RenU-encoding sequence ) did not show the same phosphorylated protein species ( Fig 4B ) . These results suggest that the phosphorylated protein was of M . smegmatis origin and associated with RenU . To identify the RenU-associated protein that is phosphorylated by PknG , the identities of proteins co-purified with RenU . 6H expressed in M . smegmatis were analyzed by mass spectrometry . Among the 15 proteins found to associate with RenU ( S3 Table ) , three had theoretical MWs similar to the phosphorylated protein: ssrA-binding protein SmpB ( MW 18 , 287 ) , 50S ribosomal protein L13 ( or RplM , MW 16 , 119 ) , and 50S ribosomal protein L16 ( or RplP , MW 15 , 595 ) . M . smegmatis genes encoding these proteins were cloned and expressed in E . coli as 6H-tagged proteins . The recombinant proteins were purified and subjected to in vitro phosphorylation assays . These experiments showed that only L13 was readily phosphorylated by PknG ( Fig 4C and 4E , lane 5 ) . Co-purification experiments confirmed the interaction of L13 and RenU in the cytoplasm of M . smegmatis ( Fig 4D ) . In addition , the MW displayed by L13 on Coomassie Blue gels and autoradiographs was identical to the protein previously found to associate with RenU purified from M . smegmatis ( Fig 4E , lanes 5 and 8 ) . Without PknG , L13 proteins from either M . smegmatis or Mtb showed no sign of phosphorylation in the presence of [γ-P32]-ATP ( Fig 4C and 4E , lanes 4 ) , showing that the phosphorylation requires PknG . Furthermore , addition of the PknG specific inhibitor AX20017 inhibited the phosphorylation of L13 by PknG ( Fig 4E , lane 6 ) . Addition of a 6H-tag shifted the phosphorylated signal of L13 visualized on autoradiograph and Coomassie Blue stained gel ( Fig 4E , lane 7 ) . These results confirmed the phosphorylation of L13 by the kinase activity of PknG . Similar to its autophosphorylation ( S3 Fig , panel A ) , the in vitro phosphorylation of L13 by PknG is affected by the redox status of the environment ( S3 Fig , panel B ) . To further establish whether L13 phosphorylation is PknG specific , in vitro phosphorylation assays were carried out using 6H . L13 as substrate , and cell lysates from M . smegmatis strains as the kinase sources . Using [γ-P32]-ATP as the phosphate donor , the in vitro phosphorylation assays were followed by pull-down of 6H . L13 using nickel-NTA-agarose beads ( Qiagen ) . Precipitated materials were washed , treated with SDS sample buffer and released proteins separated on SDS-PAGE gels , followed by autoradiography . Whereas lysates from M . smegmatis strains expressing PknG , either in trans or chromosomally , readily phosphorylated 6H . L13 , lysates from MsΔpknG failed to do so , indicating that phosphorylation of L13 specifically requires PknG ( Fig 4F ) . It is also important to note that the phosphorylation of L13 by PknG did not require RenU ( Fig 4F , lane 5 ) , suggesting that phosphorylation occurs before L13 and RenU form a complex . L13 proteins , encoded by rplM genes from both M . smegmatis ( Fig 4C and 4E ) and Mtb ( Fig 5 ) , were equally phosphorylated by PknG , indicating that this phosphate transfer reaction serves an identical function in mycobacteria . To identify the specific amino acid residues that are phosphorylated by PknG , Mtb L13 protein purified from E . coli was subjected to a cold kinase assay catalyzed by PknG . L13 was then digested with trypsin and the derived peptides were analyzed by ISL-TOFF mass spectrometry ( Taplin Biological Mass Spectrometry Facility , Harvard Medical School ) . This analysis suggested that one phosphorylated residue was present among the three amino acids closely situated at positions 11–14 of the N-terminus of L13 . Among these , T12 is absolutely conserved in all available bacterial L13 protein sequences , whereas T11 and S14 are exclusively conserved across the Mycobacterium genus ( Fig 5A , marked with asterisks ) . We first created a triple mutant of Mtb L13 , termed L13 ( 3A ) , in which all three residues T11 , T12 and S14 were mutated to alanine . In vitro phosphorylation assays showed that this mutant protein was no longer phosphorylated by PknG ( Fig 5B , lane 5 ) , confirming that the phosphorylated amino acid is among these three residues . Next , mutant L13 proteins with single mutations were made and the purified proteins were individually re-tested in in vitro phosphorylation assays . Whereas L13 ( T12A ) and L13 ( S14A ) mutants were readily phosphorylated ( Fig 5B , lanes 7 and 8 ) , L13 ( T11A ) completely failed to be phosphorylated by PknG ( Fig 5B , lane 6 ) , similar to the triple mutant L13 ( 3A ) ( Fig 5B , lane 5 ) . These results indicate that the mycobacterial conserved T11 of L13 is uniquely phosphorylated by PknG . To assess if the phosphorylation status of L13 at T11 plays a role in the biofilm growth modulated by PknG , mutant alleles rplMT11A and rplMT11E were used to replace wild type rplM in M . smegmatis genomes . Whereas L13 ( T11A ) is not activated by PknG , L13 ( T11E ) mimics the conformation of phosphorylated L13 . In M . smegmatis , replacement was successful with either rplMT11A or rplMT11E allele ( Fig 5C ) . In Mtb , however , we were only able to create a Mtb . L13 ( T11A ) replacement mutant ( rplMT11A ) but failed to obtain Mtb . L13 ( T11E ) ( rplMT11E ) . These results may suggest the essentiality of the non-phosphorylated form of L13 in M . tuberculosis , as indicated by previous work [19] . The Ms . L13 ( T11A ) mutant displayed biofilm growth defects , replicating the phenotypes observed previously with MsΔpknG and MsΔrenU ( Fig 5D–5E ) , whereas the Ms . L13 ( T11E ) mutant just showed a minor reduction compared to wild type ( Fig 5D–5E , far right panel ) . In trans expression of the L13 ( T11E ) allele from an integrative vector restored biofilm growth to the Ms . L13 ( T11A ) mutant . Similar to M . smegmatis , the Mtb . L13 ( T11A ) exhibited biofilm growth defects that could be rescued by in trans expression of an L13 ( T11E ) allele ( Fig 5F–5G ) . Unlike wild type Mtb or the MtbΔpknG/pknG strains ( Fig 1F ) , the PknG inhibitor AX20017 failed to block biofilm growth of the Mtb . L13 ( T11A ) / ( T11E ) strain ( Fig 5F–5G ) . Together , these observations suggest that ( i ) phosphorylation of L13 by PknG is required for mycobacterial biofilm growth and that ( ii ) PknG , L13 , and RenU form a functional cascade that modulates this static growth type in mycobacteria . A recent study showed that expression of PknG is tightly regulated by unknown mechanisms related to the pathogenicity of Mtb [20] . Whereas PknG is highly expressed in slow growing mycobacteria such as Mtb and M . bovis BCG , the expression in M . smegmatis is extremely low [4 , 20] . To investigate the conditions that trigger PknG expression in M . smegmatis , the bacterium was treated with various redox stimuli , followed by analysis of PknG levels by Western analysis using a specific polyclonal antibody [3 , 4 , 20] . Interestingly , we found that PknG expression is uniquely induced when M . smegmatis cells are exposed to high levels of NADH ( Fig 6A ) . None of the other tested chemicals , including FAD ( lower panel ) , induced PknG expression . The induction of PknG expression by NADH , in both concentration- ( Fig 6B ) and time-dependent ( Fig 6C ) manners , may suggest a specific regulatory mechanism , similar to the Rex system originally described in Streptomyces [21–24] , or an indirect effect due to changes in cellular metabolism or physiology caused by NADH exposure . The facts that ( i ) PknG expression is induced by NADH ( Fig 6A–6C ) , ( ii ) RenU preferentially degrades this redox cofactor in vitro ( Fig 3A–3C ) , and ( iii ) absence of PknG or RenU leads to failed oxidative stress responses ( Fig 2B–2C ) , indicate that the RHOCS pathway involving PknG , L13 , and RenU regulates cellular redox homeostasis through an NAD ( H ) -related mechanism . To elucidate if interruption of RHOCS activities affects cellular NADH levels , M . smegmatis mutants of the PknG-L13-RenU axis and the parental strain mc2155 were challenged with H2O2 , followed by extraction and analysis of NADH , NAD+ , and FAD concentrations . Whereas interruption of RHOCS did not affect NAD+ level , it resulted in dramatic accumulations of NADH and FAD by H2O2 ( Fig 6D ) . These observations reveal a novel mechanism of redox homeostasis that senses and regulates the cellular levels of NADH , the possibly other nucleoside diphosphate derivatives including FAD . To better understand the role of the phosphorylation of L13 by PknG , we first analyzed if phosphorylation affects the formation of the L13-RenU complex in the mycobacterial cytoplasm . M . smegmatis strains representing different states of L13 phosphorylation were first exposed to NADH to induce PknG expression . Cell lysates were prepared and ribosomes removed by ultracentrifugation . RenU . 6H was then added to the non-ribosomal fractions . After incubation , RenU . 6H was purified using Cobalt agarose beads and the co-purification of L13 analyzed by Western analysis using a polyclonal anti-L13 antibody . Whereas RenU . 6H was equally detected , L13 association with RenU . 6H in the cytoplasm was dependent on its phosphorylation by PknG ( Fig 6E ) . This experiment suggests that phosphorylation of L13 at T11 by PknG promotes its association with RenU in the mycobacterial cytoplasm . Because the function of RHOCS is involved with regulation of cellular NADH levels ( Fig 6A–6D ) , we examined if phosphorylated L13 affects the RenU-catalyzed NADH hydrolysis ( Fig 3C ) . To study this question , we first established a fluorescence-based assay that allowed continuous monitoring of NADH hydrolysis by RenU . The assay was based on the different spectral characteristics of folded and unfolded conformations of NADH in aqueous solutions as previously reported [25] . NADH absorbs light at a wavelength of 260 nm through its adenine moiety and emits light at a wavelength of 460 nm through its nicotinamide moiety . The efficiency of the energy transfer responsible for this excitation/emission characteristic is decreased in the unfolded conformation or , in the case of this assay , upon the hydrolysis of NADH . The hydrolysis of NADH by RenU in the presence or absence of L13 ( T11E ) , a mimic form of phosphorylated L13 , was monitored . The initial rates were fit to the Michaelis-Menten equation ( Fig 6F ) to determine Km and Vmax values ( Fig 6G ) . Analysis of Km confirmed that there was no effect of L13 ( T11E ) on RenU’s NADH-binding affinity ( one-way ANOVA , effect of L13 ( T11E ) , F ( 3 , 8 ) = 2 . 06 , p>0 . 18 ) ( Fig 6G ) . In addition , L13 ( T11E ) did not have observable effects on NADH hydrolysis in the absence of RenU ( Fig 6F , blue vs green ) ; and wild type L13 did not have observable effects on the NADH hydrolysis catalyzed by RenU ( S7 Fig , panel A ) . Importantly , analysis of Vmax of the reactions performed at 37°C displayed a 20 . 6% increase in the rate of NADH hydrolysis in the presence of L13 ( T11E ) ( one-way ANOVA , effect of L13 ( T11E ) , F ( 3 , 8 ) = 35 . 80 , p<0 . 05×10-3 ) ( Fig 6F , red vs black , and 6G ) . An increase in Vmax was also observed with temperature increments up to 42°C ( S7 Fig , panel B ) . Together , these data suggest that the phosphorylation of L13 by PknG directly impacts not only the association of L13 with RenU in the mycobacterial cytoplasm ( Fig 6E ) , but also the NADH hydrolytic activity catalyzed by RenU ( Fig 6F–6G ) . To investigate if RHOCS is related to the role of PknG in the survival and lysosomal delivery of pathogenic mycobacteria in infected macrophages [3] , Mtb RHOCS mutants and the parental strain H37Rv were used to infect murine bone-marrow derived macrophages . Survival was determined by measuring colony forming units ( CFUs ) of internalized Mtb cells at day 0 and day 4 following the infection . As shown in Fig 7A , deletion of pknG or renU , or the single mutation L13 ( T11A ) , significantly reduced the percentages of Mtb survival at day 4 relative to day 0 . By contrast , the complemented strains , namely MtbΔpknG/pknG , MtbΔrenU/renU , and L13 ( T11A ) / ( T11E ) , showed survival similar to wild type Mtb ( Fig 7A ) . As shown with biofilm growth , the mutant allele renUDEAD failed to restore the survival of the MtbΔrenU mutant ( Fig 7A ) . In addition , in trans expression of the phosphorylation-mimic form of L13 , L13 ( T11E ) , also made the L13 ( T11A ) / ( T11E ) strain resistant to AX20017 , the PknG specific inhibitor . These results , all together , indicated that the kinase activity of PknG , the Nudix hydrolase activity of RenU , as well as the phosphorylation of L13 , each is required for the survival of Mtb in host macrophages . Next , to analyze if the intracellular survival of Mtb strains correlated with their lysosomal delivery levels , trafficking of internalized Mtb strains was analyzed by microscopy . As shown previously [3] , absence of pknG resulted in increased lysosomal delivery ( Fig 7B ) . The MtbΔpknG mutant was largely localized within acidic milieus , whereas wild type Mtb displayed a low level of lysosomal localization ( Fig 7B ) . In trans expression of pknG restored wild type level of lysosomal delivery to MtbΔpknG ( Fig 7B ) . In addition , MtbΔrenU and Mtb . L13 ( T11A ) mutants exhibited lysosomal delivery levels comparable to that of MtbΔpknG ( Fig 7B ) while the corresponding complemented strains , MtbΔrenU/renU and L13 ( T11A ) / ( T11E ) , behaved like wild type in lysosomal delivery . In an agreement with the survival ( Fig 7A ) , RenUDEAD failed to rescue MtbΔrenU and the L13 ( T11A ) / ( T11E ) strain showed resistance to AX20017 ( Fig 7A ) . These results suggest that the function of RHOCS in Mtb lysosomal delivery is correlated , either as a cause or a consequence , to the survival of the bacillus in the macrophage .
This work has revealed a novel signaling mechanism that is used by mycobacteria to regulate cellular redox homeostasis ( Fig 7C ) . We propose that this system , RHOCS , is capable of sensing the key redox regulator NADH , and regulating its cellular level through direct degradation . RHOCS is composed of at least three components: a eukaryotic-type protein kinase , PknG , a ribosomal protein , L13 , and a Nudix hydrolase , RenU . RHOCS is responsive to cellular NADH levels through up-regulated expression of PknG , which phosphorylates L13 at a unique site , T11 , and promotes its cytoplasmic association with RenU . At least two possible mechanisms may lead to this increased L13-RenU association: ( i ) phosphorylation of L13 by PknG prevents the association of L13 with the ribosome , or ( ii ) the phosphorylation causes releases of L13 from the ribosome , similar to the effect of L13a phosphorylation by ZIPK observed in human macrophages [26] . Once associated with RenU in the cytoplasm , phosphorylated L13 accelerates the Nudix hydrolase activity of RenU that directly degrades NADH , thus lowering its cellular level . This paradigm of redox regulation is novel and has not been observed before in bacteria . Despite its localization on the large ribosomal subunit , the canonical ribosomal function of L13 remains enigmatic . E . coli L13 was suggested to contribute to the first step of 50S subunit assembly [27] , whereas the human analog L13a might play a role in ribosomal RNA methylation [28] . By contrast , accumulating evidence suggests that L13 plays several functions outside the ribosome . In E . coli , L13 forms a transcription anti-termination complex with other ribosomal proteins ( RpL3 , RpL4 and RpS4 ) , which binds RNA polymerase and acts on Rho-dependent anti-terminators of ribosomal RNA [29] . L13 was also shown to interact with Obg , an essential GTP binding protein involved in growth promotion and stress response in B . subtilis [30] . In human macrophages , treatment with interferon-γ ( IFN-γ ) induces phosphorylation of L13a by ZIPK [26] . Phosphorylated L13a is then released from the ribosome to form , with four other proteins , the IFN-Gamma-Activated Inhibitor of Translation ( GAIT ) complex that binds messenger RNAs and inhibits translation of proteins involved in IFN-γ responses [26 , 31] . Our data reveal a novel extra-ribosomal function of L13 , triggered through its phosphorylation by PknG , in redox homeostatic regulation in mycobacteria . The fact that both Mtb and its host macrophage use L13 phosphorylation as a common method to convey cellular stress responses is fascinating and warrants further investigation . Our work also supports the recent “depot hypothesis” , which proposes that macromolecular complexes such as the ribosome function as “reservoirs” for regulatory proteins that perform non-canonical functions [32 , 33] . The mechanism of action proposed for RHOCS ( Fig 7C ) fits nicely with some of the previous observations . Work by other groups suggests that PknG derepresses the TCA cycle through its phosphorylation of the cycle inhibitors GarA or OdhI [34 , 35] . Thus , activity of PknG in the TCA cycle is expected to increase production of NADH , which is then fed into the oxidative phosphorylation pathway that produces reactive oxygen species and free radicals . In addition , NADH is an effective inhibitor of α-ketoglutarate dehydrogenase , the key generator of NADH and oxidative stress [36] , and a target of GarA [34 , 35] . Therefore , the role of PknG in the RHOCS pathway may provide mycobacteria with a supportive mechanism that prevents cell death from redox disturbance caused by increased TCA activity . Interestingly , free radicals produced from NADH by the TCA cycle were recently suggested to mediate bacterial cell death triggered by bactericidal antibiotics [37] . Accordingly , the function of RHOCS in cellular NADH regulation may also help to explain the recent observation that absence of PknG leads to enhanced antibiotic susceptibility in mycobacteria [4 , 38] . Bacterial responses to oxidative stress have emerged as an integral part of the developmental program required for biofilm growth [39–41] . For example , oxidative stress was shown to evoke metabolic adaptation that reduce NADH production [42] and induces biofilm formation [43] . Similarly , the transcription regulator SoxR , which helps bacteria to defend oxidative stress , was shown to coordinate biofilm growth in Pseudomonas sp . , E . coli , and S . coelicolor [40 , 44] . We propose that RHOCS , through its role in redox stress regulation , is required for growth of mycobacteria in biofilms and the phagosomal milieu of host macrophages . The ability to sense and regulate cellular levels of NADH allows RHOCS to switch cells between different states of metabolism and physiology . Therefore , RHOCS may function as a key regulator that links redox homeostasis with the pathogenicity of M . tuberculosis .
M . tuberculosis H37Rv , M . bovis BCG Pasteur , and M . smegmatis mc2155 ( American Type Culture Collection ) were used as parental strains . Mycobacterial strains were grown at 37°C in 7H10 or 7H9 with appropriate supplements and antibiotics . Kanamycin and hygromycin were used at 50 and 75 μg/ml , respectively . Biofilm growth was done as previously described [10] using Sauton’s medium . For quantitation , a syringe connected to a sterile needle was used to remove the liquid medium and planktonic cells beneath the films . The biomass was harvested and growth estimated through determination of total protein by Bradford method . Targeted gene deletion or replacement was done by homologous recombination methods as previously reported [3 , 4] . Details can be found in the S1 Text . Plasmids and oligonucleotides used in this study can be found in S4 and S5 Tables , respectively . Macrophages , generated as described in Extended Experimental Procedures , were seeded in 12-well tissue culture plates ( BD Biosciences , San Jose , CA ) and let adhere overnight ( 37°C , 10% CO2 ) prior to infection . Mtb strains were grown to saturation and infections were performed at MOI 50:1 for 3 hours . Infected macrophages were washed with warm PBS and incubated for 45 minutes with 200 μg/ml amikacin to kill extracellular bacteria , and exchanged into fresh DMEM . At 0 or 72 hours of incubation at 37°C and 10% CO2 , infected macrophages were processed for CFU assays by washing 3 times with PBS , followed by lysis of the macrophages by 0 . 05% SDS for 5 minutes . Supernatants were harvested , vortexed thoroughly , and plated in triplicate in ten-fold dilutions onto 7H10-OADC agar . Plates were incubated at 37°C for 4 to 5 weeks before CFUs were counted . Statistical analyses were conducted using GraphPad Prism 5 . 0f software ( La Jolla , CA ) . Students two-tailed t-test was used to analyze the statistical significance of differences between groups . For enzyme kinetics experiments , one-way analysis of variance was performed using Excel , and non-linear least squares fits were conducted in Matlab by Mathworks ( Natick , MA ) .
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Nearly one-third of the world’s population is infected with Mycobacterium tuberculosis ( Mtb ) , the causative agent of TB . A key factor that contributes to the widespread infection of Mtb is its capacity to survive inside the host macrophage . Understanding how Mtb withstands the hostile intracellular environment of this phagocytic cell may reveal targets for development of therapeutics that enhance the innate anti-Mtb activities of the macrophage . We discovered a novel signaling pathway in mycobacteria which regulates cellular redox homeostasis through NADH and FAD , regulators of metabolism and redox balance . NADH induces the expression of a protein kinase , PknG , which then phosphorylates the ribosomal protein L13 and promotes its presence in the cytoplasm . L13 therein forms a complex with RenU , a Nudix ( Nucleoside diphosphate linked moiety X ) hydrolase that degrades NADH and FAD . Genetic disruption of this signaling cascade leads to cellular accumulation of these molecules , increased mycobacterial sensitivity to oxidative stress , impaired surface biofilm growth , and most importantly , reduced survival of Mtb in macrophages .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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A Redox Regulatory System Critical for Mycobacterial Survival in Macrophages and Biofilm Development
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Phagocytes locate microorganisms via chemotaxis and then consume them using phagocytosis . Dictyostelium amoebas are stereotypical phagocytes that prey on diverse bacteria using both processes . However , as typical phagocytic receptors , such as complement receptors or Fcγ receptors , have not been found in Dictyostelium , it remains mysterious how these cells recognize bacteria . Here , we show that a single G-protein-coupled receptor ( GPCR ) , folic acid receptor 1 ( fAR1 ) , simultaneously recognizes the chemoattractant folate and the phagocytic cue lipopolysaccharide ( LPS ) , a major component of bacterial surfaces . Cells lacking fAR1 or its cognate G-proteins are defective in chemotaxis toward folate and phagocytosis of Klebsiella aerogenes . Computational simulations combined with experiments show that responses associated with chemotaxis can also promote engulfment of particles coated with chemoattractants . Finally , the extracellular Venus-Flytrap ( VFT ) domain of fAR1 acts as the binding site for both folate and LPS . Thus , fAR1 represents a new member of the pattern recognition receptors ( PRRs ) and mediates signaling from both bacterial surfaces and diffusible chemoattractants to reorganize actin for chemotaxis and phagocytosis .
How eukaryotic phagocytes locate and recognize bacteria is a fundamental question in biology . Eukaryotic phagocytes and their interactions with bacteria began when single-celled life forms , protozoans , appeared about 2 billion years ago [1] . Since then , multicellular organisms have gradually evolved increasingly complex genomes . The phagocytic cells within these organisms , such as macrophages and neutrophils , patrol the rest of the body to detect , recognize , and eliminate invading pathogenic bacteria [2 , 3] . The current dogma is that phagocytic cells use at least two types of receptors for defense against bacterial pathogens: one for detecting and chasing pathogens via chemotaxis and another for recognizing and eliminating them via phagocytosis . It is well established that human phagocytes locate bacteria using serpentine chemoattractant receptors linked to heterotrimeric G-proteins ( hence , G-protein-coupled receptors [GPCRs] ) that regulate cell shape and movement by controlling the actin cytoskeleton [4 , 5] . Upon catching bacteria , human phagocytes use phagocytic receptors to bind and ingest opsonized targets . Phagocytic receptors recognize opsonins , such as complements or immunoglobulins ( IgGs ) , coated on the surface of the bacteria , and this process activates tyrosine kinases to promote actin polymerization [6–10] . In addition , infecting microorganisms are recognized by innate immune systems through pattern-recognition receptors ( PRRs ) , such as Toll-like receptors ( TLRs ) , scavenger receptors , and C-type lectin receptors , which collectively allow cells to recognize microbial-associated molecular patterns ( MAMPs ) [3 , 6 , 11 , 12] . However , the social amoeba Dictyostelium discoideum , whose protein repertoire is small compared to phagocytes from multicellular organisms , does not encode orthologs of any known PRRs or typical phagocytic receptors , such as complement receptors or Fcγ receptors [13–15] . Nonetheless , the cells are highly evolved as professional phagocytes that chase bacteria using chemotaxis and consume them as food , so they clearly contain specific receptors to mediate phagocytosis as well as chemotaxis . Dictyostelium is widely used for studies of actin-linked processes such as cell migration , chemotaxis , and phagocytosis , as these processes are accomplished using a simpler set of proteins but evolutionarily conserved mechanisms [4 , 16–19] . Cells inhabit the soil and feed on diverse bacterial species , including gram-positive and gram-negative bacteria [20 , 21] . They locate bacteria by detecting metabolites such as folic acid , move toward the bacteria via chemotaxis , and then consume them through phagocytosis [22] . A previous study found that Dictyostelium Similar to Integrin Beta protein A ( SibA ) shares similar structure and function to mammalian integrin β chains and plays a role in substrate adhesion during phagocytosis [15] . However , the molecular mechanisms underlying how this phagocyte recognizes bacteria to initiate phagocytosis are not understood . We recently identified a GPCR , folic acid receptor 1 ( fAR1 ) , and demonstrated that it mediates chemotaxis toward folic acid in Dictyostelium [23] . Interestingly , Dictyostelium cells lacking fAR1 receptors ( far1− ) are defective in not only chemotaxis but also phagocytosis of Klebsiella aerogenes ( gram-negative ) [23] . The genome encodes appropriate G-proteins , including 12 Gα subunits and 1 Gβγ complex [24] . We therefore investigated the role of fAR1 and its cognate G-proteins in bacterial recognition and ingestion . Here , we show that the stereotypical phagocyte Dictyostelium simultaneously utilizes fAR1 for chemotaxis and phagocytosis . The same receptor and cognate G-proteins detect the diffusible chemoattractant folate , allowing cells to locate and chase bacteria and the immobile component on the bacterial coat lipopolysaccharide ( LPS ) to engulf and consume them .
To explore how fAR1 recognizes bacteria , we first analyzed its amino acid sequence as detailed in Materials and methods . We found that fAR1 contains an amino-terminal extracellular domain , seven transmembrane domains , and a carboxyl-terminal intracellular domain ( Fig 1A ) . Structural alignment and homology modeling of the extracellular domain including approximately 350 amino acids show that it folds as a VFT structure . Computational docking analysis indicates that a folic acid molecule binds to the VFT cleft of fAR1 ( Fig 1A ) . VFT modules are found in various membrane proteins in organisms ranging from bacteria ( such as periplasmic binding proteins ) to higher metazoans in which they constitute the ligand-binding domains of the class C GPCRs , including glutamate receptors ( mGluRs ) , gamma-aminobutyric acid type B receptors ( GABABRs ) , Ca2+-sensing receptors ( CaSR ) , taste receptors ( T1R ) , pheromone receptors ( V2R ) , and olfactory receptors [25] . Since VFT domains originated from bacterial periplasmic binding proteins and interact with various ligands [26 , 27] , we conjecture that the VFT domain of fAR1 can bind molecules on the bacterial surface in addition to the diffusible chemoattractant folic acid . It was recently reported that far1− cells are defective in phagocytosis of K . aerogenes ( gram-negative ) but appear to be normal in phagocytosis of Bacillus subtilis ( gram-positive ) [23 , 28] . Thus , we examined whether a major MAMP in gram-negative bacterial outer membranes—LPS—binds fAR1 to promote engulfment . Cells of wild type ( WT ) or far1− were incubated with fluorescently labeled LPS at 4°C for 15 min , and fluorescent cells were quantified by flow cytometry ( Fig 1B ) . Binding of fluorescein isothiocyanate ( FITC ) -LPS to far1− cells was significantly reduced compared to that of WT cells , and excessive folic acid ( 1 mM ) reduced binding of LPS to WT cells . Taken together , these data indicate that LPS binds fAR1 , and the binding sites of LPS and folic acid may overlap . We then examined fAR1/G-protein-mediated chemotactic signaling in response to LPS ( Fig 1C ) . LPS stimulation induced extracellular signal-regulated kinase 2 ( ERK2 ) activation by phosphorylation in WT but not far1− or gβ− cells , while expressing fAR1–yellow fluorescent protein ( YFP ) in far1− cells restored LPS-induced ERK2 activation ( Fig 1C ) . Cells expressing Ras binding domain ( RBD ) –green fluorescent protein ( GFP ) , PH domain of cytosolic regulator of adenylyl cyclase ( PHCRAC ) -GFP , and partial sequences of LimE ( ΔlimE ) -GFP—which are the fluorescent probes for monitoring activation of Ras , phosphatidylinositol-4 , 5-bisphosphate 3-kinase ( PI3K ) , and actin polymerization , respectively [29–31]—were stimulated with soluble LPS and imaged using time-lapse fluorescence microscopy ( Fig 1D and S1 Fig ) . LPS , like folic acid , induced transient membrane translocations of RBD-GFP ( Ras signaling ) , PH-GFP ( PI3K signaling ) , and ΔLimE-GFP ( F-actin ) in WT cells , which is substantially decreased in far1− or gβ− cells ( Fig 1D and S1A–S1D Fig ) . Together , our results indicate that binding of LPS to fAR1 activates heterotrimeric G-proteins that trigger chemotactic signaling events . To further explore the role of fAR1’s VFT domain in ligand recognition , we compared ligand-induced activation of ERK2 between far1− cells expressing fAR1-YFP and a mutant fAR1 lacking the N-terminal VFT domain , fAR1ΔN-YFP ( Fig 1E and S2A Fig ) . Although both fAR1-YFP and fAR1ΔN-YFP are localized at the membrane ( S2B Fig ) , ERK2 activation by LPS or folic acid was only detected in cells expressing fAR1-YFP ( Fig 1E ) , supporting the notion that both ligands bind to the VFT domain to activate fAR1 . To identify the crucial region of LPS recognized by fAR1 , we examined chemotactic signaling induced by LPS molecules produced by different bacterial mutants , which contain the same lipid A moiety but different types of saccharide context ( Fig 1F ) . Ra-LPS and Rc-LPS , but not Rd-LPS , triggered robust actin polymerization in WT cells ( Fig 1F and S2C–S2E Fig ) . As expected , mutant LPS-mediated signaling was absent in far1− and gβ− cells ( Fig 1F and S2C–S2E Fig ) , suggesting that saccharides in the core region of LPS bind to and activate fAR1 . In previous work , we found a relatively simple computational model could explain how biased positive feedback of actin regulators could lead to amoeboid chemotaxis [32] . The activation of the cytoskeleton is mediated by an activator at the cell surface , which drives movement by causing pseudopod protrusion in the same way as the actin system [33 , 34] . Chemoattractants do not directly cause protrusion but modulate the positive feedback that maintains pseudopods . When this model was adapted to respond appropriately to rigid obstacles , by stalling parts of the pseudopod that were unable to move forward , we were surprised to see behavior that closely resembled phagocytosis—when pseudopods hit particles , they split in halves that progressed down the sides of the particle and started to surround it . However , with simple particles ( Fig 2A and S1 Video ) , the nascent cup became unstable and resolved into a pseudopod before the particle was halfway engulfed . Modeling physical adhesion between the virtual cell and the particle ( Fig 2B and S1 Video ) increased the amount and duration of contact , but it still usually failed before engulfment , leading the cell to migrate away from the particle . In contrast , when the particle was treated as if it were coated with an immobilized chemoattractant , both halves of the nascent phagocytic cup were stabilized , and the cell efficiently engulfed the particle ( Fig 2C and S1 Video ) . Increasing the chemoattractant concentration on the particle surface increased the engulfment efficiency; however , increasing the amount of adhesion failed to do so ( Fig 2D and S3A Fig ) . This model provides a plausible mechanism for why G-protein-linked signaling can be important for phagocytic efficiency , as has been found in multiple systems [35 , 36] , as well as its better-known role in chemotaxis . To validate that chemoattractants on a particle surface promote phagocytosis by amoebas , we examined the engulfment of chemoattractant-coated beads . At the aggregating stage , Dictyostelium cells chemotax robustly to cAMP but lose the ability to eat bacteria [37] . Using live cell imaging , we observed that cAMP-coated beads—but not uncoated beads—induced localized signaling responses , such as accumulation of PHCRAC-GFP and ΔlimE-GFP , followed by bead engulfment ( Fig 2E and 2F ) . Previous studies indicated that cAMP receptor 1 ( cAR1 ) works mainly with Gα2Gβγ subunits [38–40] , while fAR1 may couple with Gα4Gβγ subunits [41–43] . We found that cAMP-coated beads induced these localized responses with subsequent phagocytic cup formation in WT , gα4− , and far1− cells ( S3B Fig ) but not in car1− , gβ− , or gα2− cells , in which cAMP sensing is abolished ( S3C Fig ) . Consistent with this , coatings of interleukin 8 ( IL-8 ) , a potent chemokine for human neutrophils , are reported to promote engulfment by neutrophils [44] . Using live cell imaging of HL60 cells , a human neutrophil cell line , we observed that beads coated with IL-8—but not uncoated beads—induced actin polymerization to form a phagocytic cup , followed by engulfment ( S3D and S3E Fig ) . In addition , IL-8 beads failed to trigger engulfment when Gi signaling was blocked by pertussis toxin treatment , indicating that the chemokine IL-8 receptor and its heterotrimeric Gi-proteins are required for engulfment ( S3F Fig ) . Furthermore , we previously showed that folic acid–coated beads can trigger localized chemotactic responses , leading to fAR1-mediated engulfment by Dictyostelium amoeba [23] . These results indicate that chemoattractants immobilized on the surface of particles activate GPCR/G protein systems to induce the formation of a phagocytic cup that leads to particle engulfment by amoeba of both Dictyostelium and mammals . Next , we tested how LPS originated from bacterial surface influences cell movement and engulfment . To determine whether the binding of LPS to fAR1 directs cell migration , we performed the EZ-TAXIScan chemotaxis assay [45] to test the ability of WT , far1− , fAR1-Y/far1− , and gβ− cells migrating in a linear gradient of soluble LPS ( Fig 3A ) . We found that soluble LPS , like folic acid , functions as an attractant to guide chemotaxis for Dictyostelium . WT and fAR1-YFP/far1− moved to LPS with similar net path lengths , speeds , and directionality , while far1− and gβ− cells did not chemotax to LPS ( Fig 3A and 3B and S4 Fig ) . These findings suggest that fAR1 couples with heterotrimeric G-proteins to mediate chemotaxis toward LPS . To examine whether interactions between fAR1 and surface-bound LPS promote engulfment , we incubated biotin-labeled LPS with NeutrAvidin beads to generate LPS-coated beads and then mixed them with live cells ( Fig 3C and 3D and S2 Video ) . LPS-coated beads induced a localized phosphatidylinositol ( 3 , 4 , 5 ) -trisphosphate ( PIP3 ) response ( arrows in the upper panel of Fig 3C ) and actin polymerization ( arrows in the upper panel of Fig 3D ) around the beads , subsequently leading to bead engulfment . To dissect the function of fAR1 and heterotrimeric G proteins in LPS-mediated engulfment , we then imaged far1− and gβ− cells that had been incubated with LPS-coated beads for 5 min and counted cells with or without internalized beads ( Fig 3C and 3D and S2 Video ) . Under similar conditions , more than 80% of WT cells engulfed 1 or more beads , while less than 30% of far1− cells or 20% of gβ− cells engulfed beads ( Fig 3E ) . Our results demonstrate that the fAR1/G-protein system detects both diffusible and immobile ligands and activates the pathways leading to either cell migration toward the source of soluble attractants or to the engulfment of a particle coated with recognition patterns . To further test the roles of GPCR/G-protein systems in bacterial engulfment , we examined engulfment of live K . aerogenes by WT , gβ− , gα2− , gα4− , far1− , and car1− cells ( Fig 4 ) . We first imaged internalization of K . aerogenes labeled by the pHrodo fluorescence probe using confocal microscopy ( Fig 4A ) . Cells were incubated with pHrodo-labeled K . aerogenes for 20 min , mixed with a basic buffer to quench extracellular pHrodo fluorescence , and then imaged by confocal microscopy . WT cells effectively engulfed the bacteria and formed acidified phagolysosomes containing internalized pHrodo-labeled K . aerogenes emitting fluorescence signals ( red particles ) , as the low pH environment in phagolysosomes enhances the fluorescence of pHrodo . Relative to WT cells , gβ− and far1− cells displayed a significant decrease in bacterial internalization ( Fig 4A and 4B ) . We then measured the internalization of K . aerogenes using flow cytometry ( Fig 4C and 4D ) . Cells were incubated with pHrodo-labeled K . aerogenes , collected at the indicated time points , and analyzed by flow cytometry to quantify the pHrodo-positive cells that contained internalized bacteria ( Fig 4C ) . Compared to WT cells , gβ− and far1− cells were substantially defective in bacterial uptake over time , while gα2− , gα4− , and car1− cells still retained the ability to internalize bacteria ( Fig 4D ) . Taken together , our results suggest that ligands on the surface of K . aerogenes activate fAR1 , which links to Gβγ and 1 or more Gα subunits to mediate bacterial engulfment .
The evidence presented here and previously [23] reveals that the stereotypical phagocyte D . discoideum utilizes a GPCR/G-protein machinery to simultaneously detect a diffusible chemoattractant folate and recognize an immobile component , LPS , on the bacterial outer membrane for both chasing and engulfing bacteria ( Fig 4E ) . We find that fAR1 is different from other chemoattractant GPCRs , as it belongs to the class C GPCR family and consists of a VFT extracellular domain for sensing multiple ligands . fAR1 functions as a PRR to mediate bacterial engulfment . The VFT domain in fAR1 recognizes LPS , a generic signature in commensal and pathogenic bacteria . VFT domains originated from bacterial periplasmic acid-binding proteins ( PBPs ) , which bind amino acids , sugars , and other nutrients for bacterial growth . These domains have been acquired and adopted as extracellular ligand-binding domains by cell membrane receptors [46] , such as those in the class C GPCR family . Our analysis indicates that the D . discoideum genome encodes 14 class C GPCRs , including fAR1 , that contain extracellular VFT domains . Bioinformatics analysis suggested that the VFT domain of these members are evolutionarily closer to bacterial PBPs and eukaryotic GABABRs family than to other class C GPCRs [47 , 48] , constituting the prototype of class C GPCRs with a variety of physiological functions [49] . Interestingly , bacterial PBPs bind various ligands , while most mammalian class C GPCRs expressed in the central nerve system bind only one natural ligand , implying that during evolution , VFT domains of class C GPCRs underwent partial loss of function , such as the ability to bind various ligands [49] . However , the VFT in fAR1 still retains the ability to recognize two different ligands: the bacterial-secreted diffusible chemoattractant folate for chasing bacteria and the major MAMP , LPS for engulfing gram-negative bacteria . Thus , the chemoattractant fAR1 receptor , a VFT containing GPCR , represents a new subfamily of PRRs . It is intriguing to note that most known LPS receptors recognize the conserved lipid A moiety [50–53] , while fAR1 mainly responds to the saccharide core region of LPS instead . The lipid A moiety inserts into the membrane and links to a core complex of 8–12 sugars , which is linked to the O-antigen [54] . Interestingly , previous studies indicated that Dictyostelium may sense saccharides to mediate engulfment [55–57] . In addition , a recent study showed that brain angiogenesis inhibitor I ( BAI1 ) , an adhesion GPCR found in mammals , also recognizes the saccharide cores of LPS and promotes the engulfment of gram-negative bacteria [58] . The saccharide cores of LPS protruding outward from the bacteria membrane may be used as a target of recognition by phagocytes that engulf live bacteria . In the meantime , subtle changes on MAMPs from pathogen may substantially prevent phagocyte detection [59 , 60] . We noticed that far1− cells still maintain a low level of binding for either LPS or folic acid , suggesting that other proteins interacting with LPS and folic acid may exist on the cell surface . Future study is needed to identify them . In conclusion , our current study on the social amoeba D . discoideum sheds new light on the origin of bacterial recognition by eukaryotic phagocytes , the path through which PRRs evolved , and the unexpectedly close mechanistic connection between chemotaxis and phagocytosis . One key question that remains is how D . discoideum recognizes gram-positive bacteria . A study reported that Dictyostelium cells lacking fAR1 lost the ability to chemotax toward gram-positive and gram-negative bacteria but still retained the ability to phagocytose B . subtilis , a gram-positive bacterium [28] . Thus , other receptors must be involved for recognizing the outer-membrane components of gram-positive bacteria to mediate their engulfment , and studies are now underway to determine how Dictyostelium cells recognize those MAMPs .
For axenic culture , vegetative cells were grown in D3T medium at 22°C with or without antibiotics as required . For synchronous development in shaking suspension , cells were harvested at mid-log phase , washed in development buffer ( DB; 7 . 4 mM NaH2PO4⋅H2O , 4 mM Na2HPO4⋅7H2O , 2 mM MgCl2 , 0 . 2 mM CaCl2 , pH 6 . 5 ) twice , and then resuspended in DB to 2 × 107 cells/ml . Cells were rotated at 120 rpm on a platform shaker at 22°C for 5 h and given exogenous 75 nM pulses of cAMP every 6 min . Cells of gα2− and gα4− were obtained from DictyBase stock center [61] . Cells of car1− and gβ− were provided by Peter Devreotes lab . WT and different mutant Dictyostelium cells were grown in D3-T medium , washed twice with phosphate buffer ( PB; 7 . 4 mM NaH2PO4⋅H2O , 4 mM Na2HPO4⋅7H2O , pH 6 . 5 ) , and resuspended in PB at 2 × 107 cells/ml . Cells were stimulated with 100 μM folic acid ( Sigma ) or 100 μg/ml LPS ( Escherichia coli O111:B4 , Sigma ) . At indicated time intervals after the stimulation , 150 μl of cell suspension was taken out , mixed with 50 μl 4× sample buffer , and boiled for 3 min . Proteins were separated by SDS–PAGE , transferred to nitrocellulose membranes , and blotted with polyclonal anti–phospho-p44/p42 MAPK ( pERK2 ) antibody ( Cell Signaling Technology ) and anti-actin antibody ( Santa Cruz Biotechnology ) . Vegetative WT and mutant Dictyostelium cells expressing PHCRAC-GFP , RBD-GFP , or LimEΔcoil-GFP were prepared using the same protocol for ERK2 activation assay . Cells were plated in 4 well chambers ( Lab-Tek ) and then imaged with a Zeiss LSM 880 Laser Scanning Microscope with a 60×; 1 . 3 NA Plan-Neofluar objective lens . Fluorescent frames were acquired every 2 s and in 30 frames total . A final concentration of 100 μg/ml LPS purified from different E . coli strains ( O111:B4 , Ra , Rc , and Rd , Sigma ) was added to the cells to induce RBD-GFP , PHCRAC-GFP , or LimEΔcoil-GFP translocation from the cytosol to the plasma membrane . The temporal–spatial intensity changes of RBD-GFP , PHCRAC-GFP , or LimEΔcoil-GFP in cells were directly imaged using a confocal microscope . For each cell , a region of interest ( ROI ) was drawn at the plasma membrane to measure the fluorescence intensity change over time . The fluorescence intensities were normalized to the first frame with the appearance of LPS stimulation , which is defined as 1 . WT and mutant Dictyostelium cells were harvested from vegetative stage , washed with PB , and resuspended at 1 × 106 cells/ml . Cell migration was recorded in 15 s intervals at 22°C for 40 min in the EZ-TAXIScan chamber ( as indicated in Fig 3 ) , which was assembled as described in the manufacturer’s protocol . Chips used in the chamber were precoated with 1% BSA at 22°C for 30 min . A stable gradient of 0–1 , 000 μg/ml LPS , as described in Fig 3 and S4 Fig , was established for the assay . Cell migration analysis was performed with DIAS software . To make biotinylated cAMP , 50 μl of 18 mM biotin EZ-Link Sulfo-NHS-Biotin ( Thermo Fisher ) was incubated with 100 μl of 10 mM 6-AH-cAMP ( Biolog ) at 22°C for 8 h and purified by HPLC . NeutrAvidin beads with 1-μm diamter ( Thermo Fisher ) were washed with PB 3 times and resuspended into 1 ml PB . The beads were then incubated with biotinylated cAMP at 22°C for 2 h . The coated beads were washed 5 times with precold PB to remove excess free ligand . To make LPS-labeled beads , biotinylated bacterial LPS ( E . coli O111:B4 , InvivoGen ) was incubated with 1 μm NeutrAvidin beads 22°C for 2 h . The coated beads were washed 5 times with precold PB to remove excess free ligand . The non-coated NeutrAvidin beads or red fluorescent beads ( Thermo Fisher ) were washed 5 times with PB before use . Bacteria engulfment by Dictyostelium was conducted in both suspension and adhesion cultures as previously described [23 , 41] . Overnight cultured K . aerogenes were labeled with pHrodo Red dye ( Life Technology ) and incubated with axenic Dictyostelium cells in phosphate buffer at a 100:1 ratio at 22°C in suspension cultures ( 150 rpm ) . At indicated times , the cells were centrifuged and resuspended in basic buffer ( 50 mM Tris pH 8 . 8 and 150 mM NaCl ) to quench the fluorescence of nonphagocytized pHrodo-labeled K . aerogenes . The phagocytes and K . aerogenes were distinguished by forward scatter ( FSC ) and side scatter ( SSC ) . The appearance of pHrodo in the phagocyte population was monitored as an indicator of K . aerogenes engulfment . The phagocyte cell population characterized by high fluorescence of pHrodo was considered as the cells that engulfed K . aerogenes . Data acquisition and analysis were done using FACSort flow cytometer ( BD Bioscience ) with Cell Quest software ( v . 3 . 3 ) and analyzed using FlowJo ( v . 10 . 0 . 8; Tree Star ) . Quantification of engulfed bacteria number per Dictyostelium cell was analyzed using confocal microscopy . Dictyostelium cells were allowed to attach onto 4 well chambers ( Lab-Tek ) and then incubated with pHrodo labeled K . aerogenes in phosphate buffer . After 15 min , phosphate buffer was replaced with basic buffer to stop engulfment and quench extracellular bacteria fluorescence for imaging . To visualize the bead and bacteria engulfment by Dictyostelium cells , vegetative or developed WT and mutants expressing different protein markers were harvested , washed with PB , and settled in a 4-well chamber for 10 min . A 10-fold excess of beads was added to the Dictyostelium cells , and the engulfment process was recorded with a Zeiss LSM 880 Laser Scanning Microscope with a 60×; 1 . 3 NA Plan-Neofluar objective lens . To quantify LPS-coated bead engulfment , cells were incubated with LPS beads for 5 min and recorded . The number of beads engulfed by each cell was counted . For each cell line , about 40 cells were included for quantification . WT and far1− cells were incubated with 10 μg/ml FITC-labeled LPS purified ( E . coli O111:B4 , Sigma ) for 15 min at 4°C in the absence or presence of 1 mM folic acid . Binding was determined by flow cytometry . The representative result was shown , and quantitation results from 3 independent repeats were presented as mean fluorescence intensity ( MFI ) in Fig 1 . fAR1-ΔN-YFP were generated by inverse PCR in which pDV-fAR1-YFP was used as the template . The first 29 amino acids were kept as the signal peptide . Amino acids from position 30 to 355 of fAR1 encoding sequence were deleted . far1− cells were transfected , and a population was selected by growing them in D3-T medium containing 50 μg/ml G418 . Constructs were confirmed by DNA sequencing . The computational framework of Neilson and colleagues [32 , 62] simulates migration using a slightly modified version of the Meinhardt mathematical model [63] , in which an “activator” drives the movement of the cell perimeter in the outward-normal direction . Considering their simplicity , these simulations yield remarkably plausible biological behavior . However , if the cell contacts another object , the system generates stereotypical behavior that blocks further movement . To permit migration in the presence of obstacles such as bacteria , parts of the cell boundary that are found to lie inside an obstacle are projected ( in the inward-normal direction ) onto the boundary of the obstacle . To prevent the simulated cell from immobilizing upon contact with an obstacle , the activator is then quenched at any points of contact ( simulating the equivalent of the “stall force” of normal actin ) , allowing the edges of the pseudopod to continue . We defined full engulfment as when the simulated cell boundary wraps around an obstacle and makes contact with itself , and we added a rule so that , following engulfment , the obstacle is removed , and the cell boundary joined together at the outermost points of contact . Chemoattractants behave exactly as in the previous work [32] , except they are tied to the surface of the particle instead of diffusible . By modeling the obstacles in this fashion , the local attractant excites the activator at points of the cell boundary that are very close to ( but not quite touching ) the obstacle , causing the cell to wrap itself around the obstacle and allowing the simulated cell to phagocytose obstacles that are otherwise too large to engulf . To explore how fAR1 recognizes ligands , we first analyzed amino acid sequence of fAR1 , using Protter program [64] , and found that it contains 1 extracellular N-terminal domain , 7 transmembrane domains , and 1 intracellular C-terminal domain ( Fig 1A ) . Then , we input the sequence of the extracellular domain into an HHpred program [65] to align with the protein structures available in Protein Data Bank ( PDB ) by default parameter setting . All top-20 hits are bacterial proteins whose crystal structures fold as VFT structures . We then submitted the extracellular sequence of fAR1 to the online I-TASSER server [66] , using all default settings to generate the homology model , which was used for docking . The three-dimensional conformer of folic acid ( Pubchem CID 6037 ) was downloaded from PubChem 3D [67] , which was used as the starting conformation for docking . Flexible docking of folic acid into the fAR1 model was performed by the program Glide in the Maestro suite from Schrodinger ( v . 2016–2 ) , using the induced fit docking protocol [68] . Docking was accomplished using the Extra Precision ( XP ) Glide [69]; all other parameters were defaults . A folic acid molecule gave Glide docking scores corresponding to nanomolar dissociation constant ( Kd ) . Figures of the docked poses were prepared using Chimera 1 . 12 [70] . The pose with the highest docking score of folic acid is shown in Fig 1A . The statistical significance was assessed using analysis of variance with the two-tailed unpaired Student t test . Data are presented as mean ± SD unless stated otherwise .
|
How eukaryotic cells find and interact with bacteria is a fundamental question in biology . Eukaryotic phagocytes are cells that engulf and digest bacteria . These include single-celled organisms , such as amoeba , and cell types of multicellular organisms , such as macrophages . The current dogma is that phagocytic cells use at least two types of receptors for defense against invading pathogens: one for detecting and chasing pathogens via chemotaxis and another one for recognizing and eliminating them via phagocytosis . Detection and chasing is facilitated by G-protein-coupled receptors ( GPCRs ) , whereas recognition and elimination employ pattern recognition receptors ( PRRs ) . However , the social amoeba Dictyostelium discoideum does not encode orthologs of any known PRRs or phagocytic receptors; yet they are highly evolved as professional phagocytes that chase bacteria via chemotaxis and consume them as food through phagocytosis . Here , we show that this stereotypical phagocyte utilizes folic acid receptor 1 ( fAR1 ) , a class C GPCR , to simultaneously detect bacterial secreted folate for chasing bacteria and microbial-associated molecular patterns ( MAMPs ) —lipopolysaccharide ( LPS ) —for engulfing and consuming them .
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2018
|
A G-protein-coupled chemoattractant receptor recognizes lipopolysaccharide for bacterial phagocytosis
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Occurrence of intraspecific variation in parasite virulence , a prerequisite for coevolution of hosts and parasites , has largely been reported . However , surprisingly little is known of the molecular bases of this variation in eukaryotic parasites , with the exception of the antigenic variation used by immune-evading parasites of mammals . The present work aims to address this question in immune suppressive eukaryotic parasites . In Leptopilina boulardi , a parasitic wasp of Drosophila melanogaster , well-defined virulent and avirulent strains have been characterized . The success of virulent females is due to a major immune suppressive factor , LbGAP , a RacGAP protein present in the venom and injected into the host at oviposition . Here , we show that an homologous protein , named LbGAPy , is present in the venom of the avirulent strain . We then question whether the difference in virulence between strains originates from qualitative or quantitative differences in LbGAP and LbGAPy proteins . Results show that the recombinant LbGAPy protein has an in vitro GAP activity equivalent to that of recombinant LbGAP and similarly targets Drosophila Rac1 and Rac2 GTPases . In contrast , a much higher level of both mRNA and protein is found in venom-producing tissues of virulent parasitoids . The F1 offspring between virulent and avirulent strains show an intermediate level of LbGAP in their venom but a full success of parasitism . Interestingly , they express almost exclusively the virulent LbGAP allele in venom-producing tissues . Altogether , our results demonstrate that the major virulence factor in the wasp L . boulardi differs only quantitatively between virulent and avirulent strains , and suggest the existence of a threshold effect of this molecule on parasitoid virulence . We propose that regulation of gene expression might be a major mechanism at the origin of intraspecific variation of virulence in immune suppressive eukaryotic parasites . Understanding this variation would improve our knowledge of the mechanisms of transcriptional evolution currently under active investigation .
Models of host-parasite coevolution all assume occurrence of genetic variation for host resistance and parasite virulence , such as well-described for plant-pathogen interactions [1] and in a few host-parasite models [2][3] . Advances in understanding coevolutionary interactions thus require unraveling the molecular bases of host resistance and parasite virulence , and then acquiring data on how polymorphism in genes controlling these traits affect parasitism success in the field [4] . This will enable direct observation , rather than inference , of the host-parasite coevolutionary dynamics . One largely unaddressed question in eukaryotic parasites is the basis of intraspecific variation of virulence . Regarding immune aspects , the only described mechanism is , to our knowledge , the antigenic variation used by fungal and protozoan parasites to hide themselves from the mammalian immune system [5]–[10] . Whether changes associated with virulence variation in immune suppressive parasites are qualitative and/or quantitative and what is their nature , still remain to be assessed . The biological models of interacting species that satisfy all the requirements to study coevolutionary processes , from molecular tools to population polymorphisms , are scarce and Drosophila-parasitoid wasps interactions are undoubtedly among the best of them [11] . Variation in both Drosophila resistance and parasitoid virulence is observed in the field [12]–[14] , and some major genes involved in these traits have been characterized [15]–[18] . Based on these data , we address here the question of the origin of intraspecific variation of virulence of Drosophila parasitoids . Endoparasitoid wasps develop inside the body of their arthropod host , which will die as a result of the interaction [19] , [20] . To face the immune defense of the host , they have evolved original strategies ranging from displaying surface features that prevent their recognition to altering components of the host immune system using venom proteins , virus-like particles or wasp-specific viruses , polydnaviruses [21] , [22] . However , occurrence of virulence variation together with molecular identification and characterization of the factors involved in immune suppression has only been reported in the wasp Leptopilina boulardi [15] , [16] , [23] , [24] . Drosophila melanogaster immune response to a parasitoid consists in the formation of a multicellular melanized capsule around the wasp egg that results in the death of the parasitoid [25] . Plasmatocytes first attach to the parasitoid egg and spread around it , then lamellocytes adhere to them to form multiple cell layers [26] , [27] . Two types of L . boulardi wasps have been described based on their virulence properties against Drosophila hosts . The ISm isofemale line , highly virulent against D . melanogaster ( and so-called “virulent” line ) is representative of Mediterranean L . boulardi wasps both in its virulence properties and venom protein profile [23] , [28] . It produces in its venom a RacGAP domain-containing protein , named LbGAP , whose injection in D . melanogaster larvae mimics the egg protection provided by parasitism [23] , [24] , [29] . LbGAP has a RacGAP activity and induces changes in the morphology of D . melanogaster lamellocytes [23] , [24] . It specifically interacts with and inactivates two Drosophila Rho GTPases , Rac1 and Rac2 [15] , both required for successful encapsulation of Leptopilina eggs [27] , [30] . Interestingly , ISm wasps are not virulent against the host species D . yakuba , and , accordingly , host lamellocytes remain unchanged in presence of ISm venom [31] . By contrast , the success of the ISy isofemale line of L . boulardi depends on the host phenotype and it was then called “avirulent” [12] , [13] . This line originates from Congo , where variation of parasitism success toward D . melanogaster was observed , due to occurrence of a polymorphism in the L . boulardi virulence phenotype [13] , [28] . This polymorphism is likely due to the fact that several Drosophila host species are available in tropical Africa that can successfully be parasitized , and that virulence toward D . melanogaster may be costly for the parasitoid [13] , [28] . Using the avirulent ISy line , resistant and susceptible D . melanogaster reference strains were obtained from a sympatric Congolese D . melanogaster population [32] . However , resistance to ISy parasitoids is not restricted to Congo but is present at high frequencies in tropical as well as Mediterranean host populations [13] . ISy parasitoids are able to suppress the immune defenses of susceptible larvae of D . melanogaster as well as of other host species such as D . yakuba [12] , [16] . However , their parasitism success is not associated with an alteration of the host lamellocyte shape [24] , [31] . Accordingly , at the protein level , no major band of the size of LbGAP was observed in electrophoretic analysis of ISy venom producing tissues [23] . Taken together , all these data point to LbGAP as a major virulence factor in Mediterranean L . boulardi parasitoids , involved in variation of parasitism success against D . melanogaster . In ISy tropical parasitoids , the venom contains a serpin that alters melanisation in the hemolymph of D . yakuba larvae [16] , and might be responsible for the delayed encapsulation induced by injection of total venom [31] . The way ISy females counteract the immune defenses of susceptible D . melanogaster flies is yet totally unknown . In this study , we first confirm that LbGAP is required for virulence against resistant D . melanogaster hosts . We demonstrate that both the virulent and avirulent parasitoid lines produce a RacGAP protein in their venom , and we report the sequence of the RacGAP gene homologous to LbGAP from the avirulent line ( LbGAPy ) . We then compare the activity of LbGAP and LbGAPy proteins , their level of interaction with their Rac targets and their localization in the lamellocytes of parasitized hosts . Finally , we present quantitative data on LbGAP and LbGAPy at the mRNA and protein levels on virulent , avirulent , and F1 parasitoids . Results show that differences between virulent and avirulent parasitoids regarding the RacGAP toxin are only quantitative and very likely due to variation in cis-regulation of gene expression .
Previous work had shown that LbGAP is sufficient for successful parasitism of resistant D . melanogaster hosts by virulent parasitoid females . In order to determine whether this factor is also necessary for virulence , we performed experiments of injection of ISm venom in resistant D . melanogaster larvae , which is known to protect avirulent ISy eggs from encapsulation [24] , [29] . In the present work , ISm venom was incubated before injection either with a specific polyclonal antibody against LbGAP or with the preimmune serum as a control , and larvae were then submitted to parasitism by ISy females . Venom incubated with the preimmune serum conferred active protection to avirulent eggs , with only 18 . 6% of encapsulation ( Figure 1A ) . By contrast , incubation of ISm venom with the antibody against LbGAP led to 75 . 9% of avirulent eggs being encapsulated ( Chi2 = 38 . 43 ; ddl = 1; p<0 . 001 ) . A second experiment was performed in which the LbGAP antibody or the preimmune serum were injected alone into resistant host larvae that were subsequently parasitized by virulent ISm parasitoids . The encapsulation rates were 0% with the preimmune serum and 34 . 8% following injection of the LbGAP antibody , respectively ( Chi2 = 24 . 49 ; ddl = 1 ; p<0 . 001; Figure 1B ) . These results demonstrate that LbGAP is a venom protein needed for L . boulardi virulence against resistant D . melanogaster flies . Whether an homolog of LbGAP is expressed in ISy parasitoids was questioned by performing PCR experiments on cDNAs from ISy venom-producing tissues , using primers designed from the sequence of LbGAP [23] . A 914 bp amplicon was obtained whose sequence contains a 861 bp ORF ( GenBank accession number GU300066 ) encoding a predicted protein of 286 amino acids that was named LbGAPy ( Figure 2A ) . Like LbGAP , this protein starts with a N-terminal signal peptide of 20 amino acids allowing its extracellular export , and it contains a RhoGAP domain . The nucleotide sequences of LbGAP and LbGAPy are 95 . 2% identical , while LbGAP and LbGAPy proteins share 89 . 5% identity and 94 . 8% similarity ( Figure 2B ) . LbGAPy contains the four amino acid residues Arg74 , Lys111 , Arg115 and Ser190 , described to be involved in LbGAP interaction with Rac GTPases [15] . Arg74 is conserved in all GAP proteins and forms an arginine-finger that stabilizes the GTPase invariant glutamine residue 61 or 63 to facilitate the catalysis of GTP to GDP [33] . The main difference between LbGAPy and LbGAP sequences is located at the C-terminal end of the protein outside the RhoGAP domain ( Figure 2B ) . LbGAP was previously shown to display a GAP activity with a strong preference for Rac-GTPases [15] . In order to determine if LbGAPy may have a similar GAP function in host cells , we carried out in vitro GAP assays using the LbGAPy protein produced in E . coli . Experiments were performed with human RhoA , Rac1 and Cdc42 Rho-GTPases . Human Ras , belonging to the Ras-GTPase family , was included as a negative control while LbGAP as well as the GAP domain from human p50 RhoGAP ( which stimulates GTPase activities of RhoA , Rac1 and Cdc42 in vitro ) , were used as positive controls . Other negative controls consisted in the omission of either small G-protein or GAP protein . Similarly to LbGAP , LbGAPy significantly increased the GTPase activity of human Rac1 and Cdc42 but not of RhoA and Ras ( F = 109 . 2; df = 11; p<0 . 001; Figure 3A ) . As for LbGAP , the GAP activity towards Rac1 was four times higher than towards Cdc42 , suggesting that Rac-GTPases are the preferred substrates of LbGAPy as well . As LbGAP is known to specifically interact with Drosophila Rac1 and Rac2 [15] , we questioned whether LbGAPy similarly targets these Rac-GTPases by performing yeast two-hybrid analyses . In order to stabilize interactions , we used the G12V mutated forms of Drosophila Rac1 , Rac2 and Cdc42 GTPases and the G14V mutated form of Drosophila RhoA . Each of these mutants is deficient in GTPase activity and therefore constitutively blocked in the GTP-bound active conformation . Fusions of the GAL4 activation domain with LbGAP were expressed in yeast together with fusions of the LexA-DNA binding domain either with Rac1G12V , Rac2G12V , Cdc42G12V or RhoAG14V . Direct in vivo interaction of LbGAPy with small GTPases was measured as the ability of transformed yeast to activate the transcription of HIS3 and lacZ reporter genes , both under the control of the LexA-binding sequences . Yeast growth on a selective medium lacking histidine revealed that , similarly to LbGAP , LbGAPy interacts with Rac1G12V and Rac2G12V but only weakly with Cdc42G12V , and has no interaction with RhoAG14V ( Figure 3B ) . The strength and specificity of the interaction between LbGAPy and Rac GTPases was then estimated by titration of ß-galactosidase activity ( Figure 3C ) . Substantial activity was seen using coexpression of GAL4AD-LbGAPy and either LexABD-Rac1G12V or LexABD-Rac2G12V but not in combination with non-specific sequences . The beta-galactosidase activity resulting from the interaction between LbGAPy and Rac GTPases was similar to that obtained using LbGAP and the same Rac GTPases ( F = 92 . 2; df = 13; p<0 . 001; Figure 3C ) , thus demonstrating that this interaction is as strong and specific as the one demonstrated with LbGAP . We previously showed that LbGAP enters plasmatocytes and lamellocytes in ISm-parasitized D . melanogaster larvae and that morphological changes in lamellocytes are correlated with the intracellular quantity of LbGAP [15] . Using the polyclonal antibody raised against LbGAP that equally recognizes LbGAPy ( see below ) , immunolocalization experiments were performed on hemolymph from D . melanogaster larvae 48 hours following parasitization by either ISm or ISy females . As expected , the majority of lamellocytes from ISm-parasitized larvae had a modified morphology and contained LbGAP ( red intracytoplasmic fluorescent dots; Figure 4A and 4B ) . In contrast , lamellocytes from ISy-parasitized larvae remained largely unmodified and very few contained LbGAPy dots ( Figure 4C and 4D ) . Among these , the number of dots was usually less than five whereas many lamellocytes from ISm-parasitized larvae contained more than 30 dots . qRT-PCR experiments were performed on ISm and ISy female samples of the same age to quantify differences in expression levels of LbGAP and LbGAPy genes between venom-producing tissues and the rest of the bodies , and to compare expression levels of LbGAP and LbGAPy in their respective parasitoid line . A 2200-fold higher expression was observed for LbGAP in ISm venom-producing tissues as compared to the rest of the female body ( Figure 5A; Student t-test : t = −19 . 1 , df = 12 , p<0 . 001 ) . Expression of LbGAPy was also higher in ISy venom producing tissues than in the rest of the body , but only with a 270-fold higher expression level ( Figure 5A; Student t-test: t = −16 . 6 , df = 10 , p<0 . 001 ) . When comparing parasitoid strains , LbGAPy was approximately 30 times less expressed in ISy venom-producing tissues than LbGAP in ISm venom-producing tissues ( Figure 5B; Student t-test: t = −9 . 4 , df = 15 , p<0 . 001 ) . To determine whether the difference in the number of LbGAP and LbGAPy transcripts results from a difference in the number of gene copy , qPCR experiments were performed on genomic DNA from the venom-producing tissues and from the rest of the female bodies of ISm and ISy parasitoids , respectively . No significant differences were found between the copy number of the LbGAP gene in ISm venom producing tissues and ISm residual female bodies or of the LbGAPy gene in ISy venom producing tissues and ISy residual bodies ( df = 3 , F = 1 . 4651 , p = 0 . 2953 ) . In previous Western blot experiments using a specific polyclonal antibody against the recombinant LbGAP protein , no signal was observed in ISy venom-producing tissues , possibly because the technique employed was not sensitive enough or because the antibody does not recognize LbGAPy [23] . These hypotheses were tested by producing both LbGAP and LbGAPy as GST-fusion proteins in Escherichia coli and using them to perform dot blot experiments on serial dilutions starting from the same quantity of these proteins . Our results show that the antibody recognizes specifically the LbGAP and LbGAPy recombinant proteins with the same efficiency ( Figure 6A ) . We then performed dot blot experiments with serial dilutions of total protein extracts from 20 ISm and 20 ISy venom-producing tissues ( which represent the same amount of protein ) , using the anti-LbGAP polyclonal antibody . LbGAP was easily detected in ISm sample dilutions while LbGAPy could only be detected in the undiluted ISy extracts . The quantity of LbGAPy was then estimated to be 60 times less than that of LbGAP in ISm venom tissues ( Figure 6B ) . In order to further investigate the role of LbGAP quantity in ISm virulence , we performed crossing experiments between ISm females and ISy males and we assessed the virulence level of the F1 offspring , as well as the LbGAP/LbGAPy quantity in F1 venom-producing tissues , using dot-blot experiments . The amount of the LbGAP/LbGAPy proteins in F1 venom-producing tissues was approximately half the amount of LbGAP in ISm ( Figure 6C ) . In parasitism experiments with the resistant strain of D . melanogaster in which ISy parasitoids are highly encapsulated ( virulence level 5 . 7% ) , virulence of F1 hybrids ( virulence level 98% ) did not significantly differ from virulence of ISm parasitoids ( virulence level 100% ; p<0 . 001 ) . To determine whether the variation of expression of LbGAP and LbGAPy is under the control of cis- or trans-acting elements , we performed PCR experiments on cDNA obtained from venom-producing tissues of ISm , ISy and F1 females . Two sets of primers were designed that respectively amplify LbGAP and LbGAPy and their specificity was tested using genomic DNA extracted from total bodies: a 670 bp and a 684 bp PCR product were amplified from ISm and ISy females , respectively , while both fragments were amplified from F1 individuals . Using ISm and F1 cDNAs and the LbGAP-specific primers , an intense band corresponding to a 252 bp amplicon was obtained . By contrast , only a faint band of 265 bp was observed using the LbGAPy-specific primers and cDNA from ISy or F1 individuals ( Figure 7 ) . Control of genomic DNA and cDNA quantities were performed using the internal transcribed spacer 2 ( ITS2 ) gene . Overall , these results show that F1 individuals overexpress the LbGAP and not the LbGAPy allele in venom tissues . This strongly suggests that variation of expression of LbGAP and LbGAPy is under the control of cis- rather than trans-acting elements .
Intraspecific variation in virulence occurs in several eukaryotic parasite species [31] , [34]–[36] , but it has only been explained in some mammalian parasites such as Toxoplasma gondii , Trypanosoma brucei or Plasmodium falciparum . In these species , antigenic variation occurs , mediated by the differential expression of surface molecules [5]–[10] . In parasitoid wasps , intraspecific variation in virulence has been reported in three species , Asobara tabida , Cotesia sesamiae and L . boulardi . In A . tabida , it is associated with a difference in immunoevasion capacities [35] in relation with the degree of embedment of the parasitoid egg in host tissues [37] , [38] . However , nothing is known of the mechanism by which A . tabida eggs adhere to host tissues . Parasitism success of C . sesamiae in the host Busseola fusca relies on the suppression of host immune defenses by polydnaviruses ( PDVs ) injected with the egg . Differences in the sequence of one PDV gene ( CrV1 ) and in its level of expression in the host exist between virulent and avirulent parasitoids [34] , [39] but CrV1 role in virulence of C . sesamiae has not been demonstrated . In L . boulardi , two virulence factors have been characterized and extensively studied in the venom , one in each of two lines , ISm and ISy , that display opposite virulence properties towards Drosophila host species [15] , [16] , [23] , [31] , [40] . L . boulardi then certainly provides the best parasitoid model to address the issue of the molecular bases of variation in virulence of an immune suppressive parasite . The LbGAP protein appears as a major band in venom protein electrophoretic patterns of all strains virulent against D . melanogaster analyzed to date , but it was not observed in the avirulent ISy line [23] . The demonstration that LbGAP represents a major toxin , sufficient for parasitoid virulence toward this host species , comes from experimental evidence that the proteins eluted from this band , when injected into host larvae , conferred the same protection to avirulent parasitoid eggs as injection of total ISm venom [23] , [24] , [29] . Here , we show that this protection is abolished if the venom is previously incubated with an anti-LbGAP antibody . Also , injection of the antibody into host larvae before parasitism significantly decreases the success of ISm parasitoids . LbGAP is thus the main factor responsible for protection of L . boulardi eggs in resistant D . melanogaster hosts , and it is necessary for parasitoid virulence . This might explain why virulence is reported to be controlled by a single chromosomal factor despite the presence of several proteins in the venom [41] . Variation in LbGAP is then likely responsible for most of the variation of virulence between L . boulardi strains . Here , we show that a gene homologous to LbGAP ( LbGAPy ) is expressed in venom-producing tissues of the avirulent parasitoid line and that the protein is present in the venom . The previous extensive characterization of LbGAP [15] , [23] , [24] thus provided a unique opportunity to assess whether variation of virulence is due to quantitative differences in this toxin or to qualitative changes that would impair binding to its targets or reduce its activity . LbGAP and LbGAPy deduced amino acid sequences are 89% identical , and both contain a signal peptide and a conserved GAP domain . The recombinant proteins have a similar level of GAP activity and they interact with the same host targets , in agreement with the conservation of critical interacting amino acid residues [15] . Altogether , no qualitative difference was observed between LbGAP and LbGAPy toxins in our functional assays that could explain variation in virulence between virulent and avirulent parasitoids . Occurrence of in vivo differences in protein binding or activity in fly hemocytes cannot be ruled out but is very unlikely . We previously showed that LbGAP is present in high amounts inside lamellocytes of ISm parasitized hosts [15] . Following parasitism by ISy , LbGAPy could also be detected inside host lamellocytes , but in a much lower number of cells and , when present , in a much lower quantity compared to LbGAP . Moreover , the morphology of LbGAPy-containing lamellocytes remained unchanged , in agreement with the previous observation that LbGAP quantity in a cell correlates with the degree of shape alteration [15] . LbGAP and LbGAPy are then both able to “enter” host hemocytes but the quantity of LbGAP in ISm venom is 60-fold higher than that of LbGAPy in ISy venom . This difference is sufficient to explain the difference in the amount of the two toxins inside host lamellocytes . A different rate of entry between LbGAP and LbGAPy in host cells cannot be ruled out but it would not be detected given the low quantity of LbGAPy in ISy venom . Such a high difference in quantity is probably responsible for the absence of detection of LbGAPy in ISy venom in a previous study [23] . Interestingly , the toxin amount in venom was twice lower in F1 hybrids than in ISm parasitoids while F1 hybrids were as virulent as ISm on D . melanogaster resistant flies . This also supports the idea that a minimal quantity of LbGAP is necessary for L . boulardi success in resistant D . melanogaster , and suggests the possible existence of a threshold effect on LbGAP/LbGAPy quantity in the virulence phenotype . The production of high amounts of LbGAP is probably under strong selection in Mediterranean areas where resistant D . melanogaster are often encountered as hosts [13] . The selection in tropical Africa would be relaxed due to the occurrence of alternative host species and to a possible cost of LbGAP overproduction . The reason why no resistance to virulent parasitoids has been described yet in D . melanogaster , while resistance to avirulent parasitoids is found at high frequencies , might be that resistance to injection of high amounts of LbGAP is difficult to evolve . Rac GTPases , the targets of LbGAP , are highly conserved proteins due to their key role in cell functions and target modification is unlikely to evolve . Some removal of LbGAP from the host hemolymph is performed via phagocytosis by host plasmatocytes [15] . However , the high quantity of the LbGAP injected , together with the fact that the toxin quickly enters host lamellocytes , may encompass phagocytosis capacities . Evolution of resistance would thus require evolution in the potential of detoxification by host hemocyte cells or of degradation of the toxin , for instance via host proteases . A connected question is the reason why LbGAP is not efficient on D . yakuba lamellocytes in spite of the total conservation of its Rac targets between the two host species . Answers might involve differences in their intrinsic potential of degradation of foreign proteins , the higher number of hemocytes cells recorded in D . yakuba [42] , or differences in lamellocytes that would influence the capacity of “entry” of LbGAP . Differences in the RacGAP protein amounts in venom of the two parasitoid lines were correlated with differences in the amount of LbGAP/LbGAPy mRNA in venom-producing tissues , while we found no difference in gene copy number using genomic DNA from venom tissues or residual bodies . This allowed us to conclude that variation in the RacGAP toxin between virulent and avirulent strains is mainly quantitative . It likely results from differences in regulation of gene transcription in venom-producing tissues , even if the hypothesis of a difference in LbGAP and LbGAPy mRNA stability cannot be totally ruled out . One of the characteristics of most parasitoid venom proteins is their high amount in venom compared to other tissues , which often correlates with a high level of expression of their coding genes [16] , [43]–[50] . Here , we found a much higher mRNA level of the RacGAP toxin in venom-producing tissues of the two parasitoid lines than in the rest of the body . Such a tissue-specific change of expression is one of the traits likely selected in the process of re-use of a protein as a virulence factor , because such factors need to be delivered into the host via injection of venom at each oviposition event [51] . Transcription of the LbGAP/LbGAPy gene is thus regulated both in a tissue-specific manner and differently between virulent and avirulent strains . Changes in gene regulation are now believed to play a prominent role in evolution of biological diversity . Regulatory factors that control gene expression are mainly transcription factors that bind to cis-regulatory elements in the upstream sequences of the gene , and microRNAs ( miRNA ) [52] . Specific gene expression in parasitoid venom-producing tissues might be driven by the availability of transcription factors that are tissue-specific [53] . Differences in the binding level of transcription factors to cis-regulating sequences might explain the different level of expression between parasitoid lines . They could originate either from evolutionary changes in these sequences , as recently reported at the inter-specific level [54] or from variation in accessibility of cis-regulating sequences [55] . In L . boulardi F1 individuals between ISm and ISy strains , it is the LbGAP allele that is overexpressed in the venom , the transcription of the LbGAPy allele remaining very low . This result supports the hypothesis of variation in cis-regulation of LbGAP expression . Full characterization of the mechanisms involved in regulation of LbGAP transcription will involve cloning and comparing upstream gene sequences and promoter regions between parasitoid strains , characterizing binding of transcription factors , and if necessary analyzing the miRNA expressed in venom protein-secreting cells since changes in miRNA-mediated gene regulation [52] can allow a quick and reversible diversification of the gene expression program . This would provide insights in understanding the mechanisms of transcriptional evolution , currently under active investigation , at the intra-species level . The regulation of transcription of a venom factor reported here is the first described mechanism at the origin of intraspecific variation in immune suppressive properties of a parasite . An open area of research is now to define how common is this mechanism and whether its occurrence is linked to the nature of the virulence factors , is in relation with the taxonomy , or might be parasitoid specific . Parasitoids are major auxiliaries in the control of insect pests and their host range and specificity are widely discussed in the literature [56] , [57] . Estimations of the potential for evolution of virulence molecules and acquisition of new virulence factors in a parasitoid species are essential information to understand and improve the results of biological control assays .
The origins of the L . boulardi ISy ( Gif stock number 486 ) and ISm ( Gif stock number 431 ) isofemale lines have been previously described [41] . Briefly , ISy derives from a single female originating from Brazzaville ( Congo ) while ISm derives from a single female collected in Nasrallah ( Tunisia ) . ISm females are highly virulent against D . melanogaster while parasitism success of ISy females depends on the resistant/susceptible genotype of the host [12] . L . boulardi F1 hybrid females were obtained from crosses between ISm females and ISy males . Both ISm and ISy lines , as well as F1 hybrids , were reared on a susceptible D . melanogaster strain ( Gif stock , number 1333 ) , at 25°C . After emergence , adults of both lines were kept at 18°C on agar medium with honey . For parasitism experiments , the D . melanogaster YR strain ( Gif stock , number 1088 ) , resistant to L . boulardi ISy parasitoids , was used as host [32] . In each experiment , 30 second-instar host larvae ( L2 ) were parasitized during 4 hours by one parasitoid female . The encapsulation ability was estimated 48 hours later by counting the number of encapsulated eggs after dissection of late third-instar larvae . Virulence was expressed as the ratio of non-encapsulated parasitoid eggs to the number of mono-parasitized hosts . The first injection experiment was performed using freshly collected venom from ISm parasitoid females . The venom apparatus of 20 individuals were carefully removed and placed in 20 µl of Ringer's saline solution . The sample was homogenized manually in an Eppendorf tube and the extract was centrifuged at 500×g , 4°C for 5 min to eliminate the cellular debris . 10 µl of the supernatant were then incubated during one hour at 4°C either with the preimmune serum or the specific anti-LbGAP polyclonal antibody , both diluted 1∶10 . Finally , 20 nl of the incubated venom were injected in L2 D . melanogaster YR larvae using a Nanoject II injector ( Drummond Scientific Company , Broomall , PA ) . Approximately 180 larvae were injected then parasitized by ISy parasitoid females as described above but during a two hours period . In the second injection experiment , 20 nl of the preimmune serum or of the specific anti-LbGAP polyclonal antibody , both diluted 1∶10 , were injected in approximately 180 L2 D . melanogaster YR larvae which were then parasitized by ISm females as described above . To obtain the sequence of the LbGAPy cDNA , total RNA was extracted from L . boulardi ISy venom producing tissues using the TRIzol reagent ( Invitrogen ) . RT-PCR was then performed using two specific primers designed from the cDNA sequence of LbGAP [23] , 5′-CATAATTTTCAAATCTTCAACTTTTTTAGA-3′ and 5′-TTAGTCTCTGCACTTTTTCTCA TTTGATGT-3′ . The amplified fragments were cloned into the pCR2 . 1-TOPO vector ( Invitrogen ) and sequenced . Pairwise sequence comparisons were performed using the EMBOSS program Needle at EMBL-EBI ( http://www . ebi . ac . uk/emboss/align/ ) . The search for domains was performed using CDD ( Conserved Domain Database ) at NCBI ( http://www . ncbi . nlm . nih . gov/Structure/cdd/cdd . shtml ) and InterProScan at EMBL-EBI ( http://www . ebi . ac . uk/Tools/InterProScan/ ) . Occurrence and position of the signal peptide cleavage site were predicted using SignalP at CBS ( http://www . cbs . dtu . dk/services/SignalP/ ) and Phobius at SBC ( http://phobius . sbc . su . se/ ) . In vitro GAP assays with recombinant GST-LbGAP and GST-LbGAPy proteins were performed in triplicates using the RhoGAP Assay Biochem Kit from Cytoskeleton Inc . P values were generated by ANOVA followed by pairwise comparisons using pairwise t tests performed with the R software package ( http://www . r-project . org/ ) . The LbGAPy cDNA was inserted into the pGADT7 vector by homologous recombination in yeast strain JD53 ( MATa , his3–200 , leu2–3112 , lys2–801 , trp1–63 , ura3–52 ) . Interactions between LbGAP and mutated forms of RhoA , Rac1 , Rac2 and Cdc42 GTPases were then examined individually by mating as previously described [15] . The plasmids expressing GTPase proteins were tested against the pGADT7 empty vector and the pGADT7-T control vector that encodes a fusion between the GAL4 activation domain and SV40 large T-antigen . Reciprocally , the plasmid producing LbGAPy was tested against the pLex-Lamin control vector . Interactions between LbGAP and Rac1 and Rac2 GTPases were used as positive controls [15] . Interactions were first tested by spotting five-fold serial dilutions of cells on minimal medium lacking histidine and supplemented with 3-amino-triazole at 0 . 5 mM to reduce the number of false positives . Quantification of ß-galactosidase activity in liquid assays was then performed according to the Yeast Protocols Handbook PT3024-1 ( Clontech Laboratories , Inc . ) except that yeast cells were lysed using glass beads ( Sigma ) . P values were generated by ANOVA followed by pairwise comparisons using pairwise t tests performed with the R software package . GST-LbGAP was produced using a previously obtained construct [23] corresponding to the full-length LbGAP cDNA ( without the signal peptide ) cloned into the pGEX-5X-1 vector ( GE Healthcare ) . For production of GST-LbGAPy , a cDNA fragment corresponding to the mature LbGAPy protein was amplified by RT-PCR from total RNA from ISy venom-producing tissues . The amplified fragment was cloned into the pGEX-4T-2 vector ( GE Healthcare ) using EcoRI and XhoI restriction sites . Competent BL21 Escherichia coli cells were subsequently transformed with the recombinant plasmids . The production and purification of the GST-LbGAP and GST-LbGAPy fusion proteins and GST alone were performed according to the GST Gene Fusion System Handbook ( GE Healthcare ) . Immunocytochemical experiments were performed as previously described [15] , using a rabbit anti-LbGAP polyclonal antibody [23] and Phalloidin-X5-FluoProbe 505 ( Interchim ) to visualize F-actin . Total RNA was isolated either from dissected venom apparatus or from the rest of the female bodies ( without venom-producing tissues ) using the TRIzol reagent ( Invitrogen ) , and reverse-transcribed using the iScript cDNA Synthesis Kit ( BioRad ) . qPCR reactions were then carried out on an Opticon monitor 2 ( BioRad ) using the Absolute qPCR SYBR MasterMix Plus for SYBR Green I No ROX ( Eurogentec ) and the specific primers 5′-TGAAAGGGCGAATAATTGATG-3′ and 5′-TTTGGTGGAAGTTTGGAA-3′ for LbGAP and LbGAPy , respectively . PCR conditions were as follows: 50°C for 2 min , 95°C for 10 min , followed by 40 cycles of 95°C for 30 s , 60°C for 30 s and 68°C for 30 s . Each reaction was performed in triplicate and the mean of three independent biological replicates ( venom-producing tissues ) or two independent biological replicates ( rest of the bodies ) was calculated . All data were normalized using the ITS2 ( Internal Transcribed Spacer 2 ) ribosomal sequence as a control and results were analyzed using the ΔCt method . P values were generated by Student's t test with the R software package . Genomic DNA was isolated either from dissected venom apparatus or from the rest of female bodies ( without venom apparatus ) using the DNeasy Blood & Tissue Kit ( QIAGEN ) . qPCR reactions were then carried out as described above . Each reaction was performed in triplicate and the mean of three independent biological replicates was calculated . All data were normalized using the ITS2 ribosomal sequence as a control and analyzed using qBase software ( http://medgen . ugent . be/qbase/ ) . P values were generated by ANOVA followed by pairwise comparisons using pairwise t tests performed with the R software package . Genomic DNA isolation , total RNA isolation , and reverse transcription were performed as described above . The specific primer pairs were 5′-CTCCTGAAGACAGTGTAGAAATTATTC-3′ and 5′-GAATTTTTGAAACATCACTCGAAATA-3′ for LbGAP and 5′-GCTCCT AAAGACAGTATAGCAATTGTTA-3′ and 5′-AGATTAATTGAAACATCATCCGAAAT-3′ for LbGAPy . PCR was performed using GoTaq DNA Polymerase ( Promega ) as follows: 94°C for 2 min , followed by 35 cycles of 94°C for 30 s , 60°C for 30 s and 72°C for 45 s . Serial 1∶10 dilutions were used for cDNA templates . Amplification products were analyzed on a 2% ethidium bromide-stained agarose gel . For dot blot experiments with recombinant GST-LbGAP and GST-LbGAPy proteins , serial 1∶5 dilutions , starting from 10 ng of recombinant protein , were blotted onto a nitrocellulose membrane . GST alone was used as a negative control . Non-specific binding sites were blocked by overnight incubation at 4°C with TBST-2% milk buffer ( 20 mM Tris-HCl pH 7 . 5 , 150 mM NaCl , 0 . 3% Tween 20 ) . The membrane was probed 1 h with the LbGAP antiserum used at a 1∶5000 dilution . After three washes with TBST buffer , specifically bound antibodies were detected using anti-rabbit IgG horseradish peroxidase conjugate ( Sigma ) used at a 1∶15000 dilution for a 1 h incubation period . The membrane was revealed using the chemiluminescent Immobilon Western substrate ( Millipore ) . Relative spot intensities were digitalized and quantified using GeneSnap and GeneTools softwares ( Syngene ) . For slot blot experiments comparing ISm and ISy extracts , 20 female venom apparatus were dissected in 20 µl of Ringer's solution and centrifuged for 2 min at 500×g . The supernatant was then diluted in 200 µl of denaturation solution ( 10 mM Tris-HCl pH 8 , 100 mM NaPO4 , 8 M Urea ) and blotted onto a nitrocellulose membrane . For slot blot experiments comparing ISm and F1 hybrid extracts , only 5 female venom apparatus were used for each strain . The quantity of protein in the samples was determined using the Coo Protein Assay ( Biorad ) and found to be equivalent between the different parasitoid strains . The GenBank accession number for the nucleotide sequence of LbGAPy is GU300066 .
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Evolutionary theories that discuss evolution of virulence in parasite species rely on the assumption that there is additive genetic variation for virulence traits , and that some alleles can then be readily selected , for instance following changes in host resistance genotypes . However , the molecular bases of this variation remain to be deciphered to better estimate the potential for evolution of virulence . This approach has been fruitful to understand evolution of insect resistance to insecticides , with point mutations , gene amplification and changes in expression level as possible sources of genetic variation . Parasitoids , auxiliaries used for biological control of insect pests , provide excellent models to study the coevolutionary processes that may drive changes in parasite host range . We describe here for the first time a mechanism at the origin of the intraspecific variation of virulence in a parasitoid wasp , a model for immune suppressive eukaryotic parasites , through regulation of the transcription of a major virulence factor . This study represents a new step in understanding both the evolutionary origin of virulence factors and their intraspecific variation , which may help optimize biological control success in the field .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"evolutionary",
"biology",
"biochemistry",
"molecular",
"biology"
] |
2010
|
The Origin of Intraspecific Variation of Virulence in an Eukaryotic Immune Suppressive Parasite
|
Previous studies have identified the behavioral responses of Aedes aegypti to irritant and repellent chemicals that can be exploited to reduce man-vector contact . Maximum efficacy of interventions based on irritant chemical actions will , however , require full knowledge of variables that influence vector resting behavior and how untreated “safe sites” contribute to overall impact . Using a laboratory box assay , resting patterns of two population strains of female Ae . aegypti ( THAI and PERU ) were evaluated against two material types ( cotton and polyester ) at various dark:light surface area coverage ( SAC ) ratio and contrast configuration ( horizontal and vertical ) under chemical-free and treated conditions . Chemicals evaluated were alphacypermethrin and DDT at varying concentrations . Under chemical-free conditions , dark material had significantly higher resting counts compared to light material at all SAC , and significantly increased when material was in horizontal configuration . Cotton elicited stronger response than polyester . Within the treatment assays , significantly higher resting counts were observed on chemical-treated dark material compared to untreated light fabric . However , compared to matched controls , significantly less resting observations were made on chemical-treated dark material overall . Most importantly , resting observations on untreated light material ( or “safe sites” ) in the treatment assay did not significantly increase for many of the tests , even at 25% SAC . Knockdown rates were ≤5% for all assays . Significantly more observations of flying mosquitoes were made in test assays under chemical-treatment conditions as compared to controls . When preferred Ae . aegypti resting sites are treated with chemicals , even at reduced treatment coverage area , mosquitoes do not simply move to safe sites ( untreated areas ) following contact with the treated material . Instead , they become agitated , using increased flight as a proxy indicator . It is this contact irritant response that may elicit escape behavior from a treated space and is a focus of exploitation for reducing man-vector contact inside homes .
Dengue , primarily transmitted by Aedes aegypti ( L . ) ( Diptera: Culicidae ) , is presently the most important mosquito-borne viral disease in the world with over 100 countries endemic , mostly in the tropics and subtropics [1] , and an estimated 2 . 5 billion people at risk of infection . There is no vaccine against dengue and there are no drugs to treat dengue hemorrhagic fever and dengue shock syndrome . Hence , vector control remains the cornerstone for the prevention and control of dengue transmission [2] . Patterns of dengue virus transmission are influenced by the abundance , survival , and behavior of the principal mosquito vector , Ae . aegypti . Two main emphases for Ae . aegypti control exist: ( 1 ) reduction of the larval stage through environmental management ( source reduction ) , larvicides and biological control; and ( 2 ) reduction of the adult stage using fumigation and/or residual spray of insecticides . Since the early 1900s [3] , [4] , it has been known that the most cost-effective means of preventing mosquito-borne disease is to target the adult vector , which transmit the pathogen . However , the prevailing paradigm for suppressing Ae . aegypti targets immature mosquitoes , the vast majority of which will not survive long enough to transmit virus [5] . For emergency interventions during dengue outbreaks , targeting the adult vector population by outdoor ultra-low-volume ( ULV ) application of insecticides and/or indoor thermal fogging remain the methods of choice [6] , [7] . However , most control interventions that apply adulticides by space-spraying achieve relatively low effectiveness [8]–[13] . One reason for this reduced effectiveness can be attributed to vector behavior . Aedes aegypti is extensively adapted to exploit the human environment . The female almost exclusively takes blood from humans [14] and most commonly feeds and rests indoors . This species will also lay eggs in available oviposition and larval developmental sites inside the home [15] . This extensive use of the human indoor environment poses unique challenges to traditional adult control methods since chemical applied through outdoor and peridomestic ULV methods must pass through house portals to reach the interior space where the vector can make contact with the insecticide . This approach results in the loss of some chemical prior to reaching the interior space . Control in buildings usually accomplished with indoor residual or space spray are often hampered by limited access into homes and resource limitations [5] . On the other hand , Ae . aegypti's high affinity for the human indoor environment also provides opportunities for innovative approaches to control the adult vector [5] . Aedes aegypti has been characterized as having specific resting preferences based on visual cues ( i . e . , dark colors ) [16] , [17] , and to be significantly attracted by black [18] , yellow , orange and red colors [19] . Studies that have exploited Ae . aegypti's attraction to color contrast ( i . e . simultaneous presentation of two colors , one which mosquitoes are attracted to in order to direct them to a target ) have led to the development of host-seeking adult traps such as the Fay-Prince [20] , counterflow geometry trap [21] , and the BG Sentinel™ trap [22] . Previous studies in Thailand [23] demonstrated the utility of exploiting the resting preference of Ae . aegypti to develop attractant resting boxes for quickly sampling the indoor-resting population of this species . However , in relation to world-wide dengue burden , relatively few laboratory-controlled studies have been performed to quantify these behavioral patterns , and minimal research has been conducted to determine how to exploit this knowledge to reduce Ae . aegypti mosquito densities inside homes where man-vector contact is high [23] . A full description of mosquito behavior provides important information on their role as disease vectors and could serve as the basis for their control . There is growing consensus that the scarce resources available for mitigating tropical public health problems should be utilized in an evidence-based and cost-effective manner [24] . Historically , adult mosquito control using fumigation and indoor residual spray has focused mainly on the lethal actions of chemicals [6] , [7] . However , research shows that there are other chemical actions that break vector-human host contact [25]–[32] . Two such actions are initiating a spatial repellent or deterrent effect , thereby preventing mosquito entry into a treated space ( house ) ; and a contact irritant effect , causing an escape response from a treated space prior to mosquitoes biting humans [32]–[35] . Such non-lethal chemical approaches are being evaluated in the development of a Push-Pull strategy for Ae . aegypti control currently in the proof-of-concept stage in both Peru and Thailand . “Push-Pull” is defined here as a strategy that aims to ( 1 ) prevent mosquito entry into homes through repellency and/or promote their early exit from homes through contact irritancy ( Push ) ; and ( 2 ) trap repelled and/or irritated mosquitoes in the outdoor environment using peridomestic traps ( Pull ) . The goal of the strategy is to target preferred mosquito house entry portals and/or indoor resting sites with standard vector control chemicals ( i . e . chemicals approved by World Health Organization Pesticide Evaluation Scheme for use in vector control ) to make them unsuitable . The approach is to use minimum effective chemical dose and treated surface area coverage to reduce indoor densities of host-seeking ( i . e . , female adult ) Ae . aegypti populations . One component to achieving this goal includes quantifying the patterns of resting behavior of Ae . aegypti exposed to chemical-free and chemical-treated surfaces to define the impact of untreated surfaces on irritancy behavior -is there a shift to resting on “safe-sites” resulting in an attenuated escape response ? The overall aim of the current study was to use a simple laboratory assay to characterize the resting patterns of two geographically distinct female Ae . aegypti population strains in response to material texture ( cotton and polyester ) , at varying dark:light color surface area coverage ratios , using different fabric contrast configuration ( horizontal and vertical ) under chemical-free ( baseline ) , and chemical-treated conditions against alphacypermethrin and DDT . Change in resting behavior between baseline and treatment conditions was quantified in order to determine the potential impact of safe-sites to the contact irritant response .
Two Ae . aegypti test populations ( F2–F5 generations ) were used: one from Pu Teuy Village , Kanchanaburi Province , Thailand ( THAI ) and the other from Iquitos , Peru ( PERU ) . Larvae were reared from eggs shipped to the Uniformed Services University of the Health Sciences ( USUHS ) , Bethesda , USA from Kasetsart University , Bangkok , Thailand or the Naval Medical Research Centre Detachment ( NMRCD ) Iquitos Entomology Laboratory , Iquitos , Peru . At USUHS , all eggs were vacuum-hatched and larvae were sorted into groups of 50 then maintained at 28°C and 80% RH on a 12D∶12L cycle following previously established protocols [36]–[38] . Female pupae were manually sorted from male pupae based on size , and groups of 250 were placed into 1-gallon plastic containers and allowed to emerge to adults . Females ( 5–7 days old ) were maintained with sugar pads saturated in a 10% sucrose solution until 24-hour prior to day of testing . The USUHS colonies were maintained until the F5 generations then refreshed with corresponding F1 field material to help ensure comparability between laboratory and field populations . The laboratory assay device ( i . e . “Box Assay” ) is a modular system based on the HITSS [36] and excito-repellency test chamber [39] . It is composed of metal and Plexiglas boxes ( 30×30 cm ) that can be joined together using metal hinges ( Figure 1 ) . The main test chamber contains material pieces ( either chemical-free or treated ) while the Plexiglas box can be added to quantify spatial repellency ( i . e . , reduced entry ) or contact irritancy ( i . e . , increased exiting ) during mosquito movement studies . For the purpose of this study , only the metal test boxes were used . The metal test box is fitted with a Plexiglas lid to facilitate observation of mosquito behavior during testing . The Plexiglas lid contains a portal covered with dental dam through which mosquitoes are introduced at the beginning of a test replicate and removed following the last observation . The Plexiglas lid can be covered with a sliding tinted cover that can be opened during observational time points and closed afterwards to maintain darkness in the box throughout the rest of the test procedure . Chemicals evaluated in this study , DDT and alphacypermethrin , were chosen based on current status of World Health Organization Pesticide Evaluation Scheme ( WHOPES ) residual chemical recommendations and/or historical use in vector control programs [40] . Chemicals were acquired as technical grade material purchased from Sigma-Aldrich ( St . Louis , MO ) : DDT ( CAS 50-29-3 ) , alphacypermethrin ( CAS 67375-30-8 ) . For resting experiments with chemical , dark material strips were treated with various doses ( 2 . 5; 25 and 250 nmol/cm2 ) of alphacypermethrin or DDT diluted in acetone solution . Assay concentrations were selected according to previous behavioral studies with these chemicals [32] , [33] , [36] . Treatment solutions were applied evenly to individual material strips using a micropipette . Additional material strips were treated with acetone solvent to serve as untreated controls . All fabric pieces were treated approximately 30 min prior to initiating the first replicate of the assays and allowed to air-dry on a drying rack for at least 15 min before being inserted into the metal test boxes . New treatment and control material strips were prepared daily . The materials used in the resting behavior studies consisted of either black or white cotton ( Natural Charm 43/44” wide 100% cotton 68×68 D/R-black and white , Bruce Variety , Bethesda , MD , USA ) ; and green or white 100% polyester netting ( BioQuip Products , Rancho Dominguez , CA , USA; mesh size 24×20/inch ) . Three variables that could influence resting behavior were evaluated for each Ae . aegypti strain: ( 1 ) surface area coverage ( SAC ) ratio of dark to light material; ( 2 ) vertical versus horizontal configuration of dark fabric strips; and ( 3 ) material texture . A total of six replicates were performed at each dark : light coverage ratio and contrast configuration ( horizontal and vertical ) for both material types ( cotton and polyester ) under chemical-free and treated conditions . Preference for upper versus lower positioning was also recorded during horizontal configuration studies . A chalk line was used to discern “upper” versus “lower” regions during 100% coverage experiments . Depending on the experiment type , chemical-free ( control and baseline assays ) and chemical-treated ( treatment assays ) cotton or polyester panels were placed into corresponding metal test boxes at 100% dark , 100% white , 75%∶25% , 50%∶50% , and 25%∶75% dark : light ( D:L ) SAC ratios ( Figure 2 ) . All material panels were attached to the assay walls using magnets . For each test assay , a matched control with chemical-free ( solvent-treated ) dark material was performed simultaneously . Separate groups of 10 females were introduced into the metal test box and counts made of resting locations every 2 minutes , during a 10 minute sampling period . Six replicates were performed for each test type . The four sides of the metal box were designated as rear , front , right and left , facilitating the recording process . In each test , resting locations were recorded as: 1 ) dark or light material; 2 ) magnet; 3 ) floor and; 4 ) Plexiglas lid . In addition , the number of mosquitoes flying inside the metal box , and those knocked down ( KD ) ( defined as lying on their side or back and unable to right themselves when the test box was gently tapped ) were also tallied . All testing was performed under controlled temperature ( 28–30°C ) and relative humidity ( 50–60% ) . For assays containing chemical treatments , test boxes were cleaned at the end of each day of testing with acetone and allowed to air-dry overnight before reuse with a new chemical or a different chemical concentration . All analyses were performed using SPSS 16 . 0 and SAS 9 . 2 . Counts made at each 2 min observation period from all six replicates for each test assay were summed and calculated as the proportion of mosquitoes observed resting for each of the specified observation locations as well as those exhibiting flying and knockdown responses . Comparisons among observations within a single test box ( control and treatment ) were performed using chi-square statistical analyses ( observed versus expected resting on dark or light material ) with a 2×2 contingency table at a 95% confidence level . The effects of material configuration were determined by comparing the difference in the proportion of mosquitoes resting on the dark material strips placed horizontally versus those resting on the strips placed vertically . For horizontal configuration experiments , proportions resting on upper and lower dark strips were also compared . The effect of texture was determined by comparing proportions resting on dark cotton versus dark polyester in a separate test . Percent change in resting on treated dark surfaces and untreated surfaces ( using proportions resting on untreated light material , KD and flying as indicators ) were quantified by comparing proportions observed in the treatment box with matched controls ( chemical-free condition ) . Pearson correlations were also used to determine relationships between chemical test dose and change in resting behavior and/or proportion flying; and relationships between SAC and change in resting behavior and/or proportion flying at each chemical test dose .
A full understanding of adult vector ecology and behavior is vital in developing novel control strategies as well as optimizing existing tools . It is general knowledge that Ae . aegypti adults prefer to rest in dark , damp locations in households , and are also attracted to black colors [16]–[18] and , in fact , the development of oviposition , host-seeking and/or other adult traps are based on these observations [20]–[23] , [41]–[43] . However , few standardized studies have been performed to quantify such behavioral patterns in an attempt to reduce adult mosquito densities inside homes , a site of disease transmission [23] , [42] . With current suggestions that sub-lethal chemical approaches to vector control ( i . e . contact irritancy ) may pose viable options to reduce disease [32]–[35] , [44] , it is important to characterize minimal effective doses of irritant chemicals and the relationship between surface area coverage of these doses and the behavioral responses that they elicit ( i . e . , rapid escape from inside homes ) . Current adult vector control approaches such as insecticide treated bed nets , and/or clothing rely on human hosts as the attractant or bait to lure mosquitoes into contact with the treated material long enough to deliver the lethal dose of the insecticide [45] . However , when relying on the treatment of resting sites , such as the interior house walls , to reduce man-vector contact through an irritant response , interaction of the vector with these treated surfaces is facultative . Untreated areas in the house or safe-sites may be available and/or preferred for resting [12] , [46] thus minimizing the impact of the intervention . It is vital therefore , to understand the drivers of these resting preferences in order to exploit and maximize the effects of irritant chemicals on vector escape responses . Such strategies will guide development of cost-effective tools for the future . The present study quantified the resting patterns of two Ae . aegypti female populations ( THAI and PERU ) under both chemical-free and treatment conditions using a simple laboratory assay . During the chemical-free baseline trials , several variables were evaluated to include material type ( cotton and polyester ) , dark : light color surface area coverage ( SAC ) , and fabric configuration ( horizontal , vertical ) . Not surprisingly , results indicate that both mosquito strains were observed resting preferentially on dark versus light colored material against both material types . These patterns were consistent using both the vertical and horizontal configuration study designs . The magnitude of this response was measured as greater than expected proportions of resting observations on the dark material even at the 25% SAC ratio despite the availability of alternate resting sites , or other behavioral responses such as flight . Similar findings have been described during our experimental hut validation studies in Thailand [Thainchum et al . unpublished data] and Peru [Castro et al . unpublished data] where most Ae . aegypti preferred to rest on dark material rather than light , regardless of fabric type even at 25% and 50% SAC . Although horizontal configuration enhanced resting on both dark cotton and polyester material strips in the current study , as well as under field conditions in experimental huts [Thainchum et al . unpublished data] , no consistent preference was observed between upper and lower locations of the dark material within the laboratory assay chamber . This may be due to the relatively small size of the assay that created a spatial bias for the test system – i . e . , the laboratory assay dimensions may have precluded substantial differences in height between upper and lower wall portions . However , similar observations have been made in our experimental hut studies where based on observations from upper and lower wall heights , greater proportions of female Aedes aegypti populations were observed resting on lower portions of the wall when exposed to cotton material whereas against polyester , upper wall portions were preferred ( unpublished data ) . An explanation for the variation in resting patterns between the two material types in the current study may include the variation in the microclimate within the test box . Previous studies under laboratory conditions have reported similar findings using Anopheles and Culex mosquitoes in which they preferred to rest on lower portion of a test box that was cooler than that of the upper portion [47] . Unfortunately , it is not possible to validate this theory using the datasets of the current study because environmental parameters were only measured from a central location inside the bioassay room rather than along the wall surfaces within the test box . Future experiments should integrate microclimate data to better understand behavioral responses . The fact that cotton enhanced resting on the dark strips as compared to polyester indicates that: 1 ) the green color of the polyester did not provide as much contrast to the white background as the black color of the cotton; 2 ) the weave or texture of the cotton provides enhanced tactile cues; or 3 ) material-specific moisture absorption properties exist under the conditions in which the assay was conducted ( i . e . cotton retains more moisture than polyester ) . When evaluating green cotton versus green polyester simultaneously , cotton still enhanced resting on the dark strips . This finding suggests that the differential resting preference observed between cotton and polyester may not be due to variations in color contrast between material types , but rather is the result of their texture and/or moisture absorption properties . Cotton exhibits greater moisture absorption than that of polyester [48] . It is interesting to note that studies under field conditions in Thailand and Peru are also indicating an overall general decrease in resting when polyester is used versus cotton under chemical-free conditions [Thainchum et al . ; Castro et al . unpublished data] . Such information could be vital in optimizing various vector control tools and could be most beneficial for products designed to target attraction/resting behaviors . Observations made within the treatment metal boxes during chemical trials indicate that , knockdown responses in all test assays were low ( ≤5% ) even at high chemical dose and treatment area coverage ( i . e . , 75% and 100% ) . Low KD even at test doses higher than WHO recommended field application rate for alphacypermethrin ( ≈7 nm/cm2 ) is probably due to a reduced resting on the treated material and consequentially an increase in proportion of mosquitoes flying ( irritated/agitated ) . It must be noted that test populations were only exposed to the treated surfaces for a total of 10 min , well below the standard 1 hour used in toxicity assays [49] . Also , as the THAI Ae . aegypti strain has been characterized as pyrethroid tolerant and DDT resistant [50] , [51] , it was expected that KD/mortality would be low in these test populations . More importantly , the THAI strain still exhibited a contact irritant response ( indicated by increased flying ) when exposed to both alphacypermethrin and DDT . These results indicate that sub-lethal approaches to vector control may be effective in resistance management . Perhaps most important for operational significance is the observation that was made in the test chamber during chemical trials indicating that both mosquito strains continued to rest in greater proportions on dark chemical-treated material versus safe-sites ( i . e . chemical-free light material , assay lids and floor ) when any dose of either alphacypermethrin or DDT were used . Even under test conditions in which shifting to safe-sites were expected ( i . e . , 25% SAC ) , results show no consistent increase in resting counts on chemical-free material . As expected , however , when observations were compared between treatment and matched control assays , significantly fewer mosquitoes were observed resting overall on the dark material treated with chemical . For all chemical evaluations , the proportion of mosquitoes observed flying was significantly increased in the treatment assay as compared to matched control regardless of the material type used , surface area coverage and configuration of the treated areas within the box . Again , these findings indicate that under current test conditions , Ae . aegypti did not simply move to safe-sites ( untreated areas ) following contact with chemical-treated material but were clearly agitated as measured by an increased flight response . It is this contact irritant response that may elicit escape behavior from a treated space and can be exploited for reducing man-vector contact inside homes . Any residual chemical that is applied to indoor surfaces and has sufficiently strong irritant properties would potentially disrupt the normal resting and may affect the feeding pattern of a vector . These actions could consequently reduce vector – human contact because of rapid escape from inside human dwellings [35] . Such a contact irritant response is well documented in previous field experimentation [32] , [52] , [53] . While the designs were different in these studies , results from each indicate a rapid escape of mosquitoes from inside experimental huts in response to irritant chemical applications and is the basis for the current laboratory conclusion . The challenge is to ensure that agitation , observed in the current study , does not increase biting on humans prior to escape as this would be counterproductive to intervention impact . Ongoing laboratory studies using the box assay are evaluating escape responses under similar current test conditions to measure the effect of focal treatment on mosquito movement away from a treatment source . It should be noted that it was not the aim of the current study to compare resting behavior patterns between THAI versus PERU Ae . aegypti strains . Each strain was evaluated independently as results from each are currently being validated under field conditions at strain-specific locales ( i . e , Kanchanaburi and Iquitos , respectively ) . However , future studies could investigate the relationship between behavioral phenotype and genetic characteristics of each geographical strain to explore differences that may exist in the resting behavior in response to chemical actions . This information would be useful in understanding the varying challenges in successful implementation of sub-lethal vector control strategies designed to have impact on mosquito populations from different geographic locations . In summary , results from the current study indicate that both strains of Ae . aegypti preferred to rest on dark versus light-colored surfaces during both chemical-free and treated assays , and that agitation ( i . e . , flight response ) was elicited under chemical conditions rather than an increase in resting on untreated safe-sites , even at the lowest 25% D:L coverage . To our knowledge , this is the first attempt to quantify resting responses to sub-lethal doses of irritant chemicals at different treatment surface area coverage . A similar concept of using minimum chemical dose and coverage is also being applied to measure the spatial repellency actions of chemicals to prevent mosquito entry into homes . Pertinent to the larger Push-Pull project under evaluation , laboratory observations have identified those variables that may have the greatest effect in eliciting an escape response following tarsal contact with a chemical-treated surface under experimental conditions . These factors include which material ( cotton versus polyester ) , and configuration ( horizontal versus vertical ) result in the highest resting response and thereby initiate flight when treated with chemical . Although encouraging , it is the increase in flying that needs to be optimized and to elicit this response in such a way as to minimize opportunities for biting humans . Quantifying vector avoidance of an irritant chemical , through observations of the resting response on untreated and treated surfaces , has been a vital initial component in estimating the likelihood of success of a contact irritant Push-Pull strategy , especially one focused on the use of minimal treatment coverage area . Findings in the current study , together with ongoing field validation , indicate such an approach could be successful .
|
Aedes aegypti , the primary vector mosquito of dengue virus , typically lives near or inside human dwellings , and feeds preferentially on humans . The control of this mosquito vector remains the most important dengue prevention method . The use of chemicals at levels toxic to mosquitoes is currently the only confirmed effective adult vector control strategy with interventions usually applied following epidemic onset . However , research indicates that sub-lethal chemical approaches to prevent human-vector contact at the house level exist: contact irritancy and spatial repellency . The optimum efficacy of an intervention based on contact irritant actions of chemicals will , however , require full knowledge of variables that will influence vector resting behavior and thereby chemical uptake from treated sources . Here we characterize the resting patterns of female Ae . aegypti on two material types at various dark:light surface area coverage ratios and contrast configurations under chemical-free and treated conditions using a laboratory behavioral assay . Change in resting behavior between baseline and treatment conditions was quantified to determine potential negative effects of untreated surfaces ( “safe sites” ) when irritant responses are elicited . We show that treatment of preferred resting sites with known irritant compounds do not stimulate mosquitoes to move to safe sites after making contact with treated surfaces .
|
[
"Abstract",
"Introduction",
"Methods",
"Discussion"
] |
[
"entomology",
"vector",
"biology",
"biology",
"microbiology",
"zoology",
"viral",
"vectors"
] |
2011
|
Effects of Irritant Chemicals on Aedes aegypti Resting Behavior: Is There a Simple Shift to Untreated “Safe Sites”?
|
Yersinia pestis is a facultative intracellular pathogen that causes the disease known as plague . During infection of macrophages Y . pestis actively evades the normal phagosomal maturation pathway to establish a replicative niche within the cell . However , the mechanisms used by Y . pestis to subvert killing by the macrophage are unknown . Host Rab GTPases are central mediators of vesicular trafficking and are commonly targeted by bacterial pathogens to alter phagosome maturation and killing by macrophages . Here we demonstrate for the first time that host Rab1b is required for Y . pestis to effectively evade killing by macrophages . We also show that Rab1b is specifically recruited to the Yersinia containing vacuole ( YCV ) and that Y . pestis is unable to subvert YCV acidification when Rab1b expression is knocked down in macrophages . Furthermore , Rab1b knockdown also altered the frequency of association between the YCV with the lysosomal marker Lamp1 , suggesting that Rab1b recruitment to the YCV directly inhibits phagosome maturation . Finally , we show that Rab1b knockdown also impacts the pH of the Legionella pneumophila containing vacuole , another pathogen that recruits Rab1b to its vacuole . Together these data identify a novel role for Rab1b in the subversion of phagosome maturation by intracellular pathogens and suggest that recruitment of Rab1b to the pathogen containing vacuole may be a conserved mechanism to control vacuole pH .
Yersinia pestis is a facultative intracellular pathogen and causative agent of the disease known as plague . There have been three human plague pandemics in history; the most notable being the Black Death in the 14th century [1 , 2] . Y . pestis can infect humans either through the bite of an infected flea or inhalation of contaminated aerosols . Flea inoculation can lead to the development of bubonic plague , a form of plague highlighted by bacterial dissemination to , and replication within , lymph nodes [1] . Inhalation of Y . pestis contaminated aerosols can result in rapid colonization of the lungs and development of pneumonic plague [1] . Both forms of plague are associated with acute disease progression and high mortality rates in the absence of timely antibiotic treatment . Furthermore , the potential for person-to-person transmission and use as a biological weapon in the absence of a vaccine highlights the risks associated with this pathogen [3] . During its natural life cycle , Y . pestis cycles between two different hosts , the mammal and the flea . The bacterium requires different virulence factors to colonize each host , and coordinates the expression of these factors accordingly [1] . Y . pestis has several well characterized antiphagocytic mammalian virulence factors , such as the Ysc type three secretion system ( T3SS ) , secreted Yop effectors and the Caf1 capsule [1] . However , these virulence factors are down regulated in the flea vector and at the time of initial colonization of the mammalian host [1] . During this transitional period , Y . pestis is highly susceptible to phagocytosis by macrophages and neutrophils [4 , 5] . Initial colonization of Y . pestis induces a rapid and early influx of neutrophils to the site of infection [4 , 6] . Upon phagocytosis by neutrophils , Y . pestis is readily killed by these professional phagocytes [7–9] . However , Y . pestis has demonstrated an increased ability to survive phagocytosis by monocytes and macrophages [4 , 5 , 10–12] . Upon entry into the macrophage , Y . pestis actively circumvents the natural maturation of the phagolysosome by remodeling the phagosome into a hospitable replicative niche called the Yersinia containing vacuole ( YCV ) [11–15] . In vitro studies have highlighted three key characteristics of the biogenesis of the YCV . First , Y . pestis is able to actively inhibit the normal acidification of the phagosome and maintain a pH between 6 . 5–7 . 5 within the YCV throughout the course of intracellular infection [12] . Second , a significant portion of YCVs appear to become autophagosomes , which is highlighted by colocalization with LC3-II and the presence of double membranes surrounding the bacteria [12 , 16] . While the contribution of autophagy to intracellular survival is unclear , data indicates that autophagy contributes to the metabolism of intracellular bacteria [16 , 17] . Finally , approximately eight hours after phagocytosis , the tight fitting vacuolar membrane of the YCV begins to expand in size to form a spacious vacuolar compartment that can be observed by both light and electron microscopy [5 , 12 , 13 , 18] . Bacterial replication within the YCV usually coincides with spacious vacuole formation . Importantly , while the fate of Y . pestis in the macrophage has been characterized , the mechanisms used to generate the YCV and avoid macrophage killing have not been defined . The ability of Y . pestis to survive within macrophages also appears to impact virulence of the bacterium . In vivo , intracellular Y . pestis are recovered from macrophages isolated from both infected nonhuman primates and rodents , but rarely from neutrophils isolated from the same animals [7 , 19 , 20] . Ye and colleagues further showed lower bacterial burdens in transgenic MaFIA mice selectively depleted of macrophage/dendritic cell populations , suggesting that macrophages are required to establish acute infection [21] . Y . pestis phoPQ mutants , which are defective for intracellular survival , are also attenuated during subcutaneous infection of BALB/c ( 75-fold change in LD50 ) and Swiss Webster mice ( no change in LD50 but a significant delay in time to death for mutant infected animals ) [22 , 23] . Moreover , macrophages isolated from canines , a species that are relatively resistant to plague [24] , are significantly more capable in killing Y . pestis than macrophages isolated from laboratory mice , a species highly susceptible to plague , suggesting that the ability of macrophages to kill Y . pestis may contribute to resistance to infection [18] . Together , these data highlight the importance of Y . pestis survival within the macrophage during pathogenesis . Rab GTPases are the largest member of the Ras Superfamily of small guanine triphosphatases and are central mediators of vesicle trafficking within eukaryotic cells [25 , 26] . These GTPases mediate vesicle trafficking by cycling through active GTP-bound and inactive GDP-bound conformations [25 , 26] . When bound to GTP , the Rab protein integrates into specific vesicle membranes to mediate the trafficking of that vesicle through interactions with other trafficking proteins . Hydrolysis of the bound GTP to GDP results in extraction of the Rab from the membrane . While approximately 60 different Rab proteins have been identified , the contributions of only a few Rabs to specific vesicle trafficking steps have been experimentally described . For example , Rab5 , Rab7 , and Rab9 have been well studied as key mediators of important steps in the phagosome maturation process [27–32] . Rab5 is recruited to the early endosome/phagosome and is required for phagocytosis [27–32] . Following phagocytosis , Rab5 disassociates from the early endosome and Rab7 is recruited to the endosome to facilitate recruitment of Rab9 and subsequent fusion with the lysosome [27–32] . A single disruption in the recruitment of a Rab protein to the maturing vesicle can stall and even terminate trafficking of that particular endocytic vesicle to its intended destination . Due to the central role of Rab proteins for endosome sorting and phagosome maturation , many intracellular pathogens target Rab proteins to subvert these processes ( see [25] for review ) . A classic example of Rab manipulation is seen in Mycobacterium infection of macrophages . M . avium and M . tuberculosis alter the normal distribution of Rab5 and Rab7 on their vacuole—retention of Rab5 and exclusion of Rab7 –to inhibit phagosomal fusion with the lysosome and subsequent killing of the bacteria [33–38] . More recently , Rab1 has emerged as a common target required for the intracellular survival of many pathogens [37 , 39–49] . Rab1 has two isoforms , Rab1a and Rab1b , which share 92% amino acid similarity and are thought to be functionally redundant [50 , 51] . Both isoforms have been shown to be involved in ER-to-Golgi trafficking [43 , 52] . More recently Rab1a has been associated with proper endosome sorting during receptor mediated endocytosis and Rab1b has also been linked to autophagosome formation [44 , 53–56] . Several pathogen containing vacuoles ( PCVs ) have been shown to associate with Rab1 , and this recruitment is essential for subsequent survival of the pathogens contained within the PCV [39–47 , 57] . Coxiella burnetii requires Rab1 for the Coxiella replicative vacuole ( CRV ) to expand in both Chinese hamster ovary ( CHO ) and RAW264 . 7 macrophage cells [39] . This expansion is significantly hindered in the presence of a GTP restricted form of Rab1 [39] . Similarly , Anaplasma phagocytophilum also recruits Rab1 directly to the Anaplasma containing vacuole ( APV ) and it has been speculated that recruitment of Rab1 to the APV allows the bacteria to hijack endocytic trafficking [43] . Perhaps the best studied subversion of Rab1 by a pathogen comes from Legionella pneumophila . Rab1 has been shown to accumulate on the L . pneumophila containing vacuole ( LCV ) as early as 10 min after bacterial uptake and Rab1 knockdown has been shown to inhibit L . pneumophila intracellular replication [40 , 42 , 46] . Furthermore , several L . pneumophila secreted effectors have been identified that specifically target and modify Rab1 to alter its localization [40 , 42 , 46 , 47 , 57–62] . In contrast to the requirement of Rab1 for the survival of these intracellular pathogens that exist within vacuoles , Shigella flexneri , which replicates in the host cytoplasm , is hindered by Rab1 [41] . Inactivation of Rab1 by S . flexneri is critical for bacterial survival and is mediated by the VirA/EspG secreted effector family [41] . Together , these studies suggest a distinct role for host Rab1 GTPases for intracellular survival of pathogens that replicate within vacuolar compartments . Since Rab1 appears to be targeted by several pathogens that reside within vacuoles in order to survive intracellularly , we investigated the role of Rab1 in the survival of Y . pestis within macrophages . We demonstrate that siRNA knockdown of Rab1b in macrophages infected with Y . pestis significantly increases YCV acidification and association with the lysosomal marker Lamp1 , resulting in decreased intracellular survival of Y . pestis . Furthermore , we show Rab1b is recruited to the YCV , suggesting a direct interaction with Rab1b is required for proper YCV maturation . Importantly , Rab1b is the first host protein to be identified that is required by Y . pestis to alter phagosome maturation and YCV acidification and impact the ability of this pathogen to survive within the eukaryotic cell . Finally , we also demonstrate for the first time that Rab1b recruitment to the L . pneumophila containing vacuole also impacts vacuole pH , suggesting a conserved mechanism for the recruitment of Rab1b to pathogen containing vacuoles .
Since Y . pestis exists within a vacuolar compartment within macrophages [5 , 11 , 14] , and Rab1 has been linked to survival of several other intracellular pathogens that exist within vacuoles [39 , 40 , 43–46 , 48] , we sought to determine if Rab1 is required for Y . pestis intracellular survival . Toward this goal , we initially screened whether either isoform of Rab1 is required for Y . pestis to survive in macrophages . RAW264 . 7 macrophages were transfected with either Rab1a or Rab1b specific siRNAs ( pool of 3 siRNAs targeting each gene ) . 48 h after transfection , macrophages were infected with Y . pestis CO92 pCD1 ( - ) LuxPtolC , which contains a bioluminescent bioreporter to monitor Y . pestis numbers [63] . Extracellular bacteria were killed with gentamicin , and intracellular bacterial survival was monitored via bioluminescent signal ( Fig 1A ) . While no change in Y . pestis bioluminescence was observed in Rab1a siRNA treated cells compared to scrambled siRNA treated controls , we observed a significant decrease in bioluminescence in Rab1b siRNA treated cells , indicating that Rab1b , but not Rab1a , is required for Y . pestis survival within macrophages . To confirm Rab1b is required for Y . pestis intracellular survival , RAW264 . 7 macrophages were transfected with a single Rab1b siRNA optimized for Rab1b knockdown and cell viability ( S1 Fig ) and infected with Y . pestis CO92 pCD1 ( - ) LuxPtolC 48 h post-transfection . As a positive control , we also infected macrophages transfected with Copβ1 siRNA . Copβ1 is a component of the cotamer complex and has been shown to alter both invasion and survival of other intracellular pathogens [64 , 65] . As expected , Copβ1 knockdown resulted in a significant decrease in intracellular Y . pestis CO92 pCD1 ( - ) LuxPtolC bioluminescence at 10 h post-infection as compared to scramble siRNA treated cells ( Fig 1B; p≤0 . 0001 ) . Rab1b knockdown also resulted in a significant decrease in bioluminescent signal; Y . pestis CO92 pCD1 ( - ) LuxPtolC bioluminescence was ~50% less in Rab1b siRNA treated cells ( Fig 1B; p≤0 . 0001 ) . To confirm that Y . pestis CO92 pCD1 ( - ) LuxPtolC bioluminescence accurately represents viable intracellular bacteria , cells were lysed and bacterial numbers were determined by conventional serial dilution enumeration ( Fig 1C ) . Conventional enumeration supported our bioluminescent data and demonstrated a significant decrease in viable intracellular colony forming units ( CFU ) in Rab1b siRNA treated cells ( p≤0 . 001 ) . No differences in survival were observed if bacteria were grown at 37°C prior to infection ( S2 Fig ) . Importantly , the direct correlation between bioluminescent signal and bacterial enumeration support the use of bioluminescent data to monitor intracellular Y . pestis numbers . To confirm that the pCD1 encoded Ysc type three secretion system ( T3SS ) does not impact Rab1b mediated Y . pestis survival , Rab1b transfected cells were also infected with Y . pestis KIM D-19 LuxPtolC , which contains the pCD1 plasmid and the Ysc T3SS , and bacterial survival was monitored by bioluminescence and conventional bacterial enumeration ( Fig 1E and 1F ) . As observed for Y . pestis CO92 pCD1 ( - ) LuxPtolC , we observed an ~50% decrease in Y . pestis KIM D-19 LuxPtolC survival in Rab1b siRNA treated cells ( p≤0 . 001 ) . We also monitored Y . pestis intracellular bioluminescence temporally over the course of the infection to determine how early during infection Y . pestis intracellular survival was impacted by Rab1b knockdown . This analysis revealed that intracellular bacterial numbers for both strains were significantly decreased in Rab1b treated cells as early as 2 h post-infection , which is the earliest time point we can monitor after gentamicin removal ( Fig 1D and 1G; p≤0 . 001 ) . Finally , to determine if the Rab1b impact on intracellular survival is conserved in the Yersinia genus , transfected macrophages were infected with Y . pseudotuberculosis and Y . enterocolitica . As observed for Y . pestis , both enteric species were attenuated in survival when Rab1b was knocked down ( S3 Fig ) . Together these data demonstrate that Rab1b is required for Yersinia intracellular survival , which is independent of the Ysc T3SS , and bacterial survival is impacted by Rab1b very early during the infection process . We observed a difference in Y . pestis intracellular numbers in Rab1b siRNA treated cells within 2 h of macrophage infection ( Fig 1D and 1G ) . The difference in recovered bacteria at this early time point could be due to an inability of Y . pestis to avoid phaogolysomal killing in the absence of Rab1b . However , Rab1b may also be required for efficient phagocytosis and the difference in Y . pestis numbers at 2 h post-infection could be a result of less bacteria gaining entry into the macrophages prior to gentamicin treatment . Because phagolysosome fusion and bacterial killing can occur within 120 minutes of phagocytosis [25 , 27] , we could not rely on the conventional gentamicin protection assay , which requires a 1 h incubation period , to differentiate between invasion and bacterial killing in Rab1b siRNA treated cells . Therefore , we used a differential staining procedure to specifically label extracellular Y . pestis and determine if Rab1b knockdown impacted Y . pestis invasion of macrophages by confocal microscopy . Rab1b siRNA transfected RAW264 . 7 macrophages were infected with Y . pestis CO92 pCD1 ( - ) pGEN-PEM7::DsRED [66] , which constitutively expresses the DsRED fluorescent protein . At 20 and 80 min post-infection , cells and total bacteria were fixed with paraformaldehyde . Extracellular bacteria were then specifically labeled with anti-Y . pestis polyclonal antibody and Alexa Fluor 488 anti-rabbit secondary antibody ( Fig 2A ) . As a positive control , macrophages were treated with Copβ1 siRNA , which has been previously shown to be required for efficient phagocytosis [64] . As expected , cells treated with Copβ1 had significantly less intracellular Y . pestis than scrambled siRNA treated macrophages at both 20 and 80 min post-infection ( Fig 2B and 2C; p≤0 . 001 ) . Conversely , we observed no difference in the proportion of intracellular Y . pestis in Rab1b siRNA treated cells compared to scrambled siRNA treated cells . These data demonstrate that Rab1b is not required for phagocytosis of Y . pestis and suggest that the differences in intracellular bacterial numbers in Rab1b siRNA treated cells is due to a decreased ability of Y . pestis to avoid macrophage killing in the absence of Rab1b . A hallmark characteristic of Y . pestis infection of the macrophage is that the bacterium is able to rapidly subvert normal acidification of the YCV [12] . Because acidification is one of the earliest steps in phagosome maturation and is required for both efficient lysosomal fusion and degradation of phagolysosomal contents [27] , we next investigated whether Rab1b is required for Y . pestis to avoid YCV acidification . RAW264 . 7 macrophages were transfected with Rab1b siRNA and then treated with Lysotracker Red DND-99 prior to infection with Y . pestis CO92 pCD1 ( - ) pGEN222 , which constitutively expresses EGFP . Lysotracker Red DND-99 fluorescence is pH dependent ( fluoresces below pH 5 . 5 ) , and therefore , allows for identification of acidified vacuoles . As Y . pestis inhibition of YCV acidification is an active process , untransfected cells were infected with paraformaldehyde killed Y . pestis CO92 pCD1 ( - ) pGEN222 to serve as a positive control for YCV acidification . As previously reported for untransfected macrophages [12] , Y . pestis CO92 pCD1 ( - ) pGEN222 efficiently avoided YCV acidification in scramble siRNA treated macrophages , with <25% of Y . pestis found within acidified vacuoles by 80 min post-infection ( Fig 3 ) . This was significantly lower than paraformaldehyde killed Y . pestis , which were already within acidified vacuoles >80% of the time by 20 min post-infection ( p≤0 . 01 ) . The ability of Y . pestis to inhibit YCV acidification was greatly attenuated in Rab1b knocked down cells , where ~70% of the bacteria were observed within acidified vacuoles within 20 min post-infection ( p≤0 . 01 ) . Furthermore , Y . pestis remained within acidified vacuoles in Rab1b siRNA treated macrophages at 80 min post-infection . These data demonstrate that Y . pestis requires the host Rab1b GTPase to inhibit or avoid YCV acidification . Acidification of the phagosome precedes or coincides with fusion to lysosomes and degradation of foreign particles such as bacteria [27] . As Rab1b knockdown resulted in increased acidification of the YCV , we next determined if Rab1b is required for Y . pestis to avoid fusion with lysosomes . RAW264 . 7 macrophages were transfected with Rab1b siRNA and infected with live or paraformaldehyde killed Y . pestis CO92 pCD1 ( - ) pGEN-PEM7::DsRED . At 20 and 80 min post-infection , cells were washed , fixed with paraformaldehyde , and stained with anti-Lamp1 antibody , a marker for lysosomal fusion ( Fig 4A ) . In scrambled siRNA treated cells , we observed minimal association of live Y . pestis with Lamp1 ( <25% ) at 20 and 80 min post-infection , indicating limited association between the YCV and lysosomes at these time points ( Fig 4B and 4C ) . As observed for YCV acidification , there was a significant increase in the association between Lamp1 and paraformaldehyde killed Y . pestis ( >60% ) , supporting an active avoidance of lysosomal fusion by Y . pestis during macrophage infection ( Fig 4B and 4C; p≤0 . 001 ) . Rab1b knockdown also significantly altered Lamp1 association with the YCV compared to scramble siRNA ( Fig 4B and 4C; p≤0 . 001 and p≤0 . 01 , respectively ) . At 20 min post-infection , Lamp1 associated with ~55% of YCVs in Rab1b siRNA treated cells , and was maintained at this elevated level at 80 min post-infection . These data indicate that Rab1b is required not only for Y . pestis to inhibit YCV acidification but also to avoid lysosomal fusion . Importantly , the ~2-fold increase in association with Lamp1 directly correlates to a similar 2-fold decrease in Y . pestis survival in Rab1b siRNA treated macrophages ( Fig 1 ) . Autophagy has been linked to both Y . pestis and Y . pseudotuberculosis intracellular infection and may be required for sustained bacterial metabolism within cells [12 , 16] . Furthermore , studies have shown a recruitment of LC3 , a marker for autophagosomes , to the YCV during Y . pseudotuberculosis infection of HeLa cells and BMDMs [16 , 17] . Recently , Huang and colleagues demonstrated a potential role for Rab1b in autophagy and intracellular survival of Salmonella enterica Typhimurium [44] . Given the link of Rab1b to autophagy and autophagy to Yersinia intracellular infection , we next investigated if knockdown of Rab1b impacted early association of LC3 to the YCV during macrophage infection . RAW264 . 7 macrophages were transfected with Rab1b siRNA and infected with live or paraformaldehyde killed Y . pestis CO92 pCD1 ( - ) pGEN-PEM7::DsRED . 20 and 80 min post-infection cells were washed , fixed with paraformaldehyde , and stained with anti-LC3 antibody ( Fig 5A ) . In contrast to reported infection of epithelial cells with Y . pseudotuberculosis [17] , we observed a very low incidence in the association between live or killed Y . pestis with LC3 during early stages of macrophage infection ( Fig 5B and 5C ) and this association was not significantly altered in Rab1b siRNA treated cells ( ~20% association in all samples ) . These data support previous data that LC3 association with the YCV is lower in macrophages than epithelial cells [16 , 17] and demonstrate that Rab1b knockdown does not alter YCV-LC3 association during the early stages of Y . pestis infection when we observe changes in YCV maturation and intracellular survival of the bacteria . Rab GTPases mediate vesicular trafficking through direct interactions with vesicle membranes ( see [25 , 26] for review ) . Therefore , we next sought to determine whether Rab1b is recruited to the YCV during Y . pestis infection . Because Rab interactions with membranes are transient , we transfected RAW264 . 7 macrophages with a GFP-labelled , constitutively active form of Rab1b [eGFP-Rab1b ( CA ) ] . eGFP-Rab1b ( CA ) contains a mutation in the GTP binding domain that inhibits the hydrolysis of GTP , resulting in retention of the protein in the membrane in which the Rab GTPase is recruited [43 , 46 , 67 , 68] . Twenty-four hours after transfection , macrophages were infected with either live or PFA killed Y . pestis CO92 pCD1 ( - ) pGEN::mCherry or E . coli K12 pGEN::mCherry , which constitutively express the mCherry fluorescent protein . Cells were washed and fixed with paraformaldehyde at 20 and 80 min post-infection and analyzed by confocal microscopy to determine localization of eGFP-Rab1b ( CA ) ( Fig 6 ) . Less than 25% of E . coli or PFA killed Y . pestis , which traffic to acidified vacuoles , colocalized with eGFP-Rab1b ( CA ) at 20 min post-infection ( Fig 6B ) . Furthermore , we observed no significant change in colocalization at 80 min post-infection . However , in cells infected with live Y . pestis , we observed a significant increase in eGFP-Rab1b ( CA ) localization to the YCV at both time points ( Fig 6B and 6C; ~57%; p≤0 . 05 ) . These data demonstrate that while Rab1b is minimally associated with phagosomes containing E . coli or dead Y . pestis , the GTPase is associated with the YCV containing live Y . pestis at a significantly higher frequency , suggesting that Rab1b recruitment or retention to the YCV specifically contributes to Y . pestis survival . Rab1b has an important role in mediating ER-to-Golgi trafficking [69 , 70] . While Rab1b appears to be directly recruited to the YCV , it is also possible that the effect of Rab1b knockdown on Y . pestis survival is due to changes in Golgi trafficking . To determine if Golgi trafficking , specifically secretory trafficking , is required for Y . pestis to inhibit YCV acidification , we treated RAW264 . 7 macrophages with Brefeldin A ( BFA ) , which blocks Golgi trafficking independent of Rab1b by targeting Arf1 . BFA-treated macrophages were infected with Y . pestis CO92 pCD1 ( - ) LuxPtolC for 20 min , extracellular bacteria were killed with gentamicin , and intracellular bacteria bioluminescence was monitored at 2 and 10 h post infection ( Fig 7A and 7B , respectively ) . At both time points there was no significant difference in the survival of Y . pestis between untreated macrophages or cells treated with increasing concentrations of BFA . Macrophages treated with 10 μM BFA were also incubated with Lysotracker Red DND-99 and subsequently infected with Y . pestis CO92 pCD1 ( - ) pGEN222 to determine if inhibition of the secretory pathway altered YCV acidification . As a control , a separate group of cells were infected with paraformaldehyde killed Y . pestis CO92 pCD1 ( - ) pGEN222 . In agreement with the intracellular bacterial survival , there was no significant difference between YCV acidification in BFA-treated macrophages at 20 or 80 min post-infection compared to untreated cells ( Fig 7C and 7D ) . Furthermore , BFA treatment did not alter the acidification of phagosomes containing paraformaldehyde killed Y . pestis . Together these data demonstrate that Y . pestis avoidance of the phagolysosome is independent of retrograde endocytic trafficking and suggests that Rab1b impacts YCV maturation independent of its function in Golgi trafficking . Previous studies with L . pneumophila demonstrate the cyclic recruitment and release of Rab1b on the LCV within 2 hours post-infection [45] . The release of Rab1b from the nascent LCV coincides with the transition of the LCV from a neutral to acidic pH [71 , 72] . Given that Y . pestis recruits Rab1b to the YCV to prevent vacuole acidification , we hypothesized that L . pneumophila recruitment of Rab1b may also result in arrest of LCV acidification . To test this hypothesis , we transfected RAW264 . 7 macrophage cells with siRNA targeting Rab1b and treated transfected cells with Lysotracker Red DND-99 prior to infection with L . pneumophila to monitor LCV acidification . As previously reported , we observed that the majority of LCVs did not colocalize with Lysotracker in scramble siRNA treated macrophage ( only 30% of L . pneumophila was found in acidified compartments by 80 min post-infection; Fig 8 ) . In contrast , we observed a significant increase in Lysotracker colocalization in macrophages treated with siRNA targeting Rab1b at both 20 and 80 min post-infection ( Fig 8B and 8C; p≤0 . 01 and P≤0 . 001 , respectively ) . These data demonstrate that like Y . pestis , L . pneumophila requires Rab1b to inhibit LCV acidification during early stages of macrophage infection .
Rab proteins are central mediators in vesicular trafficking within the cell . As such , intracellular pathogens often target these GTPases to subvert the normal phagosome maturation pathway and survive within host cells ( see [25 , 73] for reviews ) . Rab1 was one of the first identified members of this family and has been extensively studied for its role in Golgi trafficking in yeast , Drosophila , and mammalian cells ( see [70 , 74 , 75] for reviews ) . More recently , both isoforms of Rab1 have been linked to intracellular infection by several pathogens . Chlamydial species [48] , L . pneumophila [40 , 46] , A . phagocytophilum [43] , Coxiella burnetii [39] , and S . enterica Typhimurium [44] have been shown to recruit Rab1 to the PCV . Furthermore , inhibition of Rab1 by either RNAi or expression of dominant negative Rab1 constructs indicate that Rab1 function is required for the survival/growth of L . pneumophila [40] , C . burnetii [39] , S . enterica Typhimurium [44 , 76] , and Brucella melitensis [77] . Our data demonstrate for the first time that Y . pestis also belongs to this group . Specifically , we have demonstrated that Y . pestis recruits Rab1b to the YCV during infection of macrophages and that this GTPase is required for intracellular survival . Interestingly , Rab1 has only been shown to be required for the survival of pathogens that exist within vacuolar compartments , suggesting a role ( s ) for Rab1 in subverting normal phagosome maturation and generation of a protective PCV . In fact , functional Rab1 has been shown to be detrimental to the survival of the cytoplasmic pathogen Shigella flexnerii through its interaction with the autophagy system within the host cell [41] . However , S . flexnerii has also evolved to target Rab1 , through the VirG secreted effector protein , and inactivate the GTPase to inhibit macroautophagy during infection [41] . While Rab1 has been linked to the survival of several intracellular pathogens , the role Rab1 plays in the maturation of individual PCVs is less well understood . In C . burnetii , Rab1 has been shown to be required for the massive expansion of the Coxiella replicative vacuole ( CRV ) [39] . This requires the acquisition of new membrane in order for the CRV to grow , and Rab1 recruitment to the vacuole may mediate the interception of vesicles ( and their membranes ) from the secretory pathway . This hypothesis is supported by studies showing that treatment with BFA , which independently inhibits the secretory pathway , also inhibits the expansion of the CRV [39] . Studies from A . phagocytophilum and Chlamydial species , which also form a large replicative vacuole , also suggest that Rab1 recruitment is important for formation of a spacious vacuolar compartment [43 , 48] . Therefore , a common goal of bacteria that recruit Rab1 to their PCV may be to subvert the secretory pathway in order to remodel the PCV . Furthermore , Rab1b has also been linked to autophagy [44] , which is also associated with the replication of both C . burnetii and A . phagocytophilum [78 , 79] . It is possible that in addition to the secretory pathway , Rab1 recruitment may also contribute to the recruitment of autophagsomal membranes to these PCV , though this has yet to be demonstrated . Since the YCV also expands late during infection ( though not to the degree of these former pathogens ) to form a spacious vacuole [5 , 12 , 18] , it is possible that Rab1b may contribute to YCV expansion . However , we have not observed changes in spacious YCV formation in Rab1b siRNA treated macrophages . Furthermore , our data also suggest that early association with the autophagosome marker LC3 does not appear to protect YCV from acidification , as we observed no difference in YCV-LC3 association in Rab1b siRNA treated cells . More importantly , our data with Y . pestis reveal a potential new benefit of Rab1 recruitment to the PCV , which is to avoid phagosomal acidification and subsequent fusion to the lysosome . While it is currently unclear how Rab1b inhibits YCV acidification , it appears to be independent from its contributions to the secretory pathway , as BFA treatment did not result in similar changes to YCV acidification . Importantly , while knockdown of Rab1B does not alter the expression of Rab 5 , 7 or 9 , which are required for phagosome maturation ( S1A Fig ) , it is possible that recruitment and retention of Rab1b to the early phagosome inhibits interactions with these Rabs ( and/or Rab effector proteins ) to inhibit normal phagosome maturation . Rab1 has also been linked to endosomal sorting through direct interactions with the kinesin Kifc1 , which in turn affects directional vesicular motility within the cell [55 , 56] . Thus , Rab1b recruitment may alter early sorting of the YCV to avoid acidification and lysosomal fusion . Studies to better characterize the early YCV , including differences in Rab composition and vATPase recruitment as compared to the normal phagosome are ongoing and will provide further insight into these mechanisms . Rab1 recruitment to the YCV also occurs significantly earlier than reported for C . burnetii ( ≤20 min vs . >12 h , respectively ) [39] , suggesting that timing of recruitment may indicate which function , inhibition of phagosome maturation or membrane acquisition , is contributing to pathogenesis of various pathogens . It should be noted that C . burnetii requires passage through an acidified vacuole to induce the expression of important virulence factors and subsequent intracellular survival [80] . Therefore , our observations that early acquisition of Rab1 inhibits PCV acidification may explain why Rab1 recruitment is delayed during C . burnetii infection . In contrast to C . burnetii , L . pneumophila , which inhibits LCV acidification early during infection [71 , 72 , 81] , recruits Rab1 in a similar time frame as seen during Y . pestis infection ( within 10 min ) [46] . In support of our hypothesis that early recruitment of Rab1b is a mechanism for pathogens to inhibit phagosome acidification , we demonstrated that knockdown of Rab1b decreased the ability of L . pneumophila to inhibit LCV acidification ( Fig 8 ) . Interestingly , L . pneumophila appears to control both recruitment and later release of Rab1 from the LCV ( discussed below ) . The timing of Rab1 modification by L . pneumophila coincides with a transition from a neutral to an acidic LCV [71 , 72] , suggesting that Rab1 inhibition of acidification may be an active process that is reversible upon removal of Rab1 from the vacuolar membrane . Phagosome acidification has been shown to be a key step in phagosome maturation . Acidification of the phagosome is believed to work in concert with Rab5 , Rab7 and Rab9 to mediate phagosome maturation and ultimately fusion with lysosomes [27 , 28] . Initially , the early phagosome , highlighted by association with Rab5 , is slightly acidic ( ~pH 6 . 0 ) . As the phagosome matures , the pH decreases and Rab7 replaces Rab5 on the phagosome . Rab7 subsequently recruits more vATPase complexes , resulting in further acidification of the phagosome and recruitment of Rab9 . By the time Rab9 mediates lysosomal fusion , the pH of the phagosome is approaching 4 . 0 , which is the optimal pH to activate hydrolases and proteases delivered to the phagosome by the lysosome . Several lines of evidence indicate that acidification of the phagosome is required in order for efficient lysosomal fusion and function to occur [31 , 32 , 82–84] , which suggest that inhibition of acidification could influence proper lysosomal fusion to the PCV . In line with these hypotheses , we observed a direct correlation between increased YCV acidification with increased Lamp1 association , and subsequent decreased Y . pestis survival , in Rab1b siRNA treated cells . This direct correlation makes it difficult to separate the impact of acidification directly on Y . pestis survival ( acidic killing ) from lysosomal fusion , but further supports the importance of inhibiting YCV acidification as mechanism for Y . pestis intracellular survival [12] . While Rab1 is important for the intracellular survival of several pathogens , bacterial virulence factors that target Rab1 have only been identified for Chlamydia [48] and L . pneumophila [45 , 47 , 85–91] . In the case of L . pneumophila , multiple Dot/Icm secreted factors have been shown to target Rab1 and modify the protein to manipulate localization to the LCV; cycling the host Rab1 between active ( anchored to the LCV ) and inactive states . The effectors DrrA/SidM , SidD and LepB work in concert to first recruit Rab1 to LCV , and then later remove it [42 , 47 , 59 , 62 , 92] . L . pneumophila also manipulates Rab1 independent of recruitment to the LCV through the action of SidC/SdcA , LidA and AnkX [85 , 89 , 91 , 93] . The redundancy in Rab1 targeting proteins indicates that Rab1 manipulation by L . pneumophila is extremely important for the intracellular survival of this pathogen . For Y . pestis , we have yet to define the virulence factors that mediate Rab1b recruitment to the YCV . However , we have shown that Y . pestis does not require the pCD1 plasmid ( including the Ysc T3SS ) or the high pathogenicity island ( pgm locus ) to recruit Rab1b and inhibit YCV acidification . These findings are in agreement with previous work that has shown both of these genetic elements are dispensable for intracellular survival [5 , 8 , 14 , 20] . Therefore , virulence factors encoded elsewhere in the genome are mediating both Rab1b interactions and intracellular survival . While the PhoPQ two component regulator has been shown to contribute to intracellular survival , likely through the regulation of other genes [13 , 15 , 22 , 23] , we speculate that these genes do not regulate survival through Rab1b because phoPQ mutants still inhibit YCV acidification during infection [13] . However , defining Rab1b recruitment to the phoPQ mutant YCV is needed to confirm this hypothesis . Studies to specifically identify Y . pestis factors involved in Rab1b recruitment to the YCV are ongoing . In summary , we have shown here for the first time that recruitment of Rab1b to the PCV directly correlates to the ability of a pathogen to inhibit acidification of the vacuole . These findings indicate a novel function for Rab1b in inhibiting phagosome maturation and suggest that other pathogens may use a similar strategy to modify the maturation of the PCV . Furthermore , in the context of Y . pestis infection , Rab1b is the first factor , either host or bacterial , identified that directly impacts acidification of the YCV . Future studies to define how Rab1b impacts phagosome acidification and to identify additional host factors that contribute YCV biogenesis will be important for us to understand how this pathogen evades killing by macrophages .
All bacterial strains used in this study are listed in S1 Table in the Supporting Information . Y . pestis CO92 [94] pCD1 ( - ) and KIM D-19 ( pgm ( - ) ) ( BEI Resources ) were cultivated at 26°C in Brain Heart Infusion ( BHI ) broth ( Difco ) . When needed , carbenicillin was used at 50μg/mL . Bioluminescent derivatives were generated using the LuxPtolC bioreporter as described previously [63] . To generate fluorescent bacterial strains , Y . pestis and E . coli K12 DH5α were transformed with pGEN222 , pGEN-PEM7::DsRED , or pGEN222::mCherry [66] . E . coli was cultivated at 37°C in Luria-Bertani ( LB ) broth ( Difco ) supplemented with 50μg/mL carbenicillin . L . pneumophila AA100 , a clinical isolate containing pMIP-GFP , was grown on BCYE agar plates for 3 days at 37°C prior to macrophage infection [95–97] . The pGEN222::mCherry plasmid was generated by replacing the EGFP gene from pGEN222 with the mCherry gene using Gibson Cloning [98] . Constitutive active EGFP-Rab1b was generated by site directed mutagenesis of pEGFP-Rab1b [99] using primers 5’- TGG AAC GGT TCC GGA C -3’ and 5’- GGC CCG CTG TGT CC -3’ to mutate the Glutamine at residue 67 to a Leucine as previously described [99] . RAW264 . 7 macrophages were obtained from ATCC and cultured in DMEM , 100 mM glucose + 10% FBS ( Hyclone ) . For siRNA transfection , 20 μl of 0 . 165 μM Silencer siRNA ( Life Technologies ) diluted in Opti-MEM ( Life Technologies ) was mixed with 10 μl of 0 . 03% ( v/v ) Lipofectamine RNAiMax/Opti-MEM ( Life Technologies ) as described by the manufacturer . 30 μl of the siRNA-Lipofectamine complex was added to each well of a white flat-bottom 96-well plate ( Greiner ) , incubated at room temperature for 10 min , and then 1x104 RAW264 . 7 macrophages suspended in 80 μl of DMEM+10% FBS were added . Cells were incubated for 48 h at 37°C with 5% CO2 . For 24-well plates used for microscopy , all reagents were increased by 4-fold . For plasmid transfection , 4 μg of plasmid was transfected into 4 . 4 x 105 RAW264 . 7 macrophages using Lipofectamine 2000 ( Life Technologies ) or 0 . 5 μg of plasmid with JetPrime ( Polyplus ) as described by the manufacturers . Luminescence was monitored with a Synergy 4 plate reader ( BioTek ) ( 1 sec read with sensitivity set at 150 ) . Macrophages were infected with Y . pestis strains as previously described [11 , 63] . Briefly , bacteria were grown at 26°C in BHI , washed in PBS , and diluted appropriately in prewarmed DMEM+10%FBS . Bacteria were added to macrophages and the infection was synchronized by centrifugation . After 20 min , extracellular bacteria were killed with gentamicin ( 16μg/mL ) . One hour after gentamicin treatment , the medium was replaced with DMEM + 10% FBS containing 2μg/mL gentamicin . Intracellular Y . pestis numbers were determined by bioluminescence using a Synergy HT plate reader ( Biotek ) or conventional bacterial enumeration as described previously [63] . For L . pneumophila , bacteria were swabbed directly from plates and diluted appropriately in prewarmed DMEM+10%FBS . Bacteria were added to macrophages and the infection was synchronized by centrifugation . At 20 minutes and 80 minutes post-infection cell monolayers were washed three times with PBS and fixed as described below [96 , 97] . All MOIs were confirmed by conventional enumeration of the inoculum at the time of infection . For vacuole acidification experiments , 75 nM Lysotracker Red DND-99 ( Life Technologies ) was added to the cells 1 h prior to fixation . Brefeldin A ( Sigma ) was added to cells 2 h prior to Y . pestis infection and maintained throughout the infection . For confocal microscopy , cells were fixed to coverslips with 4% paraformaldehyde for 30 min . For indirect immunofluorescent staining , fixed cells were blocked with 3% BSA overnight and incubated with rabbit anti-Y . pestis serum ( 1:1 , 000 ) , anti-Lamp1 ( 0 . 8ug/ul; Abcam ab24170 ) , or anti-MAP-LC3α/β ( 1:200; Santa Cruz sc-16756 ) antibodies for 1 h . Unbound primary antibodies were removed by washing and anti-rabbit Alexa Fluor 488 secondary antibody ( 1:4000; Life Technologies ) was added for 1 h . All coverslips were mounted with Prolong Gold with DAPI ( Life Technologies ) and imaged on an Olympus FV100 laser or Zeiss LSM 710 laser confocal microscope . Colocalization of Lysotracker Red DND-99 or proteins to the YCV was determined using the Coloc function in the Imaris image analysis software ( BitPlane ) . All data are shown as mean and standard deviation of three to six biological replicates and each experiment was repeated three times to confirm the phenotypes . For microscopy , at least 50 vacuoles per biological replicate were analyzed . p-values were calculated by one-way ANOVA ( or t-test for L . pneumophila experiments ) using GraphPad Prism software .
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Yersinia pestis is the bacterial agent that causes the human disease known as plague . While often considered a historic disease , Y . pestis is endemic in rodent populations on several continents and the World Health Organization considers plague to be a reemerging disease . Much of the success of this pathogen comes from its ability to evade clearance by the innate immune system of its host . One weapon in the Y . pestis arsenal is its ability to resist killing when engulfed by macrophages . Upon invasion of macrophages , Y . pestis actively manipulates the cell to generate a protective vacuolar compartment , called the Yersinia containing vacuole ( YCV ) that allows the bacterium to evade the normal pathogen killing mechanisms of the macrophage . Here we demonstrate that the host protein Rab1b is recruited to the YCV and is required for Y . pestis to inhibit both the acidification and normal maturation of the phagosome to establish a protective niche within the cell . Rab1b is the first protein , either from the host or Y . pestis , shown to contribute to the biogenesis of the YCV . Furthermore , our data suggest a previously unknown impact of Rab1b recruitment in the phagosome maturation pathway .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Yersinia pestis Requires Host Rab1b for Survival in Macrophages
|
Recent studies have demonstrated the importance of accounting for human mobility networks when modeling epidemics in order to accurately predict spatial dynamics . However , little is known about the impact these movement networks have on the genetic structure of pathogen populations and whether these effects are scale-dependent . We investigated how human movement along the aviation and commuter networks contributed to intra-seasonal genetic structure of influenza A epidemics in the continental United States using spatially-referenced hemagglutinin nucleotide sequences collected from 2003–2013 for both the H3N2 and H1N1 subtypes . Comparative analysis of these transportation networks revealed that the commuter network is highly spatially-organized and more heavily traveled than the aviation network , which instead is characterized by high connectivity between all state pairs . We found that genetic distance between sequences often correlated with distance based on interstate commuter network connectivity for the H1N1 subtype , and that this correlation was not as prevalent when geographic distance or aviation network connectivity distance was assessed against genetic distance . However , these patterns were not as apparent for the H3N2 subtype at the scale of the continental United States . Finally , although sequences were spatially referenced at the level of the US state of collection , a community analysis based on county to county commuter connections revealed that commuting communities did not consistently align with state geographic boundaries , emphasizing the need for the greater availability of more specific sequence location data . Our results highlight the importance of utilizing host movement data in characterizing the underlying genetic structure of pathogen populations and demonstrate a need for a greater understanding of the differential effects of host movement networks on pathogen transmission at various spatial scales .
When infectious agents invade naïve host populations and are propagated predominantly by local transmission , we expect to observe wave-like spread across geographic space [1–3] . Local transmission processes should concomitantly generate patterns of pathogen genetic variation approximating isolation-by-distance , where the geographic distance between locations and the genetic distance between pathogen variants is positively correlated [4 , 5] . However , for pathogens of humans and other hosts that frequently travel long distances or along pathways not determined by local geography ( e . g . aviation networks ) , accounting for species-specific movement patterns provides an alternative method of defining distance which may better describe spatial spread . For example , diseases may transmit over a network , spreading first between well-connected populations through to poorly-connected populations . Populations that are geographically close to one another may not necessarily be well connected; distance in this model should instead be defined by the quantity of individuals moving between locations rather than their spatial proximity [6–12] . For human pathogens , transmission between distant populations has become increasingly common , as modern transportation now frequently allows individuals to move long distances over short periods of time [13 , 14] . Recent work has repeatedly shown that incorporating human mobility into epidemic models allows for more accurate predictions of the rate and timing of disease invasion and spread [6 , 15] . However , the impact of these various transportation networks on pathogen genetic structure is strongly dependent on spatial scale . Failure to detect similar patterns in structure across multiple spatial resolutions suggests that transmission processes are scale-dependent . For instance , although connectivity based on air travel volume between locations often correlates well with the trajectory of pathogen diffusion at the global scale [6] , at finer resolutions , this mobility network may instead facilitate random mixing among hosts . These contrasting outcomes are influenced by attributes of the mobility network , which can include its size and span in relation to the geographic scale of interest , the number of hosts that utilize it and the regularity of host movements along it , as well as by the epidemiological properties of the pathogen . Seasonal influenza A , a virus which causes major morbidity and mortality worldwide [16] , provides an ideal system with which to compare the effects of human movement networks on pathogen population structure across various spatial scales . Although evidence suggests that the H3N2 subtype of influenza A ( H3N2 ) is genetically structured as a source-sink metapopulation at the global scale [17 , 18] , it is generally accepted that no structure is present at finer spatial scales [19] . This is problematic for the design of containment strategies , since it suggests that the seasonal spread of influenza within countries is determined by stochastic processes and is therefore unpredictable . However , epidemiological reports and mortality statistics from influenza-like illness ( ILI ) data have revealed that spatial patterns do exist , with greater synchronization in epidemic peak timing observed between cities that are geographically close and exchange many commuters [20] . Studies tracking the intra-continental spread of influenza have thus far utilized ILI and excess mortality data , which cannot differentiate between the two subtypes of influenza A ( H3N2 and H1N1 ) that circulate each season . Of the two viruses , H3N2 causes the most morbidity and mortality and has been dominant in six of the past ten influenza seasons in the United States ( US ) [21] . Its rapid evolution results in annual lineage replacement so that little genetic diversity is observed within seasons [22] . In contrast , lower substitution rates are common for seasonal H1N1 , and seasons dominated by this subtype are generally characterized by reduced mortality and morbidity and increased genetic diversity among co-circulating lineages as compared to H3N2 [22–24] . It follows that these contrasting epidemiological dynamics could lead to subtype-specific population structure , but this hypothesis has not yet been formally tested . We explored whether using alternative measures of distance can explain the population genetic structure of seasonal influenza A subtypes within the US . Since it has been shown that airline travel is important for the spread of influenza at the global scale [25] and that both commuter and airline travel contribute to the epidemiological dynamics of influenza within the US [20 , 26] , we investigated the roles that these transportation networks play at the regional scale . We constructed models of the US aviation and commuter networks and quantified interstate connectedness based on the daily number of individuals exchanged . If transmission is dominated by the local spread of influenza across the commuter network rather than long distance spread over the aviation network , we expect that sequences collected from pairs of states that are well-connected in terms of commuter flow will be more similar to each other than those collected from poorly-connected state pairs . To test this hypothesis , we obtained influenza sequences collected from 2003–2013 to compare associations of intra-seasonal pairwise genetic distances with geographic and network distance measures . Results indicate that population structure is indeed detectable , though this pattern is subtype specific .
Comparison of the aviation and commuting networks within the continental US revealed significant differences in their basic properties , despite the similarity in data resolution ( travelers/day ) ( Fig 1 ) . The aviation network , composed of 48 nodes connected by 2 , 160 edges , is highly homogeneous in terms of the total number of connections per node ( degree ) and has a high graph density ( density = 0 . 96 ) , reflecting that most states are directly connected to most other states . In contrast , connection weights differed greatly across state pairs . During the influenza season , approximately 1 . 6 million people travel along the interstate aviation network per day . In contrast , the commuter network is composed of 49 nodes and only 312 edges . Decreased graph density ( density = 0 . 13 ) in comparison to the aviation network reflects that the commuter network is highly spatially organized , with connections generally only occurring between neighboring states . Over 3 . 8 million people travel daily across the interstate ground-travel commuter network , and interstate connections in the east tend to be stronger than those in the west . The community detection algorithm identified an average of 16 communities in the unweighted commuter network with an overall mean modularity of 0 . 55 ( sd = 0 . 003 ) across the 1000 simulations ( Fig 2A ) . In the weighted commuter network , an average of 135 communities were identified and mean modularity was 6 . 03 x 10−4 ( sd = 1 . 33 x 10−5 ) ( Fig 2B ) . For both networks , communities tend to span multiple states . Phylogenetic trees were constructed for nine influenza seasons within the US from 2003–2004 to 2012–2013 ( S1–S9 Figs ) ; seven of these seasons contained clades for which we were able to evaluate population structure . The number of sequences available per season varied from147 in 2005–2006 to 1 , 276 in 2012–2013 and the number of states represented during a season varied from 29 in 2003–2004 to 49 in 2010–2011 , 2011–2012 , and 2012–2013 ( S2 Table ) . The MRCA for each season existed from 1–3 years before present . Clades fitting the criteria for inclusion ( see Materials & Methods ) were not available from the 2004–2005 or 2008–2009 seasons . Detailed information on each season and clade tested obtained through the phylogenetic analysis can be found in S3 Table . We detected a significant correlation between genetic distance and commuter distance for seven out of the 23 clades tested encompassing six out of seven seasons studied ( Table 1 ) . Mantel r correlation coefficients ranged from 0 . 09–0 . 38 . We detected a significant correlation between genetic distance and geographic distance for five clades in four of the nine seasons ( Mantel r: 0 . 14–0 . 33 ) and between genetic distance and aviation distance for two clades in two seasons ( Mantel r: 0 . 31–0 . 42 ) . Temporal distance between sequences , measured as the difference in number of days between collections , was never a significant predictor of population structure . For many clades , more than one distance measurement was significantly associated with genetic distance . After performing partial Mantel tests to account for these interactions , we found that commuter distance remained significant for four clades in four different seasons . Geographic distance remained significant for three clades in three different seasons and air travel remained significant for two clades in two different seasons . Phylogenetic trees were constructed for six influenza seasons within the US from 2006–2007 to 2012–2013 ( S10–S15 Figs ) ; five of these seasons contained clades for which we were able to evaluate population structure . Correlations between genetic distance and commuter travel were detected for a greater proportion of clades when the analyses were repeated for H1N1 at the regional scale ( Table 2 ) . The number of sequences available per season varied from 165 in 2007–2008 to 371 in 2010–2011 and the number of states represented during a season varied from 16 in 2008–2009 to 48 in 2010–2011 ( S2 Table ) . The MRCA for each season existed from 1–4 years before present ( S4 Table ) . Detailed information on each season and clade tested obtained through the phylogenetic analysis can be found in S4 Table . Significant associations between genetic distance and commuter network distance occurred in all five seasons ( Mantel r: 0 . 17–0 . 38 ) . Both aviation network distance and geographic distance were associated with genetic distance in two clades in one and two different seasons , respectively ( aviation Mantel r: 0 . 26–0 . 32; geographic Mantel r: 0 . 44–0 . 56 ) and temporal distance appeared significant in one clade from the 2011–2012 season ( Mantel r: 0 . 31 ) . After performing partial Mantel tests for clades in which more than one distance measure appeared significant , the commuter network remained significantly associated with genetic distance in five clades over four different seasons . In the 2012–2013 season , both commuter distance and aviation distance were significantly associated with genetic distance , although partial Mantel tests showed that neither remained significant when accounting for the other .
We have shown here the first evidence , to our knowledge , that population structure for seasonal influenza A is detectable at the scale of the continental US . Although all distance metrics were correlated with genetic distance for at least one clade , we found that the commuter network was more often associated with genetic distance than any other measure of spatial or network distance for the H1N1 subtype . Further , the association between genetic distance and the commuter network often remained significant after geographic distance was taken into account , demonstrating that the relative magnitude of host movement over space has a greater influence on the route of pathogen spread than the geographic proximity of sampling locations . In contrast , population structure was not detected in the majority of clades tested for H3N2 , even though both geographic distance and commuter distance were , at times , correlated with genetic distance . This discrepancy suggests that epidemiological differences between H3N2 and H1N1 affect our ability to detect population structure of influenza within a season at this spatial scale . Striking differences in the epidemiological dynamics of seasons dominated by H3N2 and H1N1 have been previously documented [20] . The rapid bicoastal spread of H3N2 should obscure our ability to detect patterns based on geography or commuting if long distance transmission ( through the aviation network , for example ) quickly moves the virus between spatially distant localities . Models of the effect of Ro on the spread of influenza across the US and its implications for spatial synchrony have previously shown that ILI cases in cities across the entire US tend to peak around the same time when influenza spread is rapid [20] . In contrast , seasons dominated by H1N1 tend to be milder and characterized by slower dispersal . The slower nationwide spread of H1N1 may facilitate the detection of population structure if H1N1 is allowed to diffuse over short-range connections once it is introduced into a new geographic area . Differences in the rate of spread between multiple clades from the same season could possibly account for our failure to consistently detect these patterns across all lineages . The degree of matching between vaccine strains and circulating lineages could also potentially act to reduce transmission so that the commuter network would be able to exert a sufficiently strong influence in structuring the influenza population . However , there are multiple other factors that vary seasonally which could confound this relationship including , for example , vaccine efficacy , availability , population coverage , or age structure of vaccinated individuals . Models combining genetic and epidemiological data may be able to shed light on this proposed relationship but have only recently been utilized [22 , 27–29]; adding a spatially explicit component to these models remains an area for future research [30] . An investigation into the two circulating lineages of influenza B , a virus which causes milder disease than either subtype of influenza A [31] , would provide an interesting point of comparison to our findings . As population structure based on commuter travel is more pronounced for A/H1N1 , we might expect it to also be evident for influenza B . However , as influenza B primarily affects children [31] , the role of commuters in transmission may be reduced such that structure is instead based on geographic distance . Interestingly , recent work on the epidemiology of influenza B in China showed that the Yamagata lineage tends to infect older age groups than the Victoria lineage [30]; examining these lineages separately may reveal differences in population structure patterns and/or modes of spread within the US . So far , little research to date has been done on the spreading patterns of influenza B and unfortunately , few sequences are publicly available on GenBank , as compared to either influenza A subtype . Apart from biological explanations , uneven sampling may also be responsible for our inability to detect population structure in more seasons , or across all clades within a season . Differences in the number of sequences available for each season are a product of inconsistent sampling among states within a season and differential severity of the influenza virus across seasons . For example , the number of testing facilities differs by state and the quantity of samples sequenced has historically been a function of individual laboratory capacity [32] . Additionally , seasons that are characterized by more severe influenza subtypes or poor vaccine performance tend to yield more sequences [33] . Furthermore , seasons dominated by H3N2 generally result in higher rates of morbidity and mortality than those dominated by H1N1 or influenza B [34] . Better virologic surveillance in less populous locations that are not travel hubs ( i . e . in states outside of New York or Texas for example , which often contributed an excess of sequences per season ) would enable us to better catalog influenza diversity outside of major cities and potentially increase our power to detect spatial patterns in this genetic data . The correlations we detected are not as strong as those observed between these same distance metrics and epidemiological data [20] . First , we caution against the interpretation of the Mantel r value as a standard correlation coefficient such as that calculated from a linear regression . Mantel r correlation coefficients are typically much lower than those reported for other statistical tests , owing to the comparison of distances between variables rather than their absolute values . Further , due to differences in the calculation of the sum of squares statistic , a standard R2 cannot be derived from this value for use as a measure of the variation in the dependent variable explained by the predictor variable [35] . However , the discrepancy in correlation strength may be due to differences in the underlying processes producing these associations . For example , epidemics in different locations could follow similar trajectories in terms of peak timing if one directly seeded the other; however , this could also result if the epidemics were initiated at similar times due to similarities between states in population size or climate . In contrast , correlations between locations based on genetic distance should only arise if epidemics in one location were directly seeded by the other . In systems such as this , where long distance dispersal is prevalent , noise due to the circulation of multiple lineages in a single location likely obscures fine scale signatures of diffusion [19] . We have attempted to account for this noise by using phylogenetic methods to aggregate samples by clade so that only sequences derived from the same introduction , and therefore the same genetic lineage , are compared . However , uncertainty surrounding divergence dates always exists; that we are able to detect any correlation at all is surprising , as none have been found previously [19] . At this spatial scale , the ability of the commuter network to exert a structuring influence on regional influenza populations is directly counteracted by the aviation network , which instead acts to create a randomly mixed viral population . These opposing effects stem from differences in the predictability of transmission processes within the two transportation networks . The commuter network is highly spatially organized , with 99% of commutes occurring over distances less than 150 miles ( 242 km ) . Individuals travel along the commuter network on a daily basis , increasing both the probability of transmission to coworkers and any others with whom an infected individual encounters regularly . These movements along the network lead to a genotypic cline; viral sequences collected from nodes separated by less traveled paths appear less similar than those collected from node pairs that are well connected . In contrast , movement along the aviation network is less predictable . Although individuals traveling by air are likely to remain at their destination for several days , these trips are not likely to reoccur multiple times within a season , thus counteracting the structuring effects of routine commuting . That we find any structure at all is an indication that daily travel to and from work is an important route of interstate spread for seasonal influenza . Although infection pathways can be linked to air travel at the global scale [25] , at the regional scale , air transportation likely functions to move the virus long distances into new areas that have not yet been invaded [15] where it then undergoes short-range dispersal by commuters . In our characterization of the US commuting network , we were able to partition the US into communities of high modularity based on county-to-county connections . While partitioning these communities using daily total commuter flow estimates ( weighted networks ) resulted in weakly supported subdivisions that provided little information about human mobility , analyzing county-to-county connections based on the presence or absence of commuter movements ( unweighted networks ) resulted in subdivisions of high modularity . These communities tended to span multiple states , lending further support to the hypothesis that interstate commuter travel is a viable means of influenza transmission . More importantly , states tended to be part of multiple communities , suggesting that aggregation of sequences by state may be somewhat arbitrary and that finer scale location data for sequences is needed . Our results are in good agreement with previous characterizations of US community structure [36] , which have used currency movement as a proxy for human mobility . Since human movement tends to be limited to spatially compact groups of counties and repeated studies have shown that commuters are responsible for a significant portion of transmission , grouping sequences by commuting community rather than by state may provide a more accurate method of determining which sequences are most likely to be closely related [25]; comparing these sequences sets with network distance may then yield stronger and more consistent relationships between genetic distance and the commuter network . Further , these communities may in fact provide a measure of the spatial extent over which commuting is responsible for the majority of transmission , with air travel operating to transfer influenza lineages between communities . Unfortunately , the spatial data associated with most publicly available sequences is currently limited to the US state of collection . Since commuting communities are defined by county-level associations , the availability of only state-level reporting hinders our ability to analyze the data at this alternative resolution . Clearly , there is a need for more informative spatial data to be made publicly available in order to facilitate analyses using more natural geographic groupings , rather than those arbitrarily imposed by political boundaries . The results from our study complement recent findings that the aviation network plays an important role in the world-wide transmission of seasonal influenza . While the aviation network is undoubtedly of importance in structuring populations at the global scale , we find that , when population structure is detectable , it is the commuter network that is of greater importance at more regional scales . Host movement governs disease transmission patterns , and distinct modes of movement by discrete segments of the population can have varying levels of importance . While the magnitude of the correlations we detected was not overly strong , this may not be the case at finer geographic resolutions , such as within commuting communities or at the state-wide level , or at finer temporal resolutions , such as during the onset of an epidemic before any appreciable long distance transmission has occurred . While commuters living near state borders likely accounted for much of the interstate connectivity measured by our metric , at the intrastate scale , commuters moving between counties may comprise a larger segment of the population . However , local movement networks , such as that of children being transported to and from school , may prove more important in structuring influenza populations at this scale . Previous work has suggested that children are responsible for much of the transmission within communities [37] . Future work is needed to further elucidate the scales at which different movement patterns contribute most to disease transmission .
In total , 3 , 063 influenza A/H3N2 , and 1 , 366 A/H1N1hemagglutinin sequences collected from 2003–2013 in the continental US were obtained from the National Center for Biotechnology Information Influenza Virus Resource for use in this analysis [38] . Collection date was used to assign each sequence to a season , with seasons defined as occurring from Oct 1 to May 31 . We restricted our analyses to seasons containing more than 90 sequences that were collected in at least 10 different states . This criterion was based on a natural break in the data , as seasons that did not fit this criterion tended to have fewer than 30 sequences that were restricted in their geographic distribution . This criterion was therefore necessary to achieve representative seasonal datasets in terms of sequence diversity and geographic coverage . For example , only 11 H3N2 sequences were available from the 2009–2010 season since the H1N1 subtype was dominant; this season was therefore excluded from all analyses of H3N2 data . Using this criterion , we were able to evaluate influenza phylogenetic structure in nine seasons for H3N2 ( 2003–2004 to 2012–2013 , excluding 2009–2010 ) , and six seasons for H1N1 ( 2006–2007 to 2012–2013 , excluding the 2009–2010 pandemic; see below ) . For each subtype , isolates came from all locations within the 48 continental states and the District of Columbia . The specific set of states represented varied seasonally and with each subtype . GenBank accession numbers for all sequences used in this study , as well their location and collection dates are listed in S1 Table . Sequences were aligned using MUSCLE in Geneious [39] and the HA1 domain was extracted for use in all analyses ( H3N2: 987 nt , H1N1: 1701 nt ) . Seasonal influenza is introduced into the US multiple times over the course of the season [19] . To account for these multiple introductions , phylogenetic trees were inferred separately for each season using a bayesian framework in the program BEAST [40 , 41] . To construct phylogenies , we used the SRD06 codon position model to accommodate different substitution rates for the first and second versus the third codon position , with the HKY85 substitution model applied over these two codon positions [42] . For two seasons for which an extremely large number of sequences were available , H3N2 2007–2008 and H3N2 2012–2013 , we down-sampled from states that contributed exceptionally large numbers of sequences . For the H3N2 2007–2008 season , the GTR+I+G model used , as convergence could not be achieved using the codon position model . Trees were constructed using a strict molecular clock , with an exponential growth tree prior and relatively uninformative priors on all phylogenetic parameters except for the substitution rate , for which we used a lognormal prior with mean = 0 . 0055 ( sd = 0 . 7 ) substitutions/site/year for H3N2 sequences [43] and mean = 0 . 0018 substitutions/site/year ( sd = 0 . 4 ) for H1N1 sequences [22] . MCMC chains were run until convergence was reached and a maximum clade credibility tree was annotated after removing the first 10% of the sampled trees as a burn-in . We defined clades as groups of at least 20 sequences stemming from a node with a posterior probability of > 0 . 9 . We corrected for independent introductions into the US by choosing clades for which the entire HPD interval for the divergence time of the MRCA did not fall more than three months before the beginning of the flu season . This time limit was chosen as it was generally the most recent time period for which high posterior support could be obtained for clades . Since several clades fitting these criteria were often identified within a single season , we used a Bonferroni correction within seasons , based on the number of clades identified for a season to account for these multiple comparisons . For each clade analyzed , pairwise genetic distances were calculated as the proportion of sites that differed between each pair of sequences . To ensure that the choice of genetic distance metric did not affect our results , analyses were repeated using the evolutionary substitution models available in the R package APE [44] . The results remained the same regardless of the distance metric chosen , so we chose to present those results obtained using the raw pairwise distance measure . Pairwise spatial distances were calculated based on the great circle distance between state population centers . The 2008–2009 and 2009–2010 seasons presented a special case for H1N1 , as a new pandemic lineage emerged in the spring of 2009 that differed markedly from the currently and previously circulating H1N1 lineages . As epidemiological dynamics of influenza pandemics differ substantially from those of annual seasonal epidemics [24] , sequences from the pandemic lineage in the 2008–2009 season , as well as the entire 2009–2010 season , were excluded from all analyses . To distinguish between antigenically distinct pandemic isolates and the previously circulating H1N1 viruses , a phylogenetic tree was inferred for the 2008–2009 season using a neighbor-joining algorithm . Two clades were immediately obvious , each encompassing distinct time periods during the influenza season that corresponded well with the circulation times of the epidemic and pandemic lineages . Using the A/California/07/2009 strain of pandemic H1N1 ( GenBank accession: FJ981613 ) as a reference , sequences were classified and excluded accordingly . Data on the origin , destination and passenger volume of airline routes within the continental US during October to March from 2003–2012 were obtained from the Office of Airline Information , Bureau of Transportation Statistics , Research and Innovative Technology Administration [45] . Data were restricted to this time period to best represent human movement during the US influenza season , which occurs during the fall and winter and generally peaks anytime from late November to March [46] . Passenger movement data for each airport were aggregated by state , so that each state was considered a node in each season-specific aviation network model . Data on intra-state passenger movement was excluded . Each seasonal aviation network model therefore contained 48 nodes ( all continental US states ) , with directed edges weighted by the number of daily passengers traveling between each unique state pair during the influenza season . Because there are no airports located within the District of Columbia , sequences from this location were excluded for the aviation analysis . To ensure that this did not affect our results , we repeated the analysis with sequences from the District of Columbia coded as being from Maryland or from Virginia; no qualitative differences in the Mantel test results were observed . To facilitate summary comparisons with the commuter network model , a single aviation network model was also constructed based on the average number of passengers exchanged per day between states over all ten winter seasons Data on the origin , destination and commuter volume between all US county pairs collected during the 2000 census were available from the US Census Bureau [47] . Commuter volume estimates were based on census participant responses when questioned on the county location worked in most often during the preceding week . As commuting data are intended as a proxy for long-distance influenza transmission occurring by means other than airline travel , commutes exceeding 150 miles ( 242 km ) were excluded from the final commuter network ( and accounted for only 0 . 07% of county-to-county movements ) . To assess the sensitivity of our results to this assumption , the analyses were repeated using the full commuter network , which included journeys of all distances . For all but one H3N2 clade , and two H1N1 clades tested , results were similar regardless of whether the full or reduced commuter network was used; we therefore only present the results using the reduced commuter matrix . Intra-state commutes were also excluded . Data on commuter movements between counties were aggregated by state so that the final commuter network model contained 49 nodes ( all continental US states and the District of Columbia ) with directed edges weighted by the number of daily commuters traveling between each unique state pair . For each transportation network model , each node corresponds to a single state , and each edge represents the total daily number of either commuter or air travel passengers moving between those states . To compare the basic properties of the two different transportation networks , node degrees and graph density metrics were calculated . Node degree is defined as the total number of connections per node and graph density is calculated as the proportion of edges present in the graph out of the maximum number of edges possible . To assess the validity of aggregating sequences by state , a community detection algorithm based on simulated annealing [48–50] was run for both unweighted and weighted networks of county level commuter movements . We used the methods described by Thiemann and colleagues [36] to compute 1000 partitions of high modularity to determine the underlying community structure for each network . Communities in this context refer to groups of nodes which have stronger ties internally than externally . The community structure of a network can be summarized by network modularity , Q , which measures the overall magnitude of difference between partitions [49] . The modularity value of a particular set of partitions is calculated by taking the difference between the fraction of total connections occurring within communities and the expected value of the fraction of total edges occurring within communities in a network of identical community partitions with randomized connections between nodes . Q is bounded between 0–1 , with Q = 0 indicating that that the community subdivisions provide no more information than that of a random partitioning of nodes . Associations between pairwise genetic distances and measures of geographic and network distance were assessed individually for each season through the use of Mantel’s test [51] . In order to conduct these tests , connection weights between states for each of the transportation networks were symmetrized by taking the sum of both connecting edges . Mantel tests were performed on both the raw connectivity distance matrices ( constructed using the raw number of people traveling between states ) and connectivity distance matrices constructed using the effective distance metric developed by Brockman et al . [6] . This metric is based on the proportion of individuals commuting between states in relation to the total number of commuters in the entire US . Results were similar regardless of the connectivity metric chosen; all results presented are those results obtained using raw connectivity . To account for multiple comparisons , a Bonferroni correction was applied to the results when multiple clades were tested from a single season . When multiple distance metrics ( geographic , aviation or commuter distances ) were significantly correlated with genetic distance for a single clade , partial Mantel tests were performed to account for these interactions . Partial Mantel tests allow for the comparison of two matrices while controlling for the effects of a third by regressing the two matrices of interest on the third matrix , and performing a standard Mantel tests using these residuals . Results of the partial Mantel tests were used to identify the distance metric responsible for driving patterns of population structure .
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The rapid , long-distance spread of human pathogens such as seasonal influenza A across modern transportation networks presents a tremendous challenge for public health . Previous work based on influenza-like illness reports has demonstrated that commuters play an important role in the transmission of influenza across the United States . However , genetic structuring of influenza populations within a single season has not previously been detected . Here , we use sequence data collected over multiple seasons to investigate how human movement along the aviation and commuter networks in the United States contributes to influenza transmission at the regional scale . We confirm that commuters can play an integral role in interstate influenza transmission , but found that this pattern was specific to the influenza A subtype under investigation . We additionally show that strong county-to-county commuter flows do not necessarily fall within state boundaries , emphasizing the need for more precise spatial data to be associated with publically available sequences . Our results demonstrate that genetic structure does exist for influenza populations during the course of a single season at the regional scale and highlight the need to incorporate host movement patterns when studying spatial population structure .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
The Role of Human Transportation Networks in Mediating the Genetic Structure of Seasonal Influenza in the United States
|
Bacteria face the challenging requirement to maintain their shape and avoid rupture due to the high internal turgor pressure , but simultaneously permit the import and export of nutrients , chemical signals , and virulence factors . The bacterial cell wall , a mesh-like structure composed of cross-linked strands of peptidoglycan , fulfills both needs by being semi-rigid , yet sufficiently porous to allow diffusion through it . How the mechanical properties of the cell wall are determined by the molecular features and the spatial arrangement of the relatively thin strands in the larger cellular-scale structure is not known . To examine this issue , we have developed and simulated atomic-scale models of Escherichia coli cell walls in a disordered circumferential arrangement . The cell-wall models are found to possess an anisotropic elasticity , as known experimentally , arising from the orthogonal orientation of the glycan strands and of the peptide cross-links . Other features such as thickness , pore size , and disorder are also found to generally agree with experiments , further supporting the disordered circumferential model of peptidoglycan . The validated constructs illustrate how mesoscopic structure and behavior emerge naturally from the underlying atomic-scale properties and , furthermore , demonstrate the ability of all-atom simulations to reproduce a range of macroscopic observables for extended polymer meshes .
The cell wall rests outside the cytoplasmic membrane and provides bacteria with shape , rigidity , and protection from lysis due to the significant turgor pressure emanating from within [1] . It is primarily composed of a porous , mesh-like network of polymerized peptidoglycan , a repeating disaccharide/oligopeptide molecule . Because it is covalently connected , the cell wall is also the largest macromolecule in nature [2] . The chemical composition of peptidoglycan is largely conserved: relatively long glycan strands are cross-linked by short oligopeptides ( see Fig . 1 ) [3] . In Gram-negative bacteria the cell wall presents as a relatively thin network ( 2–7 nm ) between the inner and outer membranes , while in Gram-positive bacteria , it is much thicker , between 20 and 35 nm [1] , [4] . Multiple theoretical models for the architecture of peptidoglycan at the mesoscopic scale have been conceived [1] . The models fall into two primary classes , a horizontal layer in which the glycan strands run parallel to the cell surface in a circumferential direction [5]–[7] and a scaffold in which the strands are oriented perpendicular to the surface [8] , [9] . While some experiments have been interpreted as support for the scaffold model , e . g . , the NMR structure of a peptidoglycan subunit [10] , more recent electron cryo-tomography ( ECT ) on purified Gram-negative sacculi revealed circumferential glycan strands [11] . Even more complex models have been put forth , such as cables of coiled peptidoglycan encircling Gram-positive bacteria based on atomic force microscopy ( AFM ) measurements [12] , although ECT on these bacteria failed to find distinct cable-like structures [4] . Using biochemical experiments and atomic-scale simulations , it was demonstrated that only layers composed of circumferential glycan strands could fully account for the ECT observations on Gram-positive bacteria , namely a distinct curling and thickening behavior of the sacculus , i . e . , the part of the cell wall remaining after cell lysis , upon shearing [4] . One limitation of many of the previously developed models is that they are typically constructed with an idealized geometric arrangement , which is then deformed according to a set of mathematical rules . Not surprisingly , this procedure tends to generate cell walls with an unnatural degree of order [3]; indeed , regular patterns of quadrilateral or hexagonal shapes are often depicted [7] , [8] . Furthermore , while apparent disagreement with a chosen set of experimental data has been used to indict some models over others [9] , an alternative explanation is that the specific rules used to construct the model as well as the presumed experimental constraints were too strict [13] . In an attempt to circumvent some of the limitations of previous models , we have constructed and simulated patches of Gram-negative cell wall in their full atomic detail . By modeling the cell wall as a intricate composite of its individual components , we restrict the number of assumptions necessary for its construction . A single-layered model was chosen based on ECT of Gram-negative sacculi and on recent simulations of Gram-positive cell-wall patches [4] . Each patch of peptidoglycan was built from the level of individual residues on up , quantifying the behavior at each level , and connecting it with experimental measurements of various structural and mechanical properties . These comparisons are used both to validate the constructions and to illustrate the robustness of the cell wall to variations in average glycan strand length within the range of those observed in vivo . The widespread agreement with experimentally measured properties favors the disordered circumferential model of peptidoglycan in Gram-negative bacteria over other models .
While the glycan strand composition is uniform across all bacteria , composed of alternating -1 , 4-linked GlcNAc and MurNAc saccharides , the peptide stem , connected to the lactyl moiety of the MurNAc residue , is quite diverse [3] , [6] . In E . coli the full , five-residue sequence is L-Ala ( 1 ) D-isoGlu ( 2 ) - ( 3 ) D-Ala ( 4 ) D-Ala ( 5 ) , where -pm is -diaminopimelic acid , a lysine derivative [3] . Also of note is that the D-isoglutamate is connected through a -carboxy linkage to the pm residue ( see Fig . 1A ) . While alanine is already present in the CHARMM force field , the remaining four constituents were originally absent . Therefore , we developed new CHARMM-compatible topologies and parameters for these constituents , as well as for the connections between them ( see Methods along with topology and parameter files provided in the Supporting Information ) . The novel force fields have already been successfully utilized for simulation of Gram-positive peptidoglycan [4] . After parameterization , a single glycan strand 320 residues long was constructed without peptides . A useful property to quantitatively characterize the flexibility of a polymer is the persistence length . It is defined as ( 1 ) where is the position along the strand , is the angle between the tangent vectors at positions and , and the average is taken over all starting positions [14] . Effectively , is a measure of the stiffness of the strand . Two 5-ns simulations of the 320-mer strand were carried out , and was determined by the initial decay of the correlation in Fig . 2 [15] , [16] . The two simulations provided values of and 13 . 6 nm; extending the latter simulation to 10 ns changed this value only marginally ( ) . This persistence length is of the same order of magnitude as that found for other simple polysaccharides from experiments and/or modeling , which can span a large range , e . g . , 4 . 5–13 . 5 nm for pectin [17] and 14 . 5 nm for cellulose [18] . Although not measured here , the persistence length of peptide cross-links is at least an order of magnitude less , being no more than 3–4 Å , making them significantly more stretchable than the relatively rigid glycan strands . The peptides project outward from the glycan strand , presumably in a helical fashion ( see Fig . 2B ) [1] . The periodicity of these peptides is intimately connected to the orientation and degree with which neighboring glycan strands can form cross-links with one another . An angle of between successive peptide side chains was assumed in the classical layered model , thus placing every other one in the plane of the cell wall [5] , [6] . An NMR structure of a peptidoglycan fragment , however , displayed an angle of , in line with that in the scaffold model [10] . To determine the equilibrium angle for an isolated peptidoglycan strand , two 60-residue-long strands were constructed and simulated for 10 ns , one with an initial peptide-peptide angle of and one with an angle of . For the strand initially at 120 , the average angle relaxed to by the end of the 10-ns simulation , while the one initially at was ( see Fig . 2B ) . Based on these results , we conclude the native periodicity of the peptides is approximately four per turn . However , the significant variability in the angle in simulations , even within a single strand , indicates that this periodicity is not strictly maintained and could be easily modified by external forces . In order to construct the full peptidoglycan network , individual glycan strands need to be covalently linked through their peptides . Although this linkage takes a variety of forms depending on species , in E . coli the most common link is a peptide bond made between the amino group of the pm residue ( position 3 ) and the carbonyl group of the penultimate D-Ala ( position 4 ) , shown in Fig . 1B [6] . In the course of transpeptidation , the terminal D-Ala ( position 5 ) is also cleaved , both processes being carried out by penicillin-binding proteins [19] . The degree of cross-linking varies between species and even growth states within a single species [1]; for E . coli it is typically around 50% on average , i . e . , about half of the peptides are linked and half are free [20] . Although alterations to the cross-linking fraction likely affects the mechanical and structural properties of the peptidoglycan network , this variable is not explored in the current study . Two-dimensional periodic patches of peptidoglycan were constructed following a specific set of procedures designed to minimize user bias ( see Methods ) ; an example of a resulting system is shown in Fig . 3A . Despite being initially constructed as an organized , patterned network , the final organization of the peptidoglycan resembles the “disordered circumferential layered” model observed in cryo-tomography images of purified sacculi [11] . However , because no tension was applied , the possibility remains that the peptidoglycan becomes more ordered under native cellular conditions , which is explored below [1] . Much like the fraction of peptides cross-linked , in the bacterial cell wall the average glycan strand length takes on a large range of values , as low as six disaccharides in the stationary growth phase of Helicobacter pylori [21] and more than 50 in Proteus morganii [22] . Even in E . coli , a range of values spanning from 9 to 60 disaccharides has been measured by different experimental techniques for different stages of growth [1] . To examine the dependence of mesoscale properties of peptidoglycan on the average length of the glycan strand , multiple models with a specific average , but non-uniform , number of disaccharides were constructed , including 83 . 2 , 175 . 8 , and 262 . 4 disaccharides , denoted avg8 , avg17 , and avg26 , respectively ( see Fig . 3 ) . Additionally , as an extreme case for comparison , two patches of cell wall with unbroken , periodic ( and therefore effectively infinite ) glycan strands with unit-cell lengths of 15 and 30 disaccharides , denoted Inf1 and Inf2 , were modeled . Because of the small number of strands used ( 12 for avg17 and avg26 , for example ) it's not possible to reproduce distributions , although the limited range of lengths in avg17 ( 8–26 disaccharides ) does agree with where the majority of the strand lengths in CG models falls [23] . A defining property of the peptidoglycan layer is its tensile elasticity , i . e . , its response to applied strain coming from the turgor pressure inside the bacterial cell , also referred to as Young's modulus . Elasticity also serves as a key metric for comparing the constructed models to experimental measurements . Because peptidoglycan is orthotropic , the elasticities along its two symmetry axes are not identical [24] . Based on the theory of mechanical deformation of a two-dimensional sheet ( see SI for a full derivation starting from the material's constitutive relations ) , the Young's moduli in each orthogonal direction , for the glycan strands and for the peptide cross-links , are given by ( 2 ) ( 3 ) where and are the applied strains in each direction , defined as , and and are the resulting stresses , measured in units of force/area . The dimensionless Poisson's ratios , and , relate the spontaneous strain arising in one direction given an applied strain in the other . In order to calculate the elasticity from simulation , varying strains were applied in the plane of the peptidoglycan by altering its dimensions , with one dimension stretched and the other held fixed at its equilibrium value , calculated from a minimum 20-ns constant-pressure simulation ( see Methods ) . Because only one of or is allowed to be non-zero in each simulation , Eqs . 2 and 3 can be simplified to ( 4 ) ( 5 ) While the stresses , and , are formally the derivatives of the free energy with respect to strain in the corresponding dimension , by virtue of the reversible work theorem they can be directly related to the thermodynamic pressure in that dimension , i . e . , a mean force ( see Text S1 ) [25] , [26] . Determination of each model's elasticity was based on six or more 2-ns-minimum simulations in which the peptidoglycan was stretched in the direction parallel to the glycan strands between 1 . 25% and 17 . 5% ( ) relative to the relaxed state and six more simulations between 5% and 45% ( ) parallel to the peptide cross-links . Each simulation was repeated to ensure consistency of the results , giving at least 24 simulations per cell-wall patch ( see Fig . S3 in SI ) . The resulting elasticities and Poisson's ratios are presented in Table 1 , along with measurements and calculations from other studies [24] , [27]–[30] . All simulated models reproduce the expected anisotropy of the elastic moduli in the two orthogonal directions [27] . The glycan strands are found to be much stiffer , with values of ranging from approximately 11 MPa to 66 MPa , compared to 4–18 MPa for ( both ranges for finite average strand lengths only ) . These values are similar to the ranges found in AFM measurements on E . coli , i . e . , = 35–60 MPa perpendicular to the cell axis and 15–30 MPa parallel [27] , as well as other theoretically derived elasticities [24] , [29] ( see Fig . 4 ) . The glycan elasticity increases with average strand length , and for infinite strand lengths , it grows to as much as 200 MPa ( see Inf1 and Inf2 in Table 1 ) . , on the other hand , has no apparent correlation with average strand length . The relationship between the Poisson's ratios , specifically that for all models , indicates that strain in the direction of the glycan strands induces a significant deformation in the peptide direction , but that the reverse is not true . Given that it is known that the glycan strands are aligned with the circumference of the cell and the peptide links with the long axis , the result is that stress applied to the cell wall will be primarily absorbed in the axial direction , leading to a lengthening of the cell , but not an increase in radius , just as observed experimentally [4] , [31] . As average strand length increases , both Poisson's ratios decrease , effectively decoupling the two components of the peptidoglycan layer . One result of this decoupling is that the ratio of the two elasticities , , increases monotonically with average strand length . Besides elasticity , other distinguishing physical characteristics of the cell wall as a whole include its thickness , the size of pores within it , the ordering of its strands , and the area per disaccharide . Using the five model patches developed , all of these characteristics were determined under different applied strains and compared to experimental measurements ( see Table 2 ) . Based on different techniques , the thickness of the E . coli peptidoglycan layer has been assigned a range of values , including 2 . 5 nm ( small-angle neutron scattering [32] ) , 6 . 0 nm ( AFM [27] ) , and 6 . 4 nm ( cryo-electron microscopy [33] ) . More recent ECT experiments estimated the thickness to be 4 nm at most [20] and AFM experiments measured ∼2 nm [34] . In contrast , cell walls from Pseudomonas aeruginosa appear even thinner , ranging from 2 . 4 nm ( cryo-EM [33] ) to 3 . 0 nm ( AFM [27] ) , while that from Caulobacter crescentus is up to 7-nm thick [11] . The thickness in the simulated constructs was determined in two different ways . First , the mass density as a function of , the coordinate orthogonal to the plane of the cell wall , was measured . This density was calculated for all the heavy atoms in the peptidoglycan , averaged over each trajectory . Values for the thickness were taken as the width of the density profile at 10% of its peak ( see Fig . 5E ) . For the relaxed cell walls , the thickness ranged from 3 . 4–3 . 9 nm , in agreement with the most recent ECT measurements [11] . Under strain , this thickness decreased by up to 20% . As a complementary measure of thickness , pressure profiles as a function of were measured for the patch in each simulation . The thickness was then taken to be the stress-bearing part of the wall , i . e . , that fraction of the simulation system with a significantly increased pressure compared to bulk water ( see Fig . S1 in SI ) . This thickness was as much as 1–1 . 5 nm less than that derived from the mass density . Such a result is unsurprising , as the free peptide chains , which project outward from the cell wall , will contribute to the mass density but do not bear any stress ( see SI for a detailed discussion of the pressure profile calculations ) . The maximum pore size in the cell wall in different states has been measured indirectly by determining the largest objects that can pass through it . For example , fluorescently labeled dextran molecules were used to estimate the pore radius in the E . coli wall as 2 . 06 nm in the relaxed state [5] . In another study , proteins up to 100 kDa in size were released from osmotically shocked cells , giving an estimated pore radius of 3 . 1 nm for stretched peptidoglycan [35] . For the cell walls with finite glycan strand lengths studied here , i . e . , avg8 , avg17 , and avg26 , the maximum pore radius averaged over time was 2 . 05 to 2 . 44 nm in the relaxed state ( see Fig . S4 ) . This radius almost uniformly increased under strain , with the maximum observed being 3 . 43 nm , in agreement with the large pore size observed in the osmotic-shock experiments [35] . These pore sizes fall in the same range as those observed in CG simulations [23] , although neither captures the very large pores ( 10-nm diameter ) observed in recent AFM experiments [34] , most likely explained by cell wall-spanning macromolecular machinery [36] . ECT images of frozen E . coli sacculi have revealed a lack of significant ordering of the glycan strands in the relaxed state [11] , although some question remains as to whether this disorder persists when the cell wall is under tension as in a living cell [1] . For the simulated cell walls , the ordering was quantified by measuring the angle between segments of each strand and the circumferential axis ( see Fig . S7 ) . The temporally and spatially averaged angle was typically close to as expected , although persistently off-axis . The standard deviation in the angle was found to be significant at around 20– ( see Table 2 ) . For avg8 , avg17 , and avg26 , the difference in this deviation was minimal under strain when compared to the relaxed state , suggesting that the wall does not become more ordered under tension . In contrast , for constructs Inf1 and Inf2 , tension in the direction of the strands notably decreases their off-axis fluctuations . The sensitivity of these fluctuations to tension is due to the strands' inability to redirect the applied stress into the peptide cross-links , reflected also in their reduced Poisson's ratios ( see Table 1 ) . The average surface area per disaccharide has been estimated at based on the number of pm molecules in a given bacterium [37] . We note that this area can depend on a variety of factors , however , including ion concentration , pH , and the presence of denaturants [2] , [4] , although in the current study , only neutralizing ions are used ( see Methods ) . For the different patches examined here , the unit area for the relaxed cell wall ranges from 2 . 6 to , and rises to 3–4 under strain ( see Table 2 ) . While at first , the discrepancy between experiment and modeling appears large , it should be noted that the cell wall may not be uniformly single layered , with up to three layers in some regions predicted [32] . Peptidoglycan in these additional layers would serve to lower the effective unit area for a single-layered cell wall . Considering a range of possible cell walls from completely single-layered to completely double-layered gives a range of possible unit areas of 2 . 5–5 . 0 . If one assumes that the initial strand spacing used during modeling is linearly related to the resulting unit area , this implies that the average strand spacing can be no less than 2 nm ( unit area of 2–2 . 67 ) and no more than 4 nm ( unit area of 4–5 . 33 ) .
The native architecture and organization of the bacterial cell wall are largely inaccessible to direct imaging techniques , though at the very edge of the resolution of ECT , glycan strands could be discerned in a Gram-negative sacculus . These strands were , nonetheless , fragmented , and the cross-links were indiscernible [11] . Furthermore , the imaged samples are no longer part of living cells . For these reasons , modeling fills a critical gap between biochemical data on the cell wall's constituents and biophysical data on its macroscopic properties . In this paper , patches of an E . coli cell wall were made using a circumferential layered model , supported by ECT imaging of both Gram-negative and Gram-positive sacculi [4] , [11] , plausibility arguments based on the thickness and glycan strand length [1] , and the average peptide-peptide angle measured above ( see Fig . 2B ) . The patches were constructed using only a few initial parameters , including the initial strand spacing ( roughly 3 nm ) , degree of cross-linking ( 50% ) , and average glycan strand length ( between 8 and 26 disaccharides ) . In the simulated cell-wall patches , peptidoglycan was found to be relatively inelastic in the direction of the glycan strands , while very elastic in the direction of the peptide cross-links . The calculated Young's moduli for the two directions , and , respectively , were found to be in good agreement with multiple AFM measurements [27] , [29] , with the best agreement being found for the constructs avg17 and avg26 ( see Table 1 ) . The average glycan strand lengths for these two constructs also match those measured experimentally for E . coli cells in the stationary ( 17 . 8 ) and exponential growth ( 25 . 8 ) phases [20] . determined for live bacteria grown in aragose gel ( 5–15 MPa ) was notably higher than our calculations , although other factors such as the outer membrane stiffness or incomplete gel polymerization may have inflated the number [30] . Further evidence of the relative stretchability of the peptide cross-links compared to the glycan strands comes from the decrease in Poisson's ratios as average glycan strand length increases . At short lengths , there is a significant coupling between the peptide cross-links and the glycan strands , allowing the former to absorb stress from the latter . At longer lengths , however , strain applied to the glycan strands is primarily absorbed by the strands alone , which , due to their inability to stretch much beyond their initial lengths , induces a large stress in the cell wall in their direction . This resistance to expansion , thus , does not depend on the peptide cross-links but is intrinsic to the glycan strands . Indeed , an intriguing suggestion is that longer glycan strands can compensate for a decrease in cross-linking percentage to maintain cell integrity [38] . While the fraction of peptides in cross-links was fixed near 50% for all models here , is directly related to the glycan strand length , whereas is independent . Although it remains to be shown , we hypothesize that , conversely , will be more sensitive than to the degree of cross-linking . Beyond elasticity several other quantifiable properties were measured from the simulations , including the cell-wall thickness , maximum pore radius , and unit area per disaccharide . Excellent agreement with experimentally determined thicknesses [11] and pore sizes [5] , [35] was found . The unit area measured in simulations ( 2 . 6–4 ) implies a cell wall that is more sparse than that estimated from experiment ( 2 . 5 ) . However , those experimental estimates are based on quantifying the total number of pm molecules per cell , irrespective of their place in the cell wall [37] . Neutron-scattering experiments have led to the suggestion that the Gram-negative cell wall is primarily a single layer , but includes regions of up to three layers over 25% of the surface [32] . The excess peptidoglycan in these additional , but limited and incomplete , layers would raise the experimental unit area for a single layer to 3 . 75 , in significantly better agreement with that from the models examined here , also supporting the choice of initial strand spacing of 3 nm . The average angle of the glycan strands with respect to the circumferential axis was found to be near , although the standard deviation was typically 20– , even under tension ( see Table 2 ) . The lack of alignment amongst the strands argues in favor of a disordered circumferential model , as previously indicated by ECT [11] . A chiral patterning of peptidoglycan has been suggested based on recent experiments , and was attributed to a helical movement of MreB , a proposed cytoskeletal protein [39] , [40] . Recent total internal reflection fluorescence and ECT experiments have indicated , however , that MreB moves circumferentially around the cell and does not form long filaments [41]–[44] . The glycan-strand angle measured here was often negative ( range of − to ) , which hints at a slight intrinsic chirality in stressed peptidoglycan networks , irrespective of their assembly . Whether this could explain the experimental results remains unclear . The widespread agreement between simulation and experiment for all of the aforementioned properties , including elasticity , thickness , pore size , and unit area , serves to validate the connection made between the modeled atomic-scale properties of peptidoglycan and the macro-scale properties probed experimentally . The present molecular models support a cell wall composed predominantly of a single layer of peptidoglycan with glycan strands running circumferentially around the cell in a disordered fashion . Furthermore , assuming our model is correct , we predict that the disorder , which is primarily due to the random orientation of the peptide cross-links relative to the strands , persists under native cellular conditions . While we do not consider possible growth mechanisms here in detail , the insertion of new peptidoglycan strands has been predicted to be a function of such disorder , as well as mechanical tension and MreB [45] , [46] . To examine tension-dependent insertion , we also created a peptidoglycan patch in which one strand was deleted , tension applied , and then the strand was added back to the gap that formed . Because some cross-links between the re-added strand and the rest of the patch formed in alternate locations , a slight decrease in the degree of connectivity resulted and one larger pore was observed ( radius of 3 . 6 nm vs . 2 . 9 nm; see Text S1 and Fig . S5 for more details ) . Because this pore may serve as a site for addition of the next peptidoglycan strand , it cannot be assumed that larger pores are an inevitable product of tension-dependent insertion . However , over repeated growth cycles , the insertion mechanism used is likely to become increasingly relevant to the large-scale structure that develops . While a number of other simulations of bacterial cell walls have been carried out in recent years [23] , [39] , [47] , they are all highly coarse grained ( CG ) , a necessary approach for modeling complete sacculi . Coarse graining the system requires , however , that one make a number of assumptions about the properties of individual “beads” in the CG model , including what underlying atoms they represent , how they are connected and interact with each other , and how they are affected by the surrounding environment , e . g . , solvent . Where possible such assumptions are rooted in experimental data , although the reliability of those data and their conversion to model parameters is not always straightforward . On the other hand , models built starting from the atomic scale , in which the parameters are not specialized for each application , can utilize the same experimental data for validation , as done here . The atomic-scale model is limited in size compared to the CG models , however , and therefore cannot fully reproduce distributions in strand length [23] nor capture structural features beyond the modeled scale , e . g . , pore sizes up to 10-nm in diameter [34]; additionally , a visual comparison of the previous CG models with the atomic-scale models here suggests that the latter models are still too ordered , likely a remnant of the initial construction [23] . Thus , future iterations will be used to probe more realistic growth models , the dependence of cellular-scale properties on the cross-linking fraction and strand spacing , and also the interactions of the network with various growth and remodeling enzymes and embedded proteins .
Force-field parameters for GlcNAc were developed by linking glucose and acetamide , with those charges and parameters near the interface determined . Similarly , MurNAc parameters were developed by linking GlcNAc with lactic acid . Charges of interfacial atoms , namely C2 on the sugar ring and the the NH group on the acetamide side chain in both residues along with C3 on the ring , the in the lactic acid side chain , and the bridging O3 oxygen in MurNAc , were modified . These charges were determined from ab initio quantum chemical calculations using a pre-release version of the Force Field Toolkit ( ffTK ) plugin for VMD , following the CHARMM parametrization procedures [48] , [49] . Bond , angle , and dihedral parameters involving the interfacial atoms were similarly determined . Because D-isoglutamate and pm are nearly identical to their standard amino-acid counterparts , glutamate and lysine , their parameters were developed solely by analogy . The complete topology and parameter set used for subsequent simulations is provided in Text S2 and S3 . Because simulating the actual transpeptidase reactions is prohibited by both current knowledge of the order of events and available computational resources , a procedure was developed to build the peptidoglycan network with a statistical view of the general organization . In the first step , a set of E . coli peptidoglycan strands with the number of disaccharides chosen according to a random Gaussian distribution of specified mean are placed parallel to one another separated by a given distance ( typically 2–3 nm , with a 0 . 5 nm random deviation ) . Each system is fully solvated in explicit water and sufficient ions were added to the solution to neutralize the high negative charge in the peptidoglycan . The final atom count ranged from 100 , 000 to 545 , 000 atoms . Initially , the glycan strands are held fixed for a 2-ns simulation while the peptides are left free to move . Next , the trajectory is analyzed to find when each available pm -nitrogen first comes near an available D-Ala carbonyl oxygen , and for what fraction of time they are within this distance . Finally , the list of possible links is ordered according to the first contact using a more stringent distance criterion along with a minimum time within range . Links are then added , in order , such that when a given pm or D-Ala residue is linked , its entire peptide is removed from further consideration . The time and distance criteria are chosen to target roughly 50% cross-linking overall , as typically observed for E . coli [1] , [20] . The cross-linked peptidoglycan network is first relaxed using energy minimization , and then allowed to equilibrate during MD simulations with no applied restraints . It should be noted that the network is periodic , with glycan strands as well as peptides covalently linked across the simulation system's periodic boundaries , thus mimicking a much larger patch of cell wall ( see Fig . 3 ) . The resulting network is simulated for at least 20 ns under constant pressure conditions , which allows its dimensions to fluctuate . The relaxed in-plane dimensions of each patch were taken as the average over the last 10 ns . These dimensions are: 9 . 30 . 218 . 10 . 5 ( avg8 ) , 18 . 70 . 233 . 40 . 25 ( avg17 ) , 17 . 20 . 451 . 20 . 4 ( avg26 ) , 18 . 60 . 313 . 60 . 1 ( Inf1 ) , and 16 . 80 . 327 . 40 . 2 ( Inf2 ) . All simulations were run with the molecular dynamics package NAMD 2 . 9 [50] and the CHARMM force field [51]–[53] . A constant temperature of 310 K was held using Langevin dynamics; a pressure of 1 atm in the direction normal to peptidoglycan layer was maintained with a Langevin piston [54] . A 2-fs time step was utilized , with short-range non-bonded interactions ( 12-Å cutoff ) evaluated every time step and long-range electrostatics every two time steps using the particle-mesh Ewald method [55] . All figures were made using VMD [56] .
|
The structure of the bacterial cell wall has been a point of controversy and contention since it was first discovered . Although the basic chemical composition of peptidoglycan , the key constituent of the cell wall , is now well established , its long-range organization is not . This dearth of information at the mesoscopic scale is a result of the inability of experimental imaging techniques to simultaneously visualize both the atomic-level detail of the peptidoglycan network and its macroscopic arrangement around the bacterium . Now , using molecular dynamics ( MD ) simulations , we have carefully constructed and validated models of sections of the Escherichia coli cell wall in full atomic detail . By comparing various properties of these models , including elasticity , pore size , and thickness with experiments , we can discriminate between them , resolving which best represents the native wall structure . In doing so , our study provides approaches for connecting measurements made in atomic-scale MD simulations with large-scale and even macroscopic properties .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"bacteriology",
"bacterial",
"biochemistry",
"biophysic",
"al",
"simulations",
"computational",
"biology",
"biology",
"cell",
"mechanics",
"microbiology",
"biophysics",
"simulations",
"biophysics",
"biomechanics"
] |
2014
|
Escherichia coli Peptidoglycan Structure and Mechanics as Predicted by Atomic-Scale Simulations
|
In Africa , relapsing fever borreliae are neglected arthropod-borne pathogens causing mild to deadly septicemia and miscarriage . The closely related Borrelia crocidurae , Borrelia duttonii , Borrelia recurrentis and Borrelia hispanica are rarely diagnosed at the species level , hampering refined epidemiological and clinical knowledge of the relapsing fevers . It would be hugely beneficial to have simultaneous detection and identification of Borrelia to species level directly from clinical samples . We designed a multiplex real-time PCR protocol targeting the 16S rRNA gene detecting all four Borrelia , the glpQ gene specifically detecting B . crocidurae , the recN gene specifically detecting B . duttonii/B . recurrentis and the recC gene specifically detecting B . hispanica . Compared to combined 16S rRNA gene and flaB gene sequencing as the gold standard , multiplex real-time PCR analyses of 171 Borrelia-positive and 101 Borrelia-negative control blood specimens yielded 100% sensitivity and specificity for B . duttonii/B . recurrentis and B . hispanica and 99% sensitivity and specificity for B . crocidurae . The multiplex real-time PCR developed in this study is a rapid technique for both molecular detection and speciation of relapsing fever borreliae from blood in Africa . It could be incorporated in point-of-care laboratory to confirm diagnosis and provide evidence of the burden of infection attributed to different species of known or potentially novel relapsing fever borreliae .
In Africa , relapsing fevers are neglected febrile infections caused by Ornithodoros spp . tick-borne borreliae ( Borrelia crocidurae , Borrelia hispanica and Borrelia duttonii ) and the Pediculus humanus louse-borne Borrelia recurrentis [1] , [2] . Also , poorly characterized , yet uncultured new “Borrelia mvumi” species has been reported in acute patient's blood and Ornithodoros porcinus argasid ticks in Tanzania [3] . The relative geographic specificity of each Borrelia species has been challenged by coexistence of two species in the same region [4] . B . hispanica prevalence was reported to be 20 . 5% among febrile patients in Northwestern Morocco [5]; the prevalence of cases attributed to B . crocidurae among febrile patients is of 11 per 100 person-years in Senegal [1] . B . duttonii has been documented in Tanzania and B . recurrentis in Ethiopia [5] , [6] , [7] , [8] . Relapsing fevers are of further concern in travelers returning from Africa in Europe [9] , [10] , [11] . Relapsing fevers are treatable infections but the severity of the disease ranges from asymptomatic to fatal if left untreated [12] . In Rwanda and in Tanzania the investigators found a 30% risk for pregnancy loss and a perinatal mortality rate of 15% [8] , [13] . The prognosis depends in part on the causative species with the case-fatality ratio being higher for B . recurrentis infection than for the other infections [12] . However , the vast majority of patients are diagnosed on the basis of non-specific clinical features that overlap with those of malaria [4] and the poorly-sensitive , non-species specific microscopic observation of blood-borne Borrelia [1] . PCR-based tests have been therefore developed to improve the laboratory-based diagnosis of relapsing fevers in Africa [4] . In particular , real-time PCR targeting the 16S rRNA gene or the glpQ gene improved the sensitivity of the diagnosis when compared to microscopy [14] , [15] . Also , we previously showed that PCR-sequencing intergenic spacers could be used for genotyping B . crocidurae , B . duttonii and B . recurrentis [16] . Here , we present the development and evaluation of a multiplex , quantitative real-time PCR detecting any relapsing fever Borrelia [14] and specifically B . crocidurae , B . hispanica and B . duttonii/B . recurrentis based on post-genomic analyses [16] , [17]
B . crocidurae Achema strain , B . recurrentis A1 strain and B . duttonii Ly strain were grown in BSK-H medium ( Sigma-Aldrich , Saint Quentin Fallavier , France ) supplemented with heat-inactivated 10% rabbit serum ( Eurobio , Courtaboeuf , France ) before DNA extraction . B . hispanica DNA was directly extracted from two argasid ticks Ornithodoros erraticus sensu lato collected from Morocco . DNA was extracted from all specimens using QIAamp DNA Blood mini kit ( QIAGEN , Hilden , Germany ) according to the manufacturer's instructions . Reference identification of borreliae was made by combining the 16S rRNA gene and flaB gene sequencing [6] , [18] . Total blood DNA was extracted from 21 blood specimens found positive by microscopy collected in 1994 from patients with relapsing fever in Addis Ababa , Ethiopia , 18 specimens collected in Mvumi , Tanzania [19] , 9 specimens collected in 2011 in Bahir Dah , Highlands of Ethiopia [19] and 224 blood specimens collected from febrile patients from Ndiop and Dielmo villages in Senegal between 2008 and 2012 where B . crocidurae is endemic . Genome sequence of B . duttonii ( GenBank accession number CP000976 ) , B . recurrentis ( GenBank accession number CP000993 ) and B . crocidurae ( GenBank accession number CP003426 . 1 ) were downloaded from GenBank . Comparative genomic analyses were performed on the chromosomes in order to identify species-specific sequences . In addition , a 16SrRNA gene sequence-based system previously developed in our laboratory was used for Borrelia genus detection as previously described ( 14 ) . Sequence alignments were performed using MULTALIN software for selection of each target sequence [20] . The primers and probes were constructed by using primer3 program at . http://frodo . wi . mit . edu/ . Specificity of primers and probes were determined in-silico . Two different fluorescent dyes , VIC and FAM were used for labeling the probes . The single real-time PCR experiment was performed on Roche Lightcycler ( RocheDiagnostic , Maylan , France ) . The amplification program included two initial holds at 50°C for 2 min and 95°C for 15 min , followed by 40 cycles consisting of 95°C for 30 seconds and 60°C for 1 minute . Five µL of extracted DNA , 0 . 5 µL of each primer ( 10 pmol ) and 0 . 5 µL of probe ( 10 pmol ) were added to the 10 µL Quantitative PCR Master mix ( Quantitec , Qiagen ) and the volume was adjusted to 15 µL by adding distilled water . The multiplex real-time PCR was performed using a Stratagene Mx3000P real-time thermocycler ( Agilent , Courbevoie , France ) by adding five microliters of extracted DNA , 0 . 5 µL of each primer ( 10 pmol ) and 0 . 5 µL of each probe ( 10 pmol ) [1 labeled with FAM and 1 labeled with VIC] to 12 . 5 µL of Quantitative PCR Master mix 2X ( Quantitec ) and the final volume was adjusted to 20 µL by adding distilled water . Negative control consisting of DNA-free water was included every 10 tested specimens . To assess the specificity of the real-time PCR systems developed herein , DNA extracted from Borrelia burgdorferi , Borrelia hermsii , Borrelia parkeri , Coxiella burnetii , Bartonella henselae , Rickettsia africae , Rickettsia felis and Tropheryma whipplei were incorporated into real-time PCR using the experimental conditions described above . In order to determine sensitivity , a puc 57 plasmid was constructed containing the human albumin gene , a 129-bp recN gene fragment from B . duttonii , a 122-bp recC gene fragment from B . hispanica and a 110-bp glpQ gene fragment from B . crocidurae ( Invitrogen , Saint Aubin , France ) ( Figure 1 ) . Tenfold serial dilutions of this constructed puc 57 plasmid were prepared equivalent to 107 to 101 Borrelia organisms . This study was approved by the IFR48 Ethic Committee . All patients provided informed written consent .
As a specific target for B . crocidurae , we selected glpQ encoding glycerophosphodiester phosphodiesterase that is conserved among relapsing fever borreliae but absent from Lyme disease borreliae and additionally possesses a B . crocidurae specific 4-bp single nucleotide polymorphisms ( SNPs ) . We selected the chromosomal recN gene encoding DNA repair ATPase for B . duttonii/B . recurrentis , that is conserved among the relapsing fever group and absent in the Lyme disease group borreliae , and furthermore exhibits a 5-bp specific SNP . For B . hispanica , we selected recC gene encoding exodeoxyribonuclease V , present in both relapsing fever and Lyme disease group borreliae and exhibiting 4-bp species-specific SNP . One probe specific for each of the three targeted regions was designed to span the region containing the SNPs . Sequences of the primers and probes are given in Table 1 . Each set of species-specific primers and probe was first evaluated alone before being incorporated into a multiplex format . There was no difference in the amplification curves when comparing the single-target real-time PCR with multi-target real-time PCR assays . Figure 2 illustrates the results of these two experimental steps and shows that 16SrRNA gene probe labeled with FAM and glpQ gene probe labeled with VIC fluorescent dyes could both be detected in one PCR reaction performed simultanoiusly . Similar results were obtained with recN and recC labeled with VIC and 16SrRNA probe labeled with FAM . In all experiments , negative controls remained negative . The cycle threshold ( Ct ) values for the constructed plasmid ranged from 18 ( 107 copies ) to 36 ( 100 copies ) per 5 µL of plasmid dilution for recN , recC and glpQ . Based on these results , we used a Ct cutoff value of 36 for interpretation a clinical blood specimens as positive . The 16S rRNA probe detected all the Borrelia-positive specimens regardless of the species with Ct values ranging from 18 to 35 . The glpQ assay designed to be specific for B . crocidurae did not amplify B . duttonii or B . recurrentis reference strains , 18 B . duttonii-positive blood samples , 30 B . recurrentis-positive blood samples , two B . hispanica-positive ticks , and other strains mentioned above . The recN assay for specific detection of B . duttonii/B . recurrentis did not detect B . crocidurae , B . hispanica , B . burgdorferi and other strains mentioned above . Likewise , the recC system specific for B . hispanica did not detect B . crocidurae , B . duttonii/B . recurrentis , B . burgdorferi and other strains mentioned above . Human albumin used as a positive control was detected by real-time PCR in all tested human blood specimens , indicating lack of PCR inhibition . When applied to 101 specimens negative for borreliae and 123 specimens found positive for B . crocidurae using combined 16S rRNA/flaB-gene PCR gold standard the observed Ct value for the clinical samples varied between 18 to 35 . The multiplex real-time PCR yielded 100% specificity and 99% sensitivity ( one positive specimen remained negative ) . No DNA remained from this false-negative specimen to enable targeted study of glpQ for mutations in the probe region . When applied to 101 specimens negative for borreliae and 30 specimens found positive for B . recurrentis and 18 specimens found positive for B . duttonii using gold standard , the multiplex real-time PCR yielded 100% specificity and sensitivity . As for B . hispanica DNAs samples , the two tick extracts were detected by recC probe .
In this study , all the negative controls remained negative in every real-time PCR experiment . Also , no evidence of PCR inhibition was detected using human blood as confirmed by amplification of the human albumin internal control in every PCR run . Specificity of primers and probes was confirmed by in-silico analyses and reinforced by experimental demonstrations that these assays failed to amplifyother microorganisms responsible for septicemia , including R . felis [21] and T . whipplei [22] , all demonstrated to be emerging , highly prevalent pathogens in Africa and in Senegal in particular . Therefore , results reported herein were interpreted as authentic . In this study , species-specific primers and probes based on the glpQ , recC and recN gene sequences were selected from the alignment of the B . crocidurae , B . duttonii , B . recurrentis and B . burgdorferi reference chromosome genomes [16] , [17] . Plasmid sequences were avoided , because of their instability among different strains of the same species , and during replication of the same isolate , with a risk of resulting in false-negative results . This approach proved successful for the differentiation between B . crocidurae , B . duttonii/B . recurrentis and B . hispanica . Despite evident interest in distinguishing B . duttonii and B . recurrentis for accurate epidemiological purposes , discrimination between B . duttonii and B . recurrentis was not possible here in agreement with previously reported very close genetic and genomic proximity of both species [16] , [17] . Indeed , genetic and genomic data suggested that B . duttonii and B . recurrentis could be regarded as a single Borrelia species [17] . This limitation may not be problematic as for the routine diagnosis since these two species are respectively transmitted by tick and lice in very different epidemiological contexts [23] . Also , the multiplex real-time PCR proved highly sensitive , detecting 100 copies , that is more sensitive than the 103–105 borreliae/µL reported for microscopy [14] , [24] . Previously , borreliae not detectable by microscopy , were detected by using real-time PCR targeting the fla and the glpQ genes [3] , [15] . These assays however could not identify borreliae at the species level [3] , [15] . Another real-time PCR assay was devoted to the specific detection of B . recurrentis and Rickettsia prowazekii , as these two pathogens are both transmitted by body lice . This targeted the flagellin gene of B . recurrentis with a sensitivity of 101 borreliae [25] . The developed real-time PCR was validated against large number of samples from areas endemic for diverse borreliae causing human infection in Africa , showing 100% sensitivity and specificity except for glpQ gene which had 99% sensitivity due to failure to identify B . crocidurae in one blood specimen . Unfortunately , we could not further analyze this specimen to assess whether this false negative result arose from glpQ mutations or was indicative of a different species or subspecies related to B . crocidurae . Indeed , several recent reports indicate that new relapsing fever Borrelia species are present in Tanzania and South Africa [26] , [27] . Therefore careful optimization is required to ensure that the multiplex real-time PCR technique employed will not miss these new species or other Borrelia species . For this , we incorporated the 16S rRNA gene probe in the system to serve as an indicator of the detection of any relapsing fever Borrelia in the specimen . A specimen detected positive by the 16S rRNA gene probe and negative by the species-specific probes would indicate a new Borrelia species . Such samples could be further subjected to in situ typing such as the recently described multiple spacer sequence typing [16] . In conclusion , as detection and identification of these genetically closely related relapsing fever borreliae in Africa remains challenging , the multiplex real-time PCR assay reported herein offers significant improvement over existing procedures for the diagnosis of relapsing fevers in Africa . Importantly , it permits rapid differentiation of relapsing fevers from the clinically similar malaria , that requires drastically different therapeutic management . It is a sensitive and specific technique capable of detection of major Borrelia pathogens in humans , yet will not overlook detection of potentially new species . This multiplex real-time assay being amenable to point-of-care laboratories in Africa [28] , it provides an effective solution for enhanced characterization of relapsing fever borreliae in Africa , improving medical management of patients and facilitating epidemiological studies .
|
Four cultured Borrelia species are responsible for relapsing fever in Africa . Three species ( Borrelia crocidurae , Borrelia duttonii , Borrelia hispanica ) are transmitted by ticks , whereas Borrelia recurrentis is transmitted by the body lice . These Borrelia species result in febrile infection mimicking malaria with varying severity , but particularly devastating during pregnancy where infection will often cause miscarriage . The lack of comprehensive laboratory tools for detection and speciation of these borreliae limits both medical management of patients and knowledge of the epidemiology of relapsing fevers in Africa . Based on genome analysis , we develop herein a multiplex real-time PCR assay targeting the 16S rRNA gene detecting all four borreliae , the glpQ gene detecting B . croidurae , the recN gene detecting B . duttonii/B . recurrentis and recC gene detecting B . hispanica . Compared to gold standard , this multiplex real-time PCR assay yielded 100% sensitivity and specificity for B . duttonii/B . reccurentis and B . hispanica and 99% sensitivity and specificity for B . crocidurae , when applied to 398 blood specimens . These findings provide the proof-of-concept that multiplex real-time PCR is a new tool for diagnosis of relapsing fever borreliae in Africa .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"relapsing",
"fever",
"medicine",
"bacterial",
"diseases",
"infectious",
"diseases",
"biology",
"microbiology"
] |
2013
|
Multiplex Real-Time PCR Diagnostic of Relapsing Fevers in Africa
|
Achieving target coverage levels for mass drug administration ( MDA ) is essential to elimination and control efforts for several neglected tropical diseases ( NTD ) . To ensure program goals are met , coverage reported by drug distributors may be validated through household coverage surveys that rely on respondent recall . This is the first study to assess accuracy in such surveys . Recall accuracy was tested in a series of coverage surveys conducted at 1 , 6 , and 12 months after an integrated MDA in Togo during which three drugs ( albendazole , ivermectin , and praziquantel ) were distributed . Drug distribution was observed during the MDA to ensure accurate recording of persons treated during the MDA . Information was obtained for 506 , 1131 , and 947 persons surveyed at 1 , 6 , and 12 months , respectively . Coverage ( defined as the percentage of persons taking at least one of the MDA medications ) within these groups was respectively 88 . 3% , 87 . 4% , and 80 . 0% , according to the treatment registers; it was 87 . 9% , 91 . 4% and 89 . 4% , according to survey responses . Concordance between respondents and registers on swallowing at least one pill was >95% at 1 month and >86% at 12 months; the lower concordance at 12 months was more likely due to difficulty matching survey respondents with the year-old treatment register rather than inaccurate responses . Respondents generally distinguished between pills similar in appearance; concordance for recall of which pills were taken was over 80% in each survey . In this population , coverage surveys provided remarkably consistent coverage estimates for up to one year following an integrated MDA . It is not clear if similar consistency will be seen in other settings , however , these data suggest that in some settings coverage surveys might be conducted as much as one year following an MDA without compromising results . This might enable integration of post-MDA coverage measurement into large , multipurpose , periodic surveys , thereby conserving resources .
Preventive chemotherapy ( PCT ) is used at a population level for seven neglected tropical diseases ( NTDs ) : lymphatic filariasis ( LF ) , onchocerciasis , trachoma , schistosomiasis , and the soil-transmitted helminthiases ( STH ) [1 , 2] . PCT is provided via mass drug administration ( MDA ) , usually conducted annually , during which drug distributors disperse medications en masse to the target populations at risk for each disease , except where contraindicated due to young age , pregnancy , or illness . Coverage , the percentage of the defined target population that takes the pills offered at MDA , is an essential indicator of the success of treatment programs and WHO guidelines mandate reporting of coverage as part of monitoring and evaluation of program activities . [2] WHO guidelines state that coverage should be based on directly observed swallowing of the tablets delivered and reported or “administrative” coverage in mass drug distributions is generally calculated as the number of persons treated ( as reported by drug distributors ) , divided by the estimated size of the target population . Accuracy of reported coverage is therefore dependent on the completeness and accuracy of the distributors’ reports and on the estimate of population size; inaccuracies in reported coverage can occur when either or both of these estimates are erroneous . Alternatively , coverage can be measured using cluster-sample surveys similar in purpose to those used by the Expanded Programme on Immunization ( EPI ) [3] . Community-based cluster surveys have several advantages as measurements of MDA coverage [4 , 5] . ( 1 ) They are independent of drug distributors , who may have financial or other incentives to over-report coverage . ( 2 ) They do not rely on estimates of population size , such as potentially outdated or inaccurate census data [6] . The can also ( 3 ) collect information on knowledge , attitudes , and practices , and ( 4 ) help monitor adherence of drug distributors to programmatic guidelines ( for example , whether distributors directly observed the pills being swallowed ) . Despite these advantages , coverage surveys are infrequently used for validation of MDA coverage , in part because of the resources ( human and financial ) needed to conduct them , but also because of concerns about susceptibility to recall and reporting bias . There are few published data regarding accuracy of respondent recall . Estimates of mothers’ recall accuracy for infant vaccination have yielded disparate results [7–9] . It is unclear whether , and under which circumstances , self-report of receipt of treatment ( vaccination or drug administration ) is acceptably accurate for use as a measurement of drug ( or vaccine ) administration . To complicate matters , receipt of PCT is becoming more complex as MDAs for multiple NTDs are integrated to maximize efficiency of distribution . Because target coverage levels vary amongst the NTDs targeted by an integrated MDA [2] , it may be necessary to estimate drug-specific coverage to satisfy reporting requirements . To do this using post-MDA coverage surveys , one might need to ask about not only whether MDA medications were taken , but also which medications ( in the event a respondent reported taking some , but not all ) . The accuracy of such results would depend on the ability of respondents to accurately recall whether they took MDA medications and which ones they took . To test the accuracy of respondent recall following an integrated MDA , we conducted community cluster-sample surveys following the first triple-drug integrated MDA in Togo in 2008 .
The overall aim of the study was to test the recall of participants in the MDA by carefully recording each person receiving MDA medications , then visiting a sample of extended-family dwellings ( compounds ) at 1 , 6 , and 12 months following the MDA to conduct coverage surveys . After the surveys , data from the MDA registers and the survey responses were compared to determine recall accuracy . A secondary aim was to measure the adherence of drug distributors to MDA guidelines . This project was submitted for human subjects review to the Center for Global Health at the Centers for Disease Control and Prevention ( CDC ) , Atlanta , Georgia , USA . The project was determined to be program evaluation under CDC policy prior to the implementation of the survey . Permission for the survey was obtained from the Togolese Ministry of Health . Kémérida Canton , one of 11 cantons within Binah District , Togo , is located along the northeastern border of Togo . Based on the population of enumeration areas that later constituted Kémérida Canton in census spreadsheets dated 2004 , the population of the canton was 4 , 488 . This site was selected as the study area due to its manageable size , making it possible to enumerate all compounds . Compounds consisted of one or more households , often belonging to members of an extended family , and usually surrounded by a wall or some other barrier . All compounds in Kémérida Canton were enumerated and marked with a number , usually on the compound wall or door . Information collected for each compound included the chief of compound’s name and number of households in the compound . All households belonged to one and only one compound . All compounds in Kémérida Canton were eligible for selection to participate in the recall surveys . A cluster sampling survey design was used , with compounds as the primary sampling units . Prior to the first survey , compounds were systematically selected for inclusion in each of the three planned surveys from a line-listing of all compounds in the Canton using a fixed sampling interval and a random starting point . For the 1-month survey , every eighth compound was selected after selecting a random start among the first eight compounds . For the 6 and 12-month surveys , every fourth compound was selected , each starting with a randomly selected compound among the first four compounds that would not lead to the inclusion of any compounds selected for a prior survey round . Study staff interviewed all members of all households within each selected compound , with mothers or another adult answering providing information for children <10 years of age . MDA medications were distributed house-to-house throughout Binah District in May 2008 by community health workers ( CHWs ) employed by the Ministry of Health . Ivermectin , albendazole , and praziquantel were distributed according to age- and height-based WHO dosing guidelines [2] ( Table 1 ) . CHWs were instructed to directly observe drugs being swallowed and to record the name , age , and gender of all treated individuals in a treatment register , according to national MDA protocol . To ensure the accuracy of the treatment registers , a trained member of the study team accompanied CHWs within the study area ( Kémérida Canton ) . These observers were literate members of the local community , often school teachers . The observers’ primary role was to ensure that the medication doses for all persons treated were accurately recorded in the MDA register . To minimize the effect their presence might have on recall , they did not actively participate in either drug distribution or education . Surveys were conducted at 1 , 6 , and 12 months following the MDA . Interviewers were residents of the local community , who were literate in French and Kabiyé , the local language . All interviewers took part in a 5-day training prior to the first survey , which provided an overview of the study design , sampling technique , and the survey instrument and included simulated interviews with trainers and practice interviews with volunteer household members . Interviewers also attended a single day of refresher training prior to each subsequent survey . Interview forms were written in French and interviews were conducted in either French or Kabiyé . Accurate translation of study questions was verified by back-translation of Kabiyé versions . Interviewers asked respondents whether they had been offered pills during the May , 2008 MDA and whether they swallowed the pills they were offered . If the respondent reported swallowing MDA medications , the interviewer showed an example of each pill and allowed the respondent to hold it , and then asked if that pill had been taken , and if yes , how many ( Fig 1 ) . he survey instrument was a 2-page , tabular form for each household that allowed responses for up to 12 household members . To facilitate compilation of treatment and recall data , the form was organized as a roster of household members , with separate column sections to record survey responses and , subsequently , treatment information from the MDA register . Slight modifications were made to the survey instrument after each survey , to improve clarity . After interviewing all members of selected households , interviewers located the treatment register from the May 2008 MDA , and located the information listed for the respondents they had interviewed . The actual treatments were then transcribed from the MDA register onto the appropriate section of the interview form . This allowed compilation of both recall and treatment information for each household on a single form , while leaving the treatment register in the hands of the community health workers or in storage at health facilities . After each survey , data were double-entered using CSPro ( US Census Bureau , Washington DC ) [10] . Discrepancies were resolved by review of the primary data forms . Data cleaning and analysis were performed using SAS version 9 . 2 ( Cary , NC ) and STATA version 12 . 1 ( College Station , TX ) . The analysis was weighted according to the differential probabilities of selection , and the standard errors took into account the cluster-sample design and the high sampling fractions . For concordance calculations , concordant responses were defined as a “yes” or “no” survey response that agreed with documentation of treatment in the MDA register . Missing or “don’t know” responses were included in the denominator as non-concordant . When calculating concordance for recall of pill numbers , ½ tablets were rounded up . To explore potential risks for inaccurate survey responses to the question of overall MDA participation ( “did you take at least one of the MDA medications” ) , we conducted a multivariable logistic regression analysis that pooled responses from all surveys , accounting for clustering by compound , the primary sampling unit ( SAS procedure “surveylogistic” , SAS version 9 . 2 , Cary , NC ) . All relevant available variables were included in the model: age ( at the time of the survey ) , gender , self-reported pregnancy status at the time of MDA , and survey date ( i . e . 1 , 6 , or 12 months ) .
Prior to the study , all compounds in Kémérida Canton were enumerated and line listed . From among the 413 compounds in the Canton , 51 were systematically selected for inclusion in the 1-month survey , 104 for the survey at 6 months , and 103 for the survey at 12 months . A total of 598 , 1 , 335 , and 1 , 073 persons were interviewed for the 1- , 6- , and 12-month surveys , respectively ( Table 2 ) . Survey data could not be collected for 12% ( 1 month ) , 14% ( 6 months ) , and 3% ( 12 months ) of residents of the responding compounds due to the unavailability of individual residents ( or , for those aged <10 years , a responsible adult ) at the time the survey was conducted . Another 3% ( 1 month ) , 1% ( 6 months ) , or 9% ( 12 months ) of those surveyed were excluded because they reported not living in their current household at the time the MDA was distributed . In total , responses were analyzed for >85% of the residents of participating compounds ( Table 2 ) . Demographics for those living in Kémérida at the time of the 2008 MDA but not available for interview during the coverage surveys can be found in the supplemental material ( S1 Table ) . The survey tested several potential recall coverage indicators . Responses to the first three questions , which dealt with overall participation in the MDA ( Table 3 , “Overall coverage” ) were highly consistent across surveys; >88% of persons in each survey indicated they were offered medication during the 2008 MDA and essentially the same proportion reported swallowing all the MDA medications they were offered . For the 1-month survey , the proportion reporting taking at least one MDA medication was almost exactly the same as the proportion recorded as taking at least one medication in the MDA register . While overall recall responses were consistent across surveys , the percentage of respondents with treatment documented in the MDA register declined ( Table 3 , “Treatment documented in MDA register” ) . The survey teams reported difficulty finding records for many surveyed individuals and households at the 6 and 12 month surveys . Since persons not appearing in the MDA register were presumed to be untreated during the MDA , the increasing difficulty of locating all treatment records in the 6 and 12 month surveys likely caused the documented coverage in these surveys to be spuriously low . There was less consistency between surveys when respondents were asked to identify which pills they swallowed ( Table 3 , “Medication specific coverage” ) . Comparing survey responses to treatment documented in the MDA register , concordance for taking at least one MDA medication was 95 . 3% for the 1 month survey , 92 . 4% for the 6 month survey , and 86 . 1% for the 12 month survey ( Table 4 ) . At one month , the discordant answers were equally distributed among those who erroneously reported taking at least one medication ( 2 . 2% ) and those who erroneously reported taking no medication ( 2 . 2% ) . The proportion of respondents reporting taking MDA medications but for whom no documentation was found in the MDA register was 2 . 5% , 5 . 0% , and 11 . 5% in the 1 , 6 , and 12 month surveys , respectively . Concordance for individual pill recall was generally lower than for overall coverage . Concordance for taking ivermectin was slightly higher ( 86 . 0 and 84 . 9 percent , respectively ) than for albendazole ( 81 . 8 and 83 . 3 percent ) or praziquantel ( 81 . 6 and 83 . 3% ) in the 1- and 12-month surveys , but these differences did not reach statistical significance . Recall accuracy for taking each individual medication was best at the 6-month survey ( Table 4 ) . To test the limits of respondent recall , we asked those who reported taking MDA medications to report how many of each tablet they took . Concordance for accurate recall of individual pill numbers was ranged from 36% ( praziquantel , 12-month survey ) to 85% ( albendazole , 6-month survey , S2 Table ) . To check compliance with MDA guidelines , we asked respondents who reported taking medications whether they swallowed them in the presence of the CHW . The percentages reporting swallowing the MDA medications in the presence of the CHW were 95 . 5% , 97 . 6% , and 96 . 5% , respectively , suggesting a high level of compliance with the MDA requirement for directly observed therapy ( S3 Table ) . To check whether MDA treatment had been adequately reported , surveyors asked whether the CHW had been accompanied by a second observer ( member of the study team ) during the 2008 MDA; 100% , 88% , and 99% of those surveyed in the 1- , 6- , and 12-month surveys , respectively , reported the CHW was accompanied by an observer . We further checked CHW adherence to guidelines by evaluating coverage among children less than two years of age and pregnant women , groups that should have been excluded from receiving MDA medications . During the coverage surveys , between 7 and 11% of women aged 15–45 reported being pregnant at the time of the 2008 MDA ( it is unclear how many of these reported the pregnancy to the CHW during the MDA ) ; among these , 0–13% reported taking at least one MDA medication , and treatment was documented in the MDA register for 9–28% . Survey and MDA register results also indicate that between 2–12% of children <2 years during the MDA received albendazole ( S3 Table ) . Because survey and MDA register data were recorded on the same form , there was the potential for interviewers to inappropriately “correct” the survey responses to align them with the MDA register data; this possibility was suggested by the very high concordance for individual pill recall from the 6-month survey . Two of the authors reviewed each of the original survey forms and found that 11% of the 6-month survey responses had evidence of having at least one response erased and re-entered , compared to only 2% at 12 months and none at 1 month . Whether this indicates that the surveyors at 6 months intentionally “corrected” survey responses to bring them in to alignment with the MDA register is unclear . There were three surveyors who participated in the 6-month survey , with “correction” rates of 9 . 5% , 9 . 9% , and 16 . 4% , rates much higher than seen on the forms from 1 and 12 months . None of the three 6-month surveyors participated significantly in the 1-month or 12-month surveys . To identify predictors of accurate recall , we examined the combined data from all three surveys by multivariable logistic regression analysis , controlling for survey , gender , and pregnancy status . Maternal recall for children <10 years of age was significantly less accurate than self-recall in other age groups ( Table 5 ) . Pregnancy status and the survey time point were also significantly associated with lower odds of concordance .
Coverage surveys are an attractive option for validation of MDA coverage because , unlike “reported” coverage ( reported by drug distributors ) , they are not affected by the accuracy of drug distributor records or target population estimates . However , the value of coverage survey estimates is dependent , among other things , on the ability and willingness of those surveyed to accurately report their treatment history . The intent of this study was to assess recall accuracy among persons receiving PCT after an integrated MDA for LF , schistosomiasis , onchocerciasis , and STH in Togo , in a coverage survey conducted shortly after the MDA . A secondary aim was to assess the duration of recall accuracy up to a year after the MDA . We found that survey respondents in Binah District , Togo , reported with high accuracy whether they had taken MDA medications when interviewed at one month post-MDA , and that the survey-derived coverage estimates for taking at least one of the MDA medications were remarkably consistent at 1 , 6 , and 12 months . Unfortunately , difficulty finding persons in the treatment registers make it difficult to draw conclusions about the accuracy of recall at 6 and 12 months . As expected , concordance for the question of whether a person had received MDA medications ( “Did you take at least one of the pills the CHW offered you ? ” ) was highest one month after MDA and lowest at 12 months , but was >86% for all surveys . This high concordance was not simply a function chance agreement based on independently high treatment rates and survey-reported coverage . For example , expected random concordance for the question “Did you take at least one of the pills ? ” , given the observed survey response rates ( 87–91% ) and the MDA register records ( 80–88% treatment ) , would be 79% , 81% , and 74% for the 1- , 6- , and 12-month surveys , yet the actual concordance rates observed were significantly higher ( 95% , 92% , and 86% , respectively; kappa statistic p<0 . 001 for all comparisons ) . By both self-report and MDA register , over 80% of the studied population took at least one MDA medicine , and this proportion among the eligible population was even higher . Furthermore , nearly everyone who took at least one pill took all the medications offered them . This suggests that a single-question query about MDA participation could accurately predict ( in Togo ) whether each individual medication was taken . In other settings where there is a high degree of resistance to taking MDA medications [11] , misrepresentation due to social desirability bias ( i . e . reporting that one took medications when in fact one did not ) may result in lower concordance . One indication that mothers in our surveys generally sought to be truthful rather than automatically reporting that their children were treated ( due to social desirability bias ) , is that mothers did not over-report treatment of children <2 years of age ( S3 Table ) . Our study has important strengths and limitations . It is the first study to directly measure the accuracy of respondent recall in the setting of MDA for NTDs . Because the study was conducted after an integrated MDA that distributed three medications , it provided an opportunity to probe respondent recall not only for overall MDA participation , but also for recall of specific medications . In addition , surveying three independent samples of the same population , but at different times , provided the opportunity to study consistency of survey responses with increasing time from MDA . To our knowledge , this is the first study of coverage survey recall to specifically address this issue . Several limitations have been discussed , including the possibility that the 6-month survey data may overestimate concordance for individual pill recall . In addition , it is likely that the MDA register data presented here under-represent the true MDA coverage in the population in the 6- and 12-month surveys . The field teams reported difficulties finding treatment data in the MDA registers ( which were kept by the CHW , not the study teams ) for many persons surveyed in the later surveys . Because persons not found in the MDA register were assumed to be untreated , the MDA register results likely underestimate treatment and therefore overestimate discordance in these surveys . In this respect , it is likely that the survey responses for overall MDA participation ( taking at least one pill or taking all pills ) are more accurate that the MDA register responses . All three surveys estimated the value of the same parameter—coverage in Kémérida Canton in the last MDA . As would be expected in accurate estimates of the value of this parameter , the three recall-based estimates were very close to each other . The drop in coverage based on the treatment registers is therefore likely due to the increasing failure rate , over time , to find the names of persons in the registers who were in the survey sample and said they had been treated . This hypothesis is further supported by the distribution of discordant responses , which were distributed relatively equally between those falsely reporting treatment and those falsely reporting no treatment at the 1-month survey , but were heavily skewed towards those reporting treatment but not recorded as being treated in the later surveys ( Table 4 ) . It is important to point out that coverage surveys ( and population-based surveys in general ) are useful only to the extent that the survey population is representative of the general population of interest . Our systematic sampling of a high proportion ( one eighth to one fourth ) of the population of compounds in Kémérida Canton should have created very representative surveys of the Canton . Whether Kémérida Canton is representative of all areas under MDA in Togo , or of other areas of world , is important to consider when evaluating our results . In addition , a small proportion ( 5–12% , Table 1 ) of compounds selected could not be interviewed , and an additional 12–15% of persons in interviewed compounds were excluded from analysis either because they were not present at the MDA or because they were not present during the survey . Because persons not interviewed might be more likely to have missed MDA ( due to frequent absence from the compound ) , it is possible that the MDA coverage estimates from our survey responses slightly overestimate true coverage . However , there is no reason to believe those not surveyed would have been less likely to accurately report whether they received MDA medications . Despite its limitations , this study provides several important insights . First , coverage survey responses were highly stable between 1 , 6 , and 12 months , suggesting that , when necessary , coverage surveys in this population might be delayed up to a year to allow inclusion in larger , periodic , multipurpose surveys such as the Demographic and Health Survey [12] without adversely affecting coverage estimates . Second , in a setting where MDA compliance is high , a single question , such as “Did you take all the medications offered you during the MDA” may be sufficient to accurately estimate coverage for multiple medications . Third , it seems clear that respondents recall more accurately for themselves than for their children—at least in the setting where both parent and child are being treated . Fourth , pregnancy can be a particularly difficult confounder when it comes to both appropriate receipt of MDA medication and to accurate reporting in coverage surveys . Announcing a pregnancy is a cultural taboo in Togo [13] and our data suggest pregnant women may choose to be treated rather than disclose they are pregnant by refusing MDA [14] . Similarly , women who are treated when pregnant may be less likely to accurately report treatment . Finally , our results highlight some of the difficulties of conducting field studies in resource-poor settings , and suggest several potential improvements for future studies of recall accuracy , including ( 1 ) blinding of surveyors to MDA treatment register results to prevent inappropriate correcting or correlation of responses by the study team; ( 2 ) documentation of treatment status of all household members at the time of MDA , including those not treated; and ( 3 ) the use of a unique identifier that can be used to facilitate unambiguous matching of survey respondents to their corresponding record in the MDA register . Subsequent studies have incorporated these improvements [15] . Further studies in a setting where MDA compliance is historically lower , will be very helpful in validating the use of cluster-sample surveys for verification of post-MDA PCT coverage .
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Mass drug administration ( MDA ) is an important tool in elimination efforts for several neglected tropical diseases , including lymphatic filariasis ( LF ) , onchocerciasis , trachoma , schistosomiasis , and soil-transmitted helminthiases ( STH ) . The success of control and elimination programs depends upon achievement of target coverage levels during MDA . Community-based surveys can be used to verify coverage after an MDA , but recall accuracy in post-MDA coverage surveys has rarely been formally tested . To test recall accuracy , we compared survey responses among members of a population that received an integrated MDA for LF , onchocerciasis , schistosomiasis , and STH in a series of coverage surveys to verified MDA treatment records . Coverage estimates based on survey responses were highly consistent between samples surveyed at 1 , 6 , and 12-months ( range 88–91% ) and concordance for any ingestion of MDA drugs was >86% in all surveys . Furthermore , respondents were able to identify which of the three MDA medications they took with up to 80% accuracy . These findings suggest that in some settings coverage surveys can provide consistent information up to a year following an integrated MDA and should be considered as a tool for primary assessment of coverage as well as for validating reported coverage .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2016
|
Accuracy of Coverage Survey Recall following an Integrated Mass Drug Administration for Lymphatic Filariasis, Schistosomiasis, and Soil-Transmitted Helminthiasis
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The oligomerization/co-localization of protein complexes and their cooperative regulation in protein function is a key feature in many biological systems . The synergistic regulation in different subunits often enhances the functional properties of the multi-enzyme complex . The present study used molecular dynamics and Brownian dynamics simulations to study the effects of allostery , oligomerization and intermediate channeling on enhancing the protein function of tryptophan synthase ( TRPS ) . TRPS uses a set of α/β–dimeric units to catalyze the last two steps of L-tryptophan biosynthesis , and the rate is remarkably slower in the isolated monomers . Our work shows that without their binding partner , the isolated monomers are stable and more rigid . The substrates can form fairly stable interactions with the protein in both forms when the protein reaches the final ligand–bound conformations . Our simulations also revealed that the α/β–dimeric unit stabilizes the substrate–protein conformation in the ligand binding process , which lowers the conformation transition barrier and helps the protein conformations shift from an open/inactive form to a closed/active form . Brownian dynamics simulations with a coarse-grained model illustrate how protein conformations affect substrate channeling . The results highlight the complex roles of protein oligomerization and the fine balance between rigidity and dynamics in protein function .
The formation of protein oligomeric units often produces increased stability with improved function for the multi-enzyme complexes [1] . The co-localization of protein subunits can shape the active sites , allow allosteric cooperativity , provide an additional level of signaling or regulation , and even permit channeling of intermediates during an enzymatic turnover , which are some of the prime concerns in protein chemistry from the mechanistic point of view [2]–[10] . Such protein dynamics are long recognized to be intimately linked to enzymatic catalysis , but their relationship is exceedingly challenging to delineate [11] . Several experimental and computational studies have probed these fundamental enzymatic processes and their relationships and have provided invaluable insights into the molecular mechanisms [12]–[17] . Hemoglobin is one of the classical and well-studied proteins that exhibit large-scale ligand-induced conformational changes and allosteric cooperativity during the regulation of oxygen transportation . However , for a more complicated and larger system such as tryptophan synthase ( TRPS ) , understanding protein function in relation to the protein dynamics and formation of the multi-enzyme complex becomes even more challenging . The current work investigated TRPS , a pyridoxal 5′-phosphate ( PLP ) -dependent αββα protein complex that catalyzes the last 2 steps of tryptophan biosynthesis in bacteria , fungi and plants . Research studies conducted over the past 40 years have revealed interesting structural , dynamic and mechanistic features of this protein . The protein was the first known enzyme to exhibit 2 distinct catalytic activities modulated by allosteric and synergistic interactions and demonstrating an intermolecular substrate channeling process through a 25-Å long tunnel without exposing the intermediate to the environment ( see Figure 1 ( a ) ) . The α–subunit of TRPS resembles TIM barrel protein and is composed of 2 functionally important α–loops , L2 ( α–residues 53–60 ) and L6 ( α–residues 179–193 ) , that surround the α–active site . The significant contributions of these loops in the α–catalysis and α/β–intersubunit communications have been widely recognized by both experimental and computational work [18]–[23] . Within the superfamily of PLP-dependent enzymes , the β–subunit of TRPS is classified as fold type II ( see definition in Text S1 ) [24] and contains a movable communication domain ( COMM domain; β–residues 102–189 ) . The β–H6 of the COMM domain ( residues 165–181 ) preferentially interacts with flexible α–L2 and α–L6 and mediates intersubunit allosteric communication . Both α– and β–subunits can adopt open and closed conformations . A fully closed conformation is proposed to be the active state of the protein in terms of catalysis and substrate channeling . Although the isolated α– and β–monomeric units of TRPS can independently catalyze the α– and β–reactions , respectively , the rate is very slow [25]–[27] . Steady–state kinetic studies [28] revealed that the rate of the α–reaction in the isolated α–subunit is ∼100 times slower than that in the αββα tetramer of Escherichia coli TRPS , which has 84% identities and 94% similarities with the Salmonella typhimurium TRPS used in our simulation studies . This observation reflects a strong synergistic effect of subunits on the α–catalysis in the multi-enzyme complex . However , the synergistic effects on the β–catalysis are less pronounced . The rate of the β–reaction in the isolated β–subunit of Zea mays TRPS ( ZmTSB1 ) , which shares 96% identity with the bacterial β–subunit of TRPS , is only 1 . 5 times slower than the oligomeric TRPS of Z . mays [29] . While studying the stability of TRPS , Yutani and co–workers found that the isolated α– and β–subunits of Pyrococcus furiosus TRPS , which share 35% and 59% sequence identity with the α– and β–subunits of the S . typhimurium TRPS , respectively , are highly stable [30]–[31] . The study concluded that entropic effects are the major factors contributing to the stability . Similar results have been observed for Thermus thermophilus , a hyperthermophile with 30% and 55% identical amino acid sequences to the corresponding α– and β–subunits of the S . typhimurium TRPS , which indicate the importance of entropic effects in stability of the monomeric subunits [32] . Other kinetic studies investigated the homologs of the S . typhimurium α–subunit , such as BX1 ( 33% identical to the S . typhimurium α–subunit ) and indole-3-glycerol phosphate lyase ( IGL ) from Z . mays . Both enzymes can efficiently catalyze the α–reaction without the other protein partner , but BX1 and IGL are about 1400 and 1150 times , respectively , more efficient than the isolated α–subunit of the E . coli TRPS [33] . The faster reaction rate for BX1 may be due to a highly stable Glu134 ( structurally and functionally equivalent to the α–Glu49 of TRPS ) . Unlike the flexible α–Glu49 of TRPS , Glu134 of BX1 is rigid and preferably stays in the active conformation [34] . This finding suggests that efficient catalysis may require a fine balance between stability and flexibility of enzymes , although the detailed molecular aspects of such linkages are not clear . In this study , we addressed fundamental questions of protein chemistry , including 1 ) the importance of oligomerization of protein subunits , 2 ) understanding subunit cooperativity and correlative motions , 3 ) the linkage between allostery and cooperativity with protein function , and 4 ) protein conformational changes in substrate channeling . We performed several sets of explicit water molecular dynamics ( MD ) simulations of α/β–dimeric and isolated α– and β–monomeric units of the S . typhimurium TRPS with and without ligands . Notably , the isolated α– and β–monomeric units are folded proteins and are stable in solution experimentally , but their catalysis rates are reduced [34] . The trajectories were analyzed , and intra– and inter–subunit correlated motions were illustrated . The ligand–protein interaction energies , entropic effects , and H–bond networks were also studied . Brownian dynamics simulations with a coarse-grained model were performed on selected protein conformations from the MD simulations to study substrate channeling .
Since the protein data bank only contains α–subunit with a closed α–L6 loop , we performed a 15-ns MD simulation with a generalized Born ( GB ) implicit solvent model to obtain an open α–L6 loop conformation [35] . This method has been already employed for studying the HIV-1 protease flaps to successfully demonstrate the open and closed states of this protein [36] . The initial structural coordinates for the α–subunit were obtained from the Salmonella typhimurium TRPS ( PDB entry 2J9X ) ; the α–site ligand was manually removed [37] . The coordinates of three missing residues ( Ala190 , Leu191 , and Pro192 ) in the α–L6 loop were taken from a completely closed S . typhimurium TRPS ( PDB entry 3CEP ) [38] . After a subsequent minimization , equilibration and MD simulations with the GB model in the Amber package [39] , several open conformations of the ligand–free α–subunit were collected on the basis of the distance between α–Thr183 ( α–L6 ) and α–Asp60 ( α–L2 ) . The open conformations of the ligand–free α–subunit were combined with a ligand–free open β–subunit ( PDB entry 1QOQ ) to construct several ligand–free TRPS with open α– and open β–subunit [40] . The modeled α/β–dimeric units were minimized and equilibrated in explicit water . The systems were then subjected to a minimum of 13–18 ns of explicit MD simulations and important distances were subsequently analyzed . The most stable ligand–free α/β–dimeric unit in terms of smooth distance fluctuations was then selected for a 60-ns MD simulation by use of the NAMD 2 . 6 program [41] . A ligand–bound complex was constructed by placing both α– and β–site ligands in the binding sites . IGP was docked into the α–site of the ligand–free complex obtained from the procedure described in the previous section ( the detail parameters of protein–ligand docking are given in Text S1 ) . Since the side-chains of the α–site produced considerable changes during the free protein simulation ( in particular the α–Phe212 ) , molecular docking programs could not reproduce the crystal structure conformation of IGP . Therefore , the substrate was manually placed into the binding site , and the distances of catalytically important residues α–Asp60 and α–Glu49 with IGP were maintained , as suggested by experiments . The β–site ligand , aminoacrylate , was docked into the β–subunit of the ligand–free α/β–complex by use of the Autodock4 package [42] . The choice of IGP and aminoacrylate as ligands for α– and β–sites , respectively , ensures the closed conformation of the α/β–complex . The system containing α– and β–site ligands is termed the ligand–bound ( LB ) complex . After subsequent minimization and equilibration , a 100-ns MD trajectory was collected to observe the possible ligand-induced conformational changes in the complex . Since the simulation may require a very long time ( probably a couple hundred ns long ) to exhibit the switching of the α– and β–subunits from open/semi-open ( LB state ) to the completely closed states , we also run a reference simulation with a completely closed conformation . Therefore , another TRPS system , with IGP and aminoacrylate in the α– and β–site , respectively , was prepared by using the initial coordinates from a crystal structure ( PDB entry 3CEP ) . This is our reference structure with completely closed α– and β–subunits , which we termed the ligand–bound–reference ( LBR ) complex . We created a 50-ns MD simulation after subsequent minimization and equilibration processes . The isolated monomeric units for all three states ( LF , LB and LBR ) were simply prepared by splitting the α/β–dimeric units into their subsequent α– and β–monomers , so that the initial geometries of isolated monomeric units were exactly the same as their corresponding subunits in the dimeric unit for comparison . For the molecular dynamics simulations , the ff03 amber force field and general amber force field ( GAFF ) were applied to both α/β–dimeric and isolated α– and β–monomeric units ( LF , LB and LBR TRPS complexes ) [43]–[44] . An antechamber was used to create the topology and coordinate files for the ligands [45] . The protonation states for histidines , aspartates and glutamates were assigned by the MCCE program [46] . The TRPS dimeric units contain one α– and one β–subunit , whereas isolated monomers contain only one of each subunit . Although no substrates bound to the LF dimeric and isolated monomeric units , a PLP molecule was kept as a co-factor in the β–active site . The systems were electronically neutralized by the addition of 14 Na+ ions for the α/β–dimeric units and 6 and 8 Na+ ions for the isolated α– and β–monomeric units . The LB TRPS represents a transition stage of the ligand binding process and was constructed by manually docking a substrate into a free subunit ( see reference [47] for details ) . The system includes 3-indole-D-glycerol-3′-phosphate ( IGP ) in the α–active site and aminoacrylate in the β–active site; systems were subsequently neutralized by the addition of 13 , 5 and 8 Na+ ions for the α/β–dimeric and isolated α– and β–monomeric units , respectively . Both LF and LB complexes have one Na+ ion placed close to the β–active site , as suggested by experiments . The LBR complex refers to a completely closed state of TRPS comprised of IGP and aminoacrylate in the β– and β–active sites of the complex , respectively . The carbonyl group of aminoacrylate was unprotonated , and six crystal waters were kept in the β–site . The Cs+ ion located close to the β–active site in the crystal structure ( PDB entry 3CEP ) was replaced with the Na+ ion; 13 more Na+ ions were added to neutralize the α/β–dimeric unit; and 5 and 8 Na+ ions were used to neutralize the isolated α– and β–monomers , respectively . All 9 complexes were solvated by use of a 12 Å TIP3P water box with the xleap program in the Amber10 package [39] . Each dimeric unit has about 86000 atoms , whereas isolated monomers have ≤48000 atoms . The initial energy minimization for water molecules involved the sander program in Amber10 . The NAMD 2 . 6 program was then used for further minimization , equilibration and production runs . Before equilibration , the systems were gradually heated from 250 to 300 K for 30 ps . The resulting trajectories were collected every 1 ps . The total trajectory lengths for the α/β–dimeric units were 60 , 100 and 50 ns for LF , LB and LBR states , respectively . For the isolated α–monomeric units , the trajectories were 50 ns long for both the LF and LBR states , and 150 ns for the LB state . The production runs for the isolated β–monomeric units were 56 , 126 and 45 ns for the LF , LB and LBR states , respectively . The NPT ensemble was applied , and periodic boundary conditions were used throughout the MD simulations . A temperature of 298 K was maintained by use of a Langevin thermostat with a damping constant of 2 ps−1 , and the hybrid Nose-Hoover Langevin piston method was used to control pressure at 1 atm . The SHAKE algorithm was used to constrain the length of all bonds involving hydrogens; therefore , the time step was set to 2 fs . The non-bonded interactions were truncated at a distance of 14 Å with a switching beginning at 12 Å . The particle mesh Ewald method was used to treat long-range electrostatic interactions beyond the cut-off limit . The VMD program [48] was used for visualization and graphical representation . PyPAT script was used to analyze the H-bond network and MutInf [49] for the correlated motions in simulated trajectories . RMSF and entropy were calculated by Bio3D [50] and T-Analyst [51] , respectively . The Brownian dynamics simulation algorithm , together with a coarse-grained model ( CGBD ) , was used to study the motions of the indole molecule in the channel formed by the α– and β–subunits . The CGBD simulation method has been well described [52]–[53] . In our simulation , the amino acids are represented by one bead placed at the Cα of each residue [54] . Most residues were assigned an effective radius from an existing publication [55] . For residues in the active sites and along the channel , the bead radius was measured by the distance between the Cα and side-chain based on a crystal structure ( PDB entry 3CEP ) . For indole , each ring is represented by one bead , and an effective radius was based on the size of the pyrrole and benzene ring of 1 . 6 Å and 1 . 9 Å , respectively . The protein is held rigid , and the motion of each bead of indole is simulated with use of the BD algorithm of Ermak and McCammon [56] and Shen et al . [57] . Although the slower protein fluctuations might have a role during indole channeling , the coupling between protein conformational changes and indole motion was not taken into account in this study [58]–[59] . Multiple protein conformations were chosen for the CGBD simulations . The diffusion coefficient used in the algorithm to move a bead was computed by the Stokes-Einstein equation , and the viscosity of water was set to 1 cp ( T = 293 K ) . In our coarse-grained model , the beads of indole are linked by a virtual bond , and Coulombic and van der Waals interactions were applied for intermolecular interactions [54]–[56] . A Lennard-Jones type functional form was used for van der Waals interactions , Uvdw = 0 . 5[ ( ( ri+rj ) / ( rij ) ) 8−1 . 5 ( ( ri+rj ) / ( rij ) ) 6] , where ri and rj are the effective radii of beads i and j , respectively . The Coulombic interaction was approximated by Uelec = qiqj/eij rij , and a distance-dependent dielectric coefficient ( eij = 4rij ) was used to avoid unrealistic in vacuo Coulombic interactions [60]–[61] . Conformations for the simulations are snapshots taken from 0 , 6 , 12 , 24 , 30 , 40 and 50-ns MD simulations in the LBR state; 2 , 12 , 24 , 48-ns MD simulations in the LF and LB states . All the snapshots were superimposed on the crystal structure ( PDB entry 3CEP ) and the coarse-grained indole molecule was placed in the same position in the α–active site shown in the crystal structure . For each snapshot , 500 different random number seeds were used to study motions of indole as it approached the β–active site . The simulations used a 50-fs time step and were run for 2–4 µs . A simulation was terminated if indole reached the β–site or escaped farther than 40 Å of the α–active site . If indole cannot reach the β–site within 4 µs , then we consider that the channel is blocked . If indole diffuses farther than 40 Å of the α–active site , then we consider that indole escapes , since it is unlikely that indole diffuses back to the active sites . We computed a distance between one bead of indole and the center of mass of the β–state in a given protein conformation to determine whether the indole reacted . If the distance was closer than 5 Å , then the indole reacted at the β–active site . The MM-PBSA approach was used to compute the ligand–protein interaction energies . The total energy Etot ( r ) can be divided into two terms: potential energy term , U ( r ) , and solvation energy term , W ( r ) , both functions of the coordinate r . The molecular mechanical energies were computed in a single MD step in the Sander module using a cutoff value of 40 Å for the non-bonded interactions . The solvation energy can be further decomposed into a Poisson-Boltzmann term , WPB , for electrostatic solvation free energy [62] , and a cavity/surface area term , Wnp , for nonpolar solvation free energy [63]–[64] . For the electrostatic component of the solvation energy , the dielectric constant of the interior protein ( solute ) was set to 1 , whereas an implicit solvent dielectric constant of 80 was defined for the solvent region . The nonpolar solvation free energy was approximated with the commonly used solvent-accessible surface area ( SASA ) model . The SASA was estimated with a 1 . 6-Å solvent-probe radius as implemented in Sander . Amber10 was used to compute all energy terms for each snapshot saved during the MD simulations , with waters removed [39] . The change in mean energy on molecular interactions can be split as follows: ( 1 ) where ΔUc represents the changes in valance energy ( bond , angle , dihedral and improper dihedral energies ) , ΔUvdw represents van der Waals interactions , ΔUele represents Coulombic interactions , and ΔWPB and ΔWnp represent polar and nonpolar solvation free energy , respectively . Each individual interaction energy term is calculated according to the following equations: ( 2 ) where Δ<EProtein-ligand> is the ligand–protein interaction energy . Note that the valance energy term is cancelled during the calculations . The configurational entropy S consists of conformational and vibrational parts , which describe the number and width of occupied energy wells , respectively [65]–[67] , computed from each dihedral angle . The configurational entropy is calculated by the Gibbs entropy formula [68]: ( 3 ) where p ( x ) is the probability distribution of dihedral x and R is the gas constant . T-analyst was used to compute the Gibbs entropy , and only the internal dihedral degree of freedom of rotatable dihedrals is considered in the entropy calculations . The absolute temperature T was set to 298 K in this study . The change in configurational entropy of dihedrals of interest between a bound and free state can be obtained by TΔSconfig . = TSbound−TSfree .
Effective local or allosteric protein communication is a key to protein function . In most macromolecules , these communications are usually governed by non-bonded inter/intra-molecular interactions , such as van der Waals and electrostatic attractions and hydrophobic effects . Among these attraction forces , changes in hydrogen bond networks and surface areas are useful quantitative measurements for protein communication . Figure 1 ( b ) demonstrated that interactions at the α/β–interface in TRPS combine hydrophobic interactions [69] , and salt bridges and H-bonds . Experimental mutational studies for some of these interacting residues show that the salt bridges and H-bonds regulate allosteric and synergistic motions in the protein complex . A quantitative comparison of some H-bond networks , across the subunits and within the subunits , at the α/β–interface of LF and LBR dimeric units is shown in Figure 2 ( a , b ) . The analysis reveals a stronger communication at the α/β–interface of the LBR dimeric unit than at that of the LF dimeric unit . This finding suggests that binding of ligands in the α– and β–active sites of TRPS enhances the subunit communications , which are necessary to synchronize the catalysis taken in both α– and β–active sites located 25 Å apart from each other . Correlated motions in proteins are ubiquitous and often related to protein functions . Assessing such correlations is therefore crucial for understanding protein function . Although we observed more inter-subunit interactions in the LBR state , the correlations are more pronounced in the LF state . The complex is also more flexible in the LF state , and the motions are not random but are in concert . Figure 3 shows a comparative correlation of regions important for subunit communication , such as α–L2 , α–L6 , β–H6 of COMM domain and residues at the α/β–interface of the TRPS dimeric unit in the LF and LBR states obtained by the use of the MutInf package [49] . With a few exceptions in the β–subunit , in general , the correlation is weaker at/near the dimeric interface in the LBR state than the LF state; loops α–L2 ( red rectangular box ) and α–L6 loops ( blue rectangular box ) show significant correlation in the LF state . The correlation map suggests that the α–subunit ( α–L2 , α–L6 and the interfacial residues ) and β–H6 of the COMM domain ( pink rectangular box ) has weak correlation in the LBR state . A possible reason for a weaker correlation is that stronger inter-subunit interactions rigidify those regions ( Tables 1 & 2 ) upon binding of the ligands , resulting in smaller magnitudes of correlative motions . We suggest that in the LF state , the concerted motions may help and guide the loops and the COMM domain to close when substrates bind to the active sites . Fully closed protein conformations are believed to appear only when both α– and β–site ligands are present in the α/β–dimeric complex; they provide the optimized geometry necessary for enzyme catalysis . The closed conformations can optimize substrate–protein interactions to stabilize the substrate in the active site . To quantify the stability of substrates binding to the α/β–dimeric unit versus the isolated α– or β–monomer , we performed end-point energy calculation , also known as MM-PBSA calculations . Although more rigorous free energy calculation methods , such as umbrella sampling or metadynamics , need to be applied to get detailed free energy profile , it may need excessively large computational power to fully sample the energy landscape for a system with this big size [70]–[71] . A simple thermodynamic cycle and single-trajectory post-processing allow for efficiently computing the various contributions and differences in ligand binding to the dimeric and isolated monomeric units . Because the catalytic rates are greatly reduced in the substrate-isolated monomeric complexes , we anticipated that both ligands might show weaker intermolecular attraction in the monomers . Unexpectedly , both α– and β–substrates in the substrate-isolated monomeric complexes showed fairly strong intermolecular attractions in the LBR TRPS state than in other states , which suggests that the monomers are nearly as stable as the dimeric unit . However , substrates in the LB monomer have higher inter-molecular energies and are unstable , and the conformations of ligand-monomer complexes deviate from their dimer conformations , especially in the α–subunit . Table 3 gives a comparison of ligand–protein interaction energies in the LB and LBR monomeric and dimeric complexes . The values of ΔEtotal for the isolated LBR monomers ( α = −7 . 6 and β = −80 . 5 Kcal/mol ) are similar to those in the LBR dimeric unit ( α = −10 . 9 and β = −76 . 7 Kcal/mol ) , which suggests that the ligand–protein intermolecular attractions do not have significant differences between the isolated LBR monomers and the dimer . The changes in the electrostatic ( Δ<Uele+WPB> ) and the non–polar solvation ( ΔWnp ) energy terms upon dissociation of the dimeric unit into the monomeric units are insignificant in the LBR states . In the LB states , the transition states during ligand binding processes , substrates interact weakly with the protein in both α– and β–monomers and the α/β–dimeric unit . Interestingly , the interactions are much weakened in the isolated α–monomer , which indicate that without forming an α/β–dimeric unit , ligand binding substantially disturbs the stability of the protein . Overall , both α– and β–substrates are less stable in the LB state than are ligands in the LBR state . The LB state is in association processes , whereas ligands are binding to TRPS . These findings suggest that the α/β–dimeric unit helps both α– and β–site ligands bind in the active sites and bring the proteins to the closed conformations through a systematically advanced allosteric communication across the α/β–interface . Absence of interface communication ( i . e . , the isolated monomers ) detains the transition of open conformations to closed conformations and results in the deceleration of catalysis in monomer complexes . Of interest is knowing whether the isolated α– and β–monomeric units are more disordered than α/β–dimeric units , which may be less favorable for ligand binding . Therefore , we calculated the root mean square fluctuations ( RMSFs ) of Cα atoms and torsional entropy for each residue for the first ∼50 ns long trajectory of the LF and LBR states . Figure 4 shows a comparison of the RMSF values of the isolated α–monomeric unit and the α/β–dimeric units for both LF and LBR states , which match well with the trends of the fluctuations in the B-factors of the TRPS crystal structures . The RMSF plot clearly indicates that most of the regions in the isolated α–monomeric unit are more rigid , as compared to the α–subunit of the α/β–dimeric unit in the LF state , while an opposite trend can be observed for the LBR state . The effect of the ionic strength on the dynamics of the hydrophobic surface for the isolated α–monomeric unit in the LBR state seems negligible . The RMSF plot obtained from a 50 ns long explicit water MD simulation with 100 mM NaCl concentration is compared with those of the isolated α–monomeric unit and the α–subunit of the α/β–dimeric unit , and is given in Figure 1 in Text S1 . For the β–monomeric units , in general , the difference in the RMSF values is insignificant . To quantitatively account for these flexibilities , torsional entropy was computed for the isolated monomeric and dimeric units in different states . The entropy computed for the peptide bond Ù angles was similar with all simulations , so we focused on other more flexible dihedral angles . The total entropic contributions for the backbone ( Ø and Ö ) and sidechains ( SCs ) indicated that in the LF state , both isolated α– and β–monomeric units are surprisingly more rigid than the dimeric unit ( see Tables 1 & 2 ) . Khare et al . [72] have observed a similar behavior in the wild-type Cu , Zn superoxide dismutase ( SOD1 ) enzyme , where some residues are more rigid in the monomeric SOD1 as compared to dimer and are coherent with the NMR data . In TRPS , the difference is particularly significant in the sidechain rotation . Regions involved in ligand binding and closing the binding sites , such as α– and β–active sites , α–L6 , α–L2 , and β–COMM , show a pronounced decrease in sidechains motions of the isolated monomeric units , thus contributing to their rigidity . The hydrophobic binding interface between the subunits provides alternative contact points that allow sidechains of residues in the dimeric unit to adopt different binding conformations ( data not shown ) . In addition , the correlated motions through non-direct sidechains contacts also increase protein flexibility , so such correlated motions vanish in the monomer . Upon ligand binding , the protein flexibility was reduced largely in the dimeric unit; however , surprisingly , no significant entropic penalty was found in the isolated LBR monomers ( TΔS = ∼1 . 6 and ∼1 . 7 kcal/mol for the α– and β–subunits , respectively ) . When the substrate binds in the α–active site , the dihedrals entropy of the α–subunit loses 57 . 6 kcal/mol in the dimeric unit ( Table 1 ) . Because ligand IGP has intra–molecular interactions and is not very flexible in its free state , the entropy loss from reducing the flexibility of a few rotatable bonds of IGP is not significant ( ∼2 kcal/mol ) . The difference is comparatively less sizable in the β–subunit; binding the β–ligand to the active site produces a protein dihedral entropy loss of 32 . 5 kcal/mol in the dimeric unit ( Table 2 ) . Interestingly and unexpectedly , without the partners , the isolated monomers are more rigid in the LF state . Although binding a chemical ligand to a protein may always result in losing the configuration entropy of the chemical compound , binding a protein ligand to a protein partner may have more complex behavior , such as gaining some flexibility in the TRPS system . A detailed study may be required to fully characterize and understand this behavior . As the LF monomer is more rigid , when ligand IGP binds to the active site , the flexibility changes between the LF monomer and the LBR monomer are also less substantial than those in the dimeric unit . In the LBR state , comparing the total entropy calculations shows that both α– and β–monomers are more flexible than the dimeric unit . In the isolated monomeric form , after ligand binding ( the LBR state ) , the subunit has more freedom to change its conformation slightly to minimize the entropic penalty associated with gain of enthalpy in ligand–protein binding . For example , Glu49 , Asp60 , Gln65 and Asp130 , which interact with the α–site ligand or communicate with the β–subunit , are able to form H–bonds with different atoms . The carboxylate or amide groups of these residues flip along with the sidechain ( See Figure 2 in Text S1 ) , which preserves the flexibility but forms multiple sets of H–bonds to gain reasonable substrate–protein interactions . Similarly , the LBR state shows a frequent flipping of carboxylate group coupled with the sidechain rotation in Glu350 and Glu172 of the β–active site in the isolated β–monomer . Figure 5 displays the percentage of H–bond networks for LBR monomeric and dimeric units for residues at the α/β–interface and active sites . Details regarding average distances and angles of H–bond are given in the Table 1 in Text S1 . We found that in TRPS , generally , the loss of inter–subunit H–bond at the α/β–interface in the isolated monomeric unit is partly compensated by the formation of new H–bond networks within the subunit ( see Figure 5a ) , as was also reported for other monomeric proteins [73] . We observed that the total number of H–bonds in the LBR monomeric states increased by at least 3–4 times as compared to the dimeric units ( data not shown ) . Therefore , the isolated monomeric units are not less stable than the dimeric units energetically . In contrast , the dimeric unit has less room to adopt different protein conformations , which results in larger entropy loss in the LBR state . However , some residues ( blue circles in Figure 6 ( c–d ) ) at the β–interface and in the β–active site show strong correlations with other interfacial residues and residues present in the β–active site of the LBR β–dimeric complex . These correlations are almost diminished in the isolated β–monomeric complex . Overall , the effects of ligand binding and oligomerization on the 2 subunits are considerably different . The reasons may be that i ) the β–subunit is larger and more rigid than the α–subunit , ii ) the β–active site is buried within the subunit , right beneath the COMM domain and located relatively far from the interface as compared with the α–active site , and iii ) the motion of the COMM domain in the β–active site is small as compared with the motion of loops in the α–subunit . The correlations within the β–subunit are minor as well ( Figure 6 ) . For example , residues involved in the communication with the α–subunit , 165 to 181 in the β–H6 of the COMM domain ( pink rectangular box ) , are correlated weakly with the β–interface ( green underline ) and the β–active site residues ( cyan underline ) in both the monomeric and dimeric units . An increasing number of studies show that co-localization of proteins contributes to the efficiency of cellular signaling events and metabolic pathways [74]–[75] . TRPS is one of the model systems , and the dimeric unit is the minimal function structure . To mimic nature's synergy , one recent strategy is to engineer proteins that consider their spatial organization [76] . However , for enzymes such as TRPS , which are involved in regulation and synchronization in producing intermediate and final products , simply assembling multiple proteins in close proximity may not be enough . The dimeric unit forms a channel for efficient intermediate transportation , but the α– and β–subunits also use the inter–subunit interactions to assist in conformational transitions and synchronize the reactions in both active sites . Our studies suggest that without a protein partner , both of the isolated α– and β–monomers form a stable and fully closed conformation when ligands are both bound in the active sites , which is the active form of the enzyme . However , the monomers , in particular the isolated α–monomer , may require an extended time to transit from an open/inactive form to a closed/active form . Forming the dimeric unit does not rigidify TRPS to form a pre–organized conformation for ligand access and to reduce entropic loss upon ligand binding . However , instead , it stabilizes the protein when the protein conformation is perturbed by the substrates during the binding processes . As a result , the dimeric unit has a smoother active–inactive transition . Notably , for both the isolated monomers and dimeric unit , the proteins sample both open and partially closed conformations , but the open ( inactive ) form is favored while the ligand is unbound in the LF state . Presumably , because the hydrophobic interface provides alternative sidechain contacts and inter–subunit interactions , the dimeric unit is more flexible than the isolated monomer . Although the more flexible LF state in the dimeric TRPS results in larger configuration entropy loss upon ligand binding , we suggest that it also contributes to ligand recruitment . While a substrate is loosely bound to the binding site , the active–inactive transition rates increase , as was recently suggested by Zhou [77] . The binding sites are moving toward the fully closed conformation , and the binding mechanism gradually shifts from population shift ( conformation selection ) to induced fit [78]–[80] . However , as revealed by our simulations , the more unstable monomeric conformations in the ligand binding processes introduce a larger transition barrier; thus the transition rates can be decreased significantly . The dimeric unit uses the inter–subunit interactions to make the conformational transition easier . In the LB state , the ΔEtot of the isolated α–monomer is ∼9 kcal/mol larger than that of the α/β–dimeric unit , while the ΔEtot for the β–monomeric and the dimeric unit lies within the standard error ( see Table 3 ) . The value suggests that the transition rate may be decreased by several orders of magnitude in the isolated α–monomer but reduced only a little in the isolated β–monomer . The results are in good agreement with experiments showing that the catalytic rate is ∼100 times slower in the isolated α–monomer but only 1 . 5 times slower in the isolated β–monomer as compared with the αββα tetramer [28]–[29] . The calculation further supports our conjecture that one major role of oligomerization in TRPS is to help the ligand binding processes . In the LBR state , the isolated monomers show frequent flipping of the carboxylate group in key catalytical residues , such as α–Glu49 , but the flipping rarely occurs in the dimeric unit . Multiple sets of H–bonds are established by the flipping of a carboxylate or an amide group and sidechain rotations , so the ligand–protein interactions are not weakened . However , the fluctuations can decrease the catalytic rate in the isolated monomeric units . Our work suggests that for residues directly involved in the catalysis , rigid sidechains are preferred for optimized protein function . A similar point has been concluded for the homomeric BX1 protein , whereby the protein has a rigid Glu134 , the residue having the same role as α–Glu49 , to enhance the catalytic rates [34] . One of the unique features of the TRPS dimeric unit is substrate channeling . Conformational changes may affect the availability of the channel , and a fully closed conformation is necessary to avoid intermediate escape [81] . Protecting indole from diffusing away from TRPS is crucial for producing the final product , tryptophan , because the intermediate is relatively unstable in solution . Considering the significance of substrate channeling and the challenge of studying the process experimentally , we carried out CGBD simulation to explore the indole channeling processes ( See Figure 7 ) . The transportation of indole in the LBR state is smooth and rapid . Almost all , 99 . 6% , of indole can reach the β–active site within 4 µs , and the average travel time is 39 ns . In contrast , on the basis of 4 different LF protein conformations taken from the atomistic simulations , only ∼50% of indole can reach the β–active site in the LF state . Note that we manually placed an indole to the α–active site in the LF state to simulate indole diffusion when TRPS is in open conformation . The travel time of indole towards the β–active site in the LF state is similar to that in the LBR state , but about a half of indole escapes the α–active site from the open α–loop6 ( Figure 7a ) . In the LB state , where the protein is undergoing transition from an open to a fully closed form , indole does not always flow smoothly into the β–active site . A simulation from a snapshot taken from a 24-ns MD simulation showed that no indole could reach the β–active site , because of the channel blockage ( Figure 7b ) . Other simulations from snapshots taken from 2- to 48-ns MD simulations revealed a leak in the α/β–interface resulting in only 73% of indole successfully arriving at the β–active site . Our work suggests that the channel also has a dynamic characteristic , which is substantially influenced by the conformational changes at the active sites . An efficient substrate channeling with a maximal success rate is only possible when both subunits are in fully closed conformation , which is in good agreement with the experiments . Since both indole and the channel are mainly non-polar , no major attraction forces that steer indole to diffuse from the α–site to the β–site were observed . Instead , indole spends longer time in positions that have larger cavities , as the molecule can freely diffuse to all direction before reaching the β–active site . The detailed channeling profile has been explored with the CGBD , and the population of indole staying in the channel formed by one conformation in the LBR state is shown in Figure 8b . The peaks correspond to large space appeared in the channel . Because our model provides fairly large space in the α–active site , indole usually needs to diffuse around the site before finding the right direction to move forward . Moreover , our trajectories show that indole may diffuse back and forth a couple of times in the channel before finally reaching the β–active site , which may be one reason that the diffusion time is an order of magnitude slower than indole diffusion in water . Our coarse-grained model keeps the protein rigid , so it cannot represent correlation between intermediate diffusion and protein conformational changes . However , as indole is a small and neutral molecule , it is unlikely to have prominent intermediate–protein correlations to accelerate the intermediate diffusion . For systems where protein motions strongly correlate with ligand channeling , a fully flexible protein system with the use of multi-bead coarse-grain models may need to be applied to more accurately capture the role of protein motions [82]–[83] . The significance of protein oligomerization in nature is widely recognized . TRPS is a good model system revealing the crucial role of oligomerization in assuring successful ligand binding and enhancing the rates of chemical catalysis . This study showed that the oligomerization of the α– and β–subunits not only provides a direct channel for efficient intermediate transportation but also permits allosteric cooperativity via inter–subunit communications to assist with conformational transitions necessary to synchronize the reactions in both α– and β–active sites .
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Conformational changes of enzymes are often related to regulating and creating an optimal environment for efficient chemistry . An increasing number of evidences also indicate that oligomerization/co-localization of proteins contributes to the efficiency of metabolic pathways . Although static structures have been available for many multi-enzyme complexes , their efficiency is also governed by the synergistic regulation between the multi-units . Our study applies molecular dynamics and Brownian dynamics simulations to the model system , the tryptophan synthase complex . The multi-enzyme complex is a bienzyme nanomachine and its catalytic activity is intimately related to the allosteric signaling and the metabolite transfer between its α– and β–subunits connected by a 25-Å long channel . Our studies suggest that the binding partner is crucial for the ligand binding processes . Although the isolated monomers are stable in the ligand–free state and can form stable interaction if the substrate is in the final bound conformation , it has higher energy barrier when ligand binds to the active site . We also show that the channel does not always exist , but it may be blocked before the enzyme reaches its final bound conformation . The results highlight the importance of forming protein complexes and the cooperative changes during different states .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results/Discussion"
] |
[
"biochemistry/protein",
"chemistry",
"biophysics/theory",
"and",
"simulation",
"biochemistry/macromolecular",
"chemistry",
"biophysics/biomacromolecule-ligand",
"interactions",
"biochemistry/theory",
"and",
"simulation",
"biophysics"
] |
2010
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The Role of Oligomerization and Cooperative Regulation in Protein Function: The Case of Tryptophan Synthase
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Assembly of the Z-ring over unsegregated nucleoids is prevented by a process called nucleoid occlusion ( NO ) , which in Escherichia coli is partially mediated by SlmA . SlmA is a Z ring antagonist that is spatially regulated and activated by binding to specific DNA sequences ( SlmA binding sites , SBSs ) more abundant in the origin proximal region of the chromosome . However , the mechanism by which SBS bound SlmA ( activated form ) antagonizes Z ring assembly is controversial . Here , we report the isolation and characterization of two FtsZ mutants , FtsZ-K190V and FtsZ-D86N that confer resistance to activated SlmA . In trying to understand the basis of resistance of these mutants , we confirmed that activated SlmA antagonizes FtsZ polymerization and determined these mutants were resistant , even though they still bind SlmA . Investigation of SlmA binding to FtsZ revealed activated SlmA binds to the conserved C-terminal tail of FtsZ and that the ability of activated SlmA to antagonize FtsZ assembly required the presence of the tail . Together , these results lead to a model in which SlmA binding to an SBS is activated to bind the tail of FtsZ resulting in further interaction with FtsZ leading to depolymerization of FtsZ polymers . This model is strikingly similar to the model for the inhibitory mechanism of the spatial inhibitor MinCD .
The Z ring is a widely conserved cytoskeletal element required for prokaryotic cytokinesis [1] . It is assembled from polymers of FtsZ that are tethered to the membrane by interaction of the short conserved C-terminal tail of FtsZ with membrane anchoring proteins [2]–[4] . In the model organisms E . coli and B . subtilis the Z ring is restricted to midcell by the action of two negative regulatory systems , Min and nucleoid occlusion ( NO ) [3] , [5] . The Min system antagonizes Z ring assembly away from midcell while NO prevents Z ring assembly over the nucleoid . In their absence , cells fail to divide due to FtsZ forming many spurious assemblies that are unable to mature into a functional Z ring [6] , [7] . Both regulatory systems employ inhibitors of Z ring assembly that are dynamically positioned by interaction with structures within the cell . The products of the Min system interact with the membrane and the NO factors interact with the nucleoid [6]–[8] . The effector of the Min system is the FtsZ antagonist MinC , which is recruited to the membrane by MinD [9] , [10] . The inhibitory MinC/MinD complex is positioned near the poles of the cell by MinE in E . coli and MinJ/DivIVA in B . subtilis [11]–[14] . MinC/MinD efficiently blocks Z ring formation by interacting with FtsZ filaments in two steps [9] . MinC/MinD first binds to the conserved tail of FtsZ through the C-terminal domain of MinC [15] . Binding to the tail of FtsZ within FtsZ filaments brings the N-terminal domain of MinC near the FtsZ filament , which is proposed to attack the filament , resulting in shortening of the filament [16] . The effectors of the NO system are SlmA in E . coli and Noc in B . subtilis [6] , [7] . Both effectors are DNA binding proteins that are positioned within the cell by binding to specific sequences more prevalent in the origin proximal region of the chromosome [17]–[19] . SlmA is a member of the TetR family of repressors and has been shown to interact directly with FtsZ [7] . Noc is a member of the ParB family whose target is currently unknown [6] . These effectors are spatially regulated by the asymmetric distribution of their binding sites and the segregation of the replicating chromosome , which removes SlmA ( Noc ) from midcell [17]–[19] . Although it is established that binding to DNA activates SlmA to be an antagonist of Z ring assembly , there is disagreement over the mechanism . One study found that SlmA binding to an SBS activated SlmA to antagonize FtsZ polymerization [17] . Another study found that SlmA bound to an SBS as a dimer of dimers and that the dimers may spread from the SBS , however , antagonism of FtsZ polymerization was not observed [20] . It was proposed that the SlmA dimers bound to an SBS recruited FtsZ filaments and this prevented FtsZ filaments from coalescing into a Z ring [20] . A recent study identified residues on SlmA important for interaction with FtsZ [21] , however , the SlmA binding site on FtsZ is not known . In this study we isolated FtsZ mutants that are resistant to SlmA . We confirmed that SlmA antagonizes FtsZ assembly and these mutants are resistant . We also found that SlmA binds the tail of FtsZ and this interaction is required for SlmA to antagonize FtsZ polymerization . Together , these results suggest a model for SlmA action that has similarities to the mechanism employed by MinC/MinD .
FtsZ mutants resistant to SlmA were isolated by taking advantage of the observation that delocalization of SlmA from the nucleoid to SBS sites on a multicopy plasmid inhibits Z ring formation [17] , [21] . The advantage of using this approach is that a 4 fold overexpression of SlmA blocks colony formation , whereas in the absence of a plasmid containing SBS sites a 40 fold increase in SlmA is required to block colony formation , which also blocks chromosome segregation [17] , [21] . The coding region of ftsZ was subjected to PCR random mutagenesis and used to replace ftsZ in pBANG112 , which produces close to ( ∼1 . 5× ) the physiological level of FtsZ [15] . Three independent libraries were introduced into the strain DU11/pKD3C&pSD133 ( W3110 ftsZ0 recA::Tn10 slmA<>frt pKD3C [ftsZ+] & pSD133 [Ptac::slmA] ) and transformants selected at 42°C . Only a functional ftsZ on pBANG112 allows colony formation since pKD3C is temperature sensitive for replication . Transformants from each of the 3 libraries were separately pooled and transformed with plasmid p2SBSK , which contains two SBS sites . Transformants were selected in the presence of 20 µM IPTG since cells with wild type FtsZ are unable to form colonies at 10 µM IPTG and above 40 µM IPTG chromosome segregation is affected . Plasmids isolated from the survivors were retested to confirm their resistance and subjected to sequencing to identify ftsZ mutations . Sequence analysis revealed that most of these resistant mutants contained the same amino acid substitution ( ftsZ-K190I ) in helix H7 that connects the two sub-domains of FtsZ ( Fig . 1A ) . Some of the ftsZ-K190I containing mutants also had other amino acid substitutions in ftsZ , but were not more resistant than the single mutant ( Table S1 ) . Another mutation , ftsZ-D86N , which alters a residue in helix H3 ( Fig . 1A ) , was isolated twice , once as a double mutation ftsZ-D86N&G95D and once as a triple mutation ftsZ-D86N&S246Y&M344I . Subsequent analysis showed that the resistance was mainly due to ftsZ-D86N ( Table S1 ) . Despite screening 3 independent libraries , and verifying the quality of the mutagenesis by selecting and identifying mutations that confer resistance to MinCD ( data not shown ) , these were the only mutations recovered . Reintroduction of the above two mutations , ftsZ-K190I and ftsZ-D86N , into pBANG112 confirmed that they complemented the ftsZ depletion strain DU11/pKD3C at 42°C and conferred resistance to SlmA in the presence of p2SBSK ( Fig . S1 ) . Such complemented strains also grew at 37°C and 30°C , although both had a mild twisted-septal phenotype at or below 37°C ( data not shown ) . Additional substitutions were introduced at these positions to see if mutants could be obtained that displayed resistance without altering the cell morphology . Changing ftsZ-K190 to Ala , Leu , Glu , Asp , Trp and Val conferred various levels of resistance ( Fig . S1 ) . The ftsZ-K190V mutation produced a similar level of resistance as ftsZ-K190I and displayed a better morphology ( Fig . S1 ) . A positive charge at position 190 in FtsZ may be important for SlmA action since ftsZ-K190R was as sensitive to SlmA as the WT ( Fig . S1 and Table S1 ) . Changing D86 to Lys also reduced the sensitivity to SBS-SlmA , but the D86K substitution , as well as other substitutions at this position , either compromised the essential activity of FtsZ or had no effect on the resistance to SBS-SlmA ( Fig . S1 , Table S1 ) . Since ftsZ-K190V and ftsZ-D86N displayed resistance to the delocalized SlmA with the least effect on cell morphology , they were chosen for further study . To make sure the resistance phenotypes of ftsZ-K190V and ftsZ-D86N were not affected by the slightly higher expression level from the plasmid the mutations were introduced onto the chromosome at the ftsZ locus using the lambda RED recombineering system [22] . The resultant strains SD160 ( ftsZ-K190V ) and SD163 ( ftsZ-D86N ) grew as well as the wild type strain at all temperatures tested ( Fig . S2B ) . The morphology of the cells , however , varied with temperature ( Fig . S2A ) . At 42°C and 37°C , cells from both SD160 ( ftsZ-K190V ) and SD163 ( ftsZ-D86N ) looked similar to wild type , whereas at 30°C , a small fraction of SD160 ( ftsZ-K190V ) cells and a larger fraction of SD163 ( ftsZ-D86N ) cells displayed a twisted-septal morphology . Inactivation of slmA in these strains to create SD161 ( ftsZ-K190V slmA::cat ) and SD165 ( ftsZ-D86N slmA::cat ) did not result in any additional changes in morphology ( Fig . 1C ) . Combining the ftsZ-K190V and ftsZ-D86N mutations ( SD164 [ftsZ-K190V ftsZ-D86N] ) resulted in cold sensitivity for growth and lysis at midcell so the combination was not studied further ( Fig . S2 ) . The creation of the strains SD161 ( ftsZ-K190V slmA::cat ) and SD165 ( ftsZ-D86N slmA::cat ) allowed us to test the resistance of FtsZ-K190V and FtsZ-D86N to delocalized SBS-SlmA at the physiological level of FtsZ . As shown in Fig . 1B , the ftsZ-WT strain SD110 ( slmA::cat ) containing an SlmA expression plasmid ( pSD133 ) along with a plasmid carrying two SBS sites ( p2SBSK ) failed to form colonies at or above 10 µM IPTG . However , the mutant strains harboring the same pair of plasmids survived at higher concentrations of IPTG , with SD161 ( ftsZ-K190V slmA::cat ) surviving at higher levels than SD165 ( ftsZ-D86N slmA::cat ) . Microscopic examination of the ftsZ-WT strain ( SD110 [slmA::cat] ) revealed that exponentially growing cells were extremely filamentous even without IPTG induction whereas cells of strain SD161 ( ftsZ-K190V slmA::cat ) were not filamentous at 10 µM IPTG but became mildly elongated as the IPTG concentration was increased ( Fig . 1C ) . The FtsZ-D86N mutant showed a similar pattern , but cells were more filamentous at equivalent IPTG concentrations ( Fig . 1C ) . DAPI staining confirmed that there was no obvious DNA segregation problem at these IPTG concentrations ( data not shown ) . Therefore , both ftsZ-K190V and ftsZ-D86N provide resistance to extra SBS bound SlmA , with ftsZ-K190V providing more resistance than ftsZ-D86N . The induction of SlmA in the absence of the SBS plasmid resulted in filamentation at 40 µM IPTG and inhibition of growth at 100 µM IPTG . The filamentation is due to FtsZ being recruited to the nucleoids [5] and FtsZ-K190V provides some resistance ( Fig . 1C; vector panels ) . The inhibition of colony formation is due to inhibition of division and an effect on DNA segregation [17] and neither FtsZ mutant provides resistance to the segregation effect . SlmA-T33A is a SlmA mutant unable to bind DNA and is therefore defective in nucleoid occlusion [17] . However , it disrupts Z ring formation when overproduced sufficiently in vivo , suggesting that the DNA-free form of SlmA can still interact with FtsZ and inhibit division [17] . Expression of SlmA-T33A from plasmid pSD128-T33A ( this plasmid produces a higher level of SlmA than pSD133 due to a modification of the ribosome binding site ) in SD110 ( slmA::cat ) prevented colony formation on plates with 40 µM IPTG or above ( Fig . S3A ) . In contrast , strains SD161 ( ftsZ-K190V slmA::cat ) and SD165 ( ftsZ-D86N slmA::cat ) carrying pSD128-T33A ( slmA-T33 ) survived at 1000 µM IPTG and 100 µM IPTG respectively . Microscopic analysis revealed that at 100 µM IPTG , the wild type strain was homogeneously filamentous whereas the FtsZ-K190V mutant was not and FtsZ-D86N was slightly elongated ( Fig . S3B ) . Thus , these FtsZ mutants provide resistance to the unactivated SlmA ( not DNA bound ) as well as to activated SlmA . A reduction in the GTPase activity of FtsZ is a common nonspecific mechanism of resistance to inhibitors of FtsZ , such as SulA and MinC [23] , [24] . If either ftsZ-K190V or ftsZ-D86N displayed resistance to these inhibitors , it would suggest that the GTPase activity of these mutants was compromised . However , neither ftsZ-K190V nor ftsZ-D86N displayed resistance to SulA ( Fig . S4A ) . Also , microscopic examination of SD160 ( ftsZ-K190V ) and SD163 ( ftsZ-D86N ) in which MinCD was over expressed revealed that the cells were as filamentous as wild type cells expressing MinCD at each IPTG concentration examined ( Fig . S4B ) . Consistent with this , neither SD160 ( ftsZ-K190V ) nor SD163 ( ftsZ-D86N ) produces minicells ( Fig . S2 ) . Thus , these alleles display no significant resistance to SulA or MinC indicating the resistance is specific to SlmA . Deletion of SlmA does not have a strong phenotype , but loss of SlmA is synthetic lethal with Δmin as the double mutant fails to assemble complete functional Z rings [7] . If the two FtsZ mutants are resistant to SlmA they should be synthetic lethal with Δmin . Although it is not completely understood , the synthetic lethality of ΔminΔslmA is temperature sensitive as the double mutant grows at 42°C but not below 37°C [16] . Thus we created strains SD162 ( ftsZ-K190V min::kan ) and SD167 ( ftsZ-D86N min::kan ) at 42°C and then monitored their growth upon shift to 30°C . As reported , the ΔminΔslmA double mutant DU5 ( min::kan slmA::cat ) could not form single colonies at 30°C on an LB plate , however , both SD162 ( ftsZ-K190V min::kan ) and SD167 ( ftsZ-D86N min::kan ) were able to grow at 30°C indicating they were not synthetic lethal with Δmin ( Fig . S5A ) . Microscopic analysis of the cell morphology indicated that cells of SD162 ( ftsZ-K190V min::kan ) were much longer than the cells of the min deletion strain S4 ( min::kan ) , while cells of SD167 ( ftsZ-D86N min::kan ) were similar to S4 ( min::kan ) ( Fig . S5B ) . To quantify the difference between them , we measured the average cell lengths of all four strains grown at 42°C and after they were shifted to 30°C for two and a half hours . The Δmin strain only increased slightly in cell length after the shift , whereas the ΔminΔslmA double mutant DU5 stopped dividing and the average cell length increased to 26 . 8 µm ( Table S2 ) . The average cell length of strain SD162 ( ftsZ-K190V min::kan ) increased from 6 . 8 µm to 16 . 7 µm indicating decreased division at 30°C . The cell length of SD167 ( ftsZ-D86N min::kan ) also increased , but it was similar to that of the min deletion strain S4 min::kan ) . These results indicate that the more resistant ftsZ-K190V is synthetic sick with Δmin while the less resistant ftsZ-D86N is not . Since some aspects of this test are not well understood , we sought an additional test . SlmA is required to prevent septation over an unreplicated nucleoid following DnaA depletion and is presumably responsible for the lack of septa forming over unsegregated nucleoids in a ParCTS mutant at the nonpermissive temperature [7] , [25] . To confirm this , SD139 ( parCTS ) and SD140 ( parCTS slmA::cat ) were examined 1 hour after a shift to 42°C to inactivate ParC . DAPI was added to the culture shortly before microscopic examination so that septation over the DNA could be visualized . Cells containing WT SlmA ( SD139 parCTS ) were mildly elongated and contained a single nucleoid mass ( Fig . 2A ) . The percentage of cells with septa ( 17 . 6%; N = 1495 ) was about one half that of cells grown at 30°C ( 29 . 5%; N = 1278 ) and among the cells with septa , 21 . 7% ( N = 263 ) were over the DNA ( Fig . 2B ) . The percentage of cells with septa was much higher in the ΔslmA strain ( SD140 parCTS slmA::cat ) at the non-permissive temperature ( 74%; N = 955 ) and more than half of the septa were over the nucleoid ( 63 . 9%; N = 707 ) . Therefore , SlmA mediated nucleoid occlusion is required to reduce the formation of septa over unsegregated chromosomes due to ParC deficiency . To test if FtsZ-K190V and FtsZ-D86N were resistant to SlmA mediated nucleoid occlusion , strains SD170 ( parCTS ftsZ-K190V ) and SD171 ( parCTS ftsZ-D86N ) were generated by P1 mediated transduction . These strains were subjected to the same treatment as above and septa over the nucleoid were counted . Similar to SD140 ( parCTS slmA::cat ) , more than 60% of cells ( 62 . 5%; N = 1295 ) of the SD170 strain ( parCTS ftsZ-K190V ) were observed with septa when shifted to non-permissive temperature , and about half of these septa ( 47 . 7%; N = 809 ) occurred over the nucleoid . Cells of SD171 ( parCTS ftsZ-D86N ) displayed a similar percentage of cells with septa ( 62 . 5%; N = 1113 ) and the percentage of the septa over the nucleoid ( 40 . 7%; N = 698 ) was slightly lower , but still higher than the WT FtsZ control . Together , these results indicate that ftsZ-K190V and ftsZ-D86N allow septation over unsegregated nucleoids and are , therefore refractory to SlmA . The in vivo results demonstrate that FtsZ-K190V and FtsZ-D86N display resistance to the extra SBS/SlmA . We wanted to test their resistance in vitro , however , there is controversy in the literature about the effect SlmA has on FtsZ assembly . In one study [17] SlmA bound SBS antagonized FtsZ assembly whereas in another study [20] SlmA bound SBS had no effect on polymerization and it was suggested that SlmA/SBS affected higher order assembly of FtsZ filaments . To determine the effect of SlmA/SBS on FtsZ assembly we examined FtsZ polymerization by electron microscopy using purified 6×His-SlmA in the presence of SBS site 17 present on a 30mer ( SBS17-30mer ) . The presence of 6×His-SlmA or the SBS17-30mer alone had no effect on FtsZ assembly , however , the presence of both dramatically decreased the amount and length of FtsZ polymers with the buffer routinely used in the laboratory ( Fig . 3A; panels on left ) . This effect was also observed in both buffers used in the previous studies as well ( Fig . S6 ) . The polymers are mostly single-stranded under the conditions used due to the presence of 100–200 mM salt . To try and determine why different effects of SlmA/SBS were observed in the previous studies the effects of different DNAs were compared . Although all DNAs carried a similar SBS , the length of the flanking sequence varied . Reducing the length of the DNA from 30 to 20 , 18 or 14 did not affect SlmA binding to the SBS but reduced the antagonistic effect on FtsZ assembly ( Figs . S6B&S9C ) . With these shorter DNA fragments the abundance and length of polymers was still reduced , but not to the same extent as with the 30mer . It is not clear why decreasing the length of the flanking sequences decreased the activity of SlmA . In the study that reported SlmA/SBS did not affect polymerization it was suggested that the polymers bound to the SlmA would clash and would be unable to propagate [20] . To test this we examined the effect of 6×His-SlmA/SBS17-30mer on stable FtsZ polymers formed in the presence of GMPCPP . Although FtsZ polymers have an increased tendency to bundle in the presence of GMPCPP ( compared to GTP ) , the morphology was not influenced by the addition of SlmA or the SBS17-30mer alone . However , the addition of 6×His-SlmA and SBS17-30mer together led to a dramatic increase in bundling ( Fig . 3B ) . This bundling was observed regardless of the length of the DNA containing the SBS ( Fig . S6C ) . These bundles did not consist of simple alignment of FtsZ filaments , but had an altered appearance consistent with SBS bound SlmA bridging the FtsZ polymers ( Fig . 3C ) . This result indicates that SlmA bound to DNA does not cause FtsZ filaments to clash such that their growth would be hindered . Since SlmA bound to the SBS17-30mer caused a drastic reduction in the formation of polymers we proceeded to test its effect on the two FtsZ mutants . As shown in Fig . 3A , FtsZ-K190V ( 2 µM ) assembled into mostly single-stranded filaments similar to WT FtsZ , whereas the filaments formed by FtsZ-D86N had an increased tendency to bundle . The enhanced bundling of FtsZ-D86N was more dramatic when the reactions were carried out at a higher concentration ( 5 µM ) ( data not shown ) . Polymers formed by two FtsZ mutants ( FtsZ-K190V and FtsZ-D86N ) were not detectably affected by the addition of either 6×His-SlmA ( 2 µM ) or SBS17-30mer DNA ( 2 µM ) alone ( Fig . S7 ) . Although the assembly of WT FtsZ was significantly reduced by the addition of 6×His-SlmA ( 2 µM ) in the presence of SBS17-30mer DNA ( 2 µM ) , the assembly of FtsZ-K190V was only mildly affected; the filaments seemed to be somewhat shorter and not as smooth as FtsZ-K190V filaments without additions ( Fig . 3A ) . Even though filaments formed by FtsZ-D86N were still readily detected upon addition of 6×His-SlmA ( 2 µM ) in the presence of SBS17-30mer DNA ( 2 µM ) , the filaments and bundles were less and shorter compared to what was observed with FtsZ-K190V and 6×His-SlmA . These results indicate that these mutants display resistance to SlmA bound to an SBS in vitro with FtsZ-K190V displaying more resistance than FtsZ-D86N , consistent with its greater resistance to SlmA in vivo . There are at least two ways that mutations in ftsZ could confer resistance to SlmA: 1 ) substitution of important residues at the FtsZ-SlmA interaction interface or 2 ) lowering the GTPase activity of FtsZ . The latter seems unlikely since the mutants did not display resistance to SulA or MinC . Direct measurement of the GTPase activity revealed that both mutants displayed GTPase activity similar to wild type ( Table S3 ) . Therefore , we used several different tests to examine the interaction between the FtsZ mutants and SlmA . The two mutations did not affect the ability of FtsZ to associate with SlmA in the bacterial two-hybrid system as both mutants showed the same weak level of interaction with SlmA as wild type FtsZ ( Fig . S8A ) . Since the interaction in the two-hybrid system is weak several additional tests were done to examine the interaction . Cho et . al showed that SlmA bound to an SBS co-sedimented with stable FtsZ polymers ( using an FtsZ mutant that was GTPase deficient ) [17] . Stable polymers are also formed in the presence of the slowly hydrolysable analogue GMPCPP . As shown in Fig . 4A , the co-sedimentation of 6×His-SlmA ( 5 µM ) with FtsZ-GMPCPP ( 5 µM ) polymers was stimulated by the presence of SBS17-30mer DNA ( 2 µM ) . Control experiments showed that 6×His-SlmA-R73D ( deficient in FtsZ interaction ) did not co-sediment with FtsZ-GMPCPP in the presence of the SBS17-30mer ( Fig . S8C ) and 6×His-SlmA bound to SBS17-30mer did not sediment in the absence of FtsZ ( Fig . S8B ) . Consistent with the bacterial two hybrid results , 6×His-SlmA bound to SBS17-30mer co-sedimented with FtsZ-K190V and FtsZ-D86N ( Fig . 4A ) . Inspection of the reactions by electron microscopy supported these results . As expected , addition of 6×His-SlmA alone did not affect the morphology of the polymers , however , the addition of 6×His-SlmA and SBS17-30mer DNA caused dramatic bundling of the mutant FtsZ polymers , similar to what was observed with WT FtsZ ( Fig . S8D ) . In a third approach we examined the interaction of SlmA/SBS with unpolymerized FtsZ . In this assay 6×His-SlmA is bound to biotinylated SBS17-30mer immobilized on a streptavidin coated biosensor . The DNA binding mutant 6×His-SlmA-T33A , did not bind whereas the FtsZ interaction mutants , 6×His-SlmA-R73D and 6×His-SlmA-F65A bound to the DNA like WT SlmA ( Fig . S9A ) [17] , [21] . The addition of FtsZ to the reaction containing 6×His-SlmA led to an increase in signal indicating binding , whereas the addition of FtsZ to the reaction containing 6×His-SlmA-R73D or 6×His-SlmA-F65A did not ( Fig . S9B ) . Importantly , both FtsZ-K190V and FtsZ-D86N bound to SlmA to a similar extent as WT FtsZ ( Fig . 4B ) , although FtsZ-K190V displayed slower binding kinetics . If the components in the assay were inverted ( His-FtsZ or His-FtsZ-K190V immobilized on a Ni-NTA biosensor and SlmA/SBS17-30mer added ) , however , no difference in binding kinetics was observed ( Fig . S9D ) . Thus , the resistance of FtsZ-K190V and FtsZ-D86N to SlmA does not appear to be due to a defect in the binding of activated SlmA to FtsZ . Interaction was also examined by attaching SlmA directly to the biosensor . When 6×-His-SlmA was attached to a Ni-NTA biosensor FtsZ binding was only detected if SlmA was preincubated with the SBS17-30mer ( data not shown ) . If 6×-His-FtsZ was bound to the biosensor no signal was observed with SlmA unless the concentration was increased to 50 µM ( Fig . S9C ) . However , in the presence of SBS17-30mer , SlmA gave a strong signal at a much lower concentration ( 1 µM ) , consistent with previous finding that SBS DNA activates SlmA to bind to FtsZ [17] . The Kd for SlmA/SBS17-30mer binding to 6×-His-FtsZ was determined to be 0 . 21 µM , similar to that previously reported using another technique [19] . Our data strongly supports the model where SBS associated SlmA prevents Z ring formation over the nucleoid by antagonizing FtsZ polymerization . However , the mechanism by which activated SlmA antagonizes FtsZ polymerization is not clear . Previous studies showed that activated SlmA stimulates the GTPase activity of FtsZ and requires the GTPase activity of FtsZ to disassemble FtsZ filaments [17] . Such a mechanism is very similar to that proposed for MinC in which the N-terminus of MinC interacts with the α10 helix of FtsZ resulting in a shortening of FtsZ polymers [16] . Interestingly , SAXS analysis of SlmA-FtsZ or SBS-SlmA-FtsZ complexes indicated that SlmA contacts FtsZ near helix 10 ( Fig . S10A ) [19] , [20] . We therefore tested FtsZ mutants with substitutions in helix 10 that are resistant to the N-terminal domain of MinC [16] . A spot test showed that these mutants were actually slightly more sensitive to SlmA in the presence of extra SBSs ( Fig . S10B ) . Therefore , even if the α10 helix is involved in SlmA binding , the way it interacts with SlmA must be different than with MinC . In addition , the fact that SlmA still co-sedimented with the FtsZ-GMPCPP polymers suggests that the α10 helix is unlikely to be the primary binding site for SlmA because it is partially occluded in the FtsZ-GMPCPP polymers . The co-sedimentation of SlmA/SBS with stable FtsZ polymers indicates that activated SlmA must bind to the lateral surface of FtsZ polymers , the linker or the conserved C-terminal tail of FtsZ . A previous study reported that the conserved C-terminal tail of FtsZ was not required for SlmA binding [19] . To confirm this , we tested 6×His-FtsZ320 , which lacks the linker and the conserved C-terminal tail , to see if it would bind to SlmA using the biosensor assay . Surprisingly , 6×His-FtsZ320 did not bind to SlmA/SBS17-30mer immobilized on the biosensor ( Fig . 5A ) suggesting that either the linker region or the conserved C-terminal tail is necessary for SlmA binding . We next tested 6×His-FtsZ360 , which also did not bind , demonstrating the conserved C-terminal tail , and not the linker , is required for SlmA binding ( Fig . 5A ) . To ensure this lack of binding was not due to the 6×His tag , we tested if FtsZ360 bound to the SlmA/SBS17-30mer . Consistent with the other results , FtsZ360 exhibited no binding signal with SlmA/SBS17-30mer , while 6×His-FtsZ and FtsZ both bound to SlmA/SBS17-30mer preloaded on the biosensor ( Fig . 5A and Fig . 6A ) . Thus , the conserved C-terminal tail of FtsZ is required for SlmA to bind to FtsZ . To test if the conserved tail of FtsZ is required for interaction between SlmA and FtsZ polymers , we tested whether SlmA bound to a SBS17-30mer co-sedimented with stable 6×His-FtsZ360 polymers assembled with GMPCPP . As shown in Fig . 5B , SBS17-30mer DNA stimulated SlmA to codsediment with FtsZ but not with FtsZ360 stable polymers . We also visualized the effect of SlmA bound to SBS17-30mer DNA on the morphology of the stable polymers . The dramatic bundling of the stable 6×His-FtsZ polymers induced by SlmA/SBS-30mer , was not observed with stable 6×His-FtsZ360 polymers ( Fig . S11 ) . Therefore , the conserved C-terminal tail of FtsZ is also necessary for SlmA to interact with polymerized FtsZ . We next checked whether the conserved C-terminal tail of FtsZ was required for SBS-SlmA induced disassembly of FtsZ polymers . As shown in Fig . 5C , 6×His-FtsZ360 , like 6×His-FtsZ , assembled into single and double stranded filaments in the absence of SlmA . The addition of SlmA along with SBS17-30mer DNA dramatically reduced the number and length of 6×His-FtsZ polymers but had no effect on 6×His-FtsZ360 polymers , indicating that the conserved C-terminal tail of FtsZ is required for disassembly of FtsZ polymers by SlmA bound to SBS17-30mer . This appears counterintuitive since the tail of FtsZ is not required for polymerization . The C-terminal tail of FtsZ ( DYLDIPAFLRKQAD383 ) is widely conserved in bacteria and many proteins involved in cell division have been reported to bind to the tail of FtsZ . In E . coli , there is evidence that the tail of FtsZ interacts with five different proteins , ZipA , FtsA , MinC , ZapD and ClpX [2] , [15] , [26]–[28] . FtsZ residues I374 and L378 are critical for the interaction with ZipA , FtsA and MinC [15] , [26] . Depending upon the amino acid substitutions at these two positions resistance to MinC-MinD or loss of interaction with ZipA and FtsA have been reported [16] , [26] . As the tail of FtsZ is required for FtsZ-SlmA interaction , it is highly likely that substitution of these two residues would also disrupt the FtsZ-SlmA interaction . Therefore , we generated FtsZ-I374K and FtsZ-L378E and tested their interaction with SlmA in the biosensor assay . As shown in Fig . 6A these mutants behaved like FtsZ360 as no binding signal was observed with SlmA bound to the SBS17-30mer immobilized on the biosensor . Thus , I374 and L378 are also important for the FtsZ-SlmA interaction . Previous studies revealed that ZipA and FtsA bind to the conserved C-terminal tail of FtsZ , although there are subtle differences in the sequence specificity [26] . Nonetheless , these proteins should compete with SlmA for binding to FtsZ . We therefore tested the C-terminal domain of ZipA , ZipA185–328 , which binds to FtsZ with high affinity [29] , [30] . As shown in Fig . 6B preincubation of FtsZ with ZipA185–328 prevented FtsZ binding to SlmA/SBS17-30mer in a concentration dependent manner . At a 1∶1 ratio of FtsZ to ZipA185–328 the binding signal for FtsZ with SlmA/SBS17-30mer decreased about 30% and at a 1∶5 ratio the binding signal was almost completely eliminated . These data demonstrate that SlmA competes with ZipA for the conserved tail of FtsZ indicating that the binding sites for these two proteins overlap . Previous studies have shown that a peptide corresponding to the C-terminal tail of FtsZ binds specifically to ZipA and FtsA [30] , [31] . Therefore , we tested a synthetic 14 amino acid peptide corresponding to the conserved C-terminal tail of FtsZ ( Ztail-WT , DYLDIPAFLRKQAD ) for binding to SlmA bound to SBS17-30mer . As shown in Fig . 6C , this peptide bound to SBS17-30mer-SlmA in a concentration dependent manner . Analysis of the binding curves revealed that the Kd for the peptide binding to SBS17-30mer-SlmA was 81±10 µM , dramatically lower than for full length FtsZ ( 0 . 21 µM; Table S4 ) . However , this is not unusual because the FtsZ tail peptide also displays low binding affinity for ZipA ( 20 µM ) and FtsA ( 50 µM ) [30] , [31] . Consistent with the results obtained above with the full length FtsZ tail mutants , the mutant peptides , Ztail-I374K and Ztail-L378E , did not bind to SlmA/SBS17-30mer even at the highest concentration tested ( 320 µM ) ( Fig . 6C ) . Furthermore , a peptide corresponding to the cytoplasmic domain of FtsN failed to bind SlmA . To further examine the FtsZ-SlmA interaction we looked at the ability of the Ztail-WT peptide to compete with FtsZ for binding to SlmA-SBS . Addition of the Ztail-WT peptide , but not mutant peptides ( Z-tail-I374K and Z-tail-L378E ) , led to a concentration dependent decrease in the binding of full length FtsZ ( Fig . 6D ) . Together , these results indicate that the binding of the Ztail-WT peptide to SlmA is specific . Some FtsZ tail mutants are insensitive to the division inhibitory activity of MinCC-MinD [15] . These FtsZ mutants , including Fts-D373E , I374V , A376P ( unpublished data ) , L378V and K380M , likely eliminate or reduce the interaction between FtsZ and MinCC but retain interaction with ZipA and FtsA ( they can replace WT FtsZ ) [15] . Each of these FtsZ mutants complemented DU11/pKD3C at 42°C when expressed from pBANG112 , however , DU11/pBANG112-L378V grew poorly and was not studied further . The well characterized FtsZ-I374V mutant was still sensitive to SlmA , indicating that although both SlmA and MinC bind to the conserved C-terminal tail of FtsZ , they must interact with the tail differently ( Fig . 7 ) . Most of the other mutants were also sensitive , however , FtsZ-K380M displayed a weak resistance to SlmA . The resistance of FtsZ-K380M to SlmA provides evidence that the interaction of SlmA with the conserved C-terminal tail of FtsZ is important in vivo .
Our finding that SlmA binds the tail of FtsZ was unexpected since it was reported that the tail of FtsZ was not involved in interaction with FtsZ [19] . However , after we failed to isolate FtsZ mutants defective in the binding of SlmA , a reexamination of the SlmA-FtsZ interaction revealed that the binding and activity of SlmA required the tail of FtsZ . We also demonstrated that ZipA competes with SlmA for the tail of FtsZ and that two of the more conserved residues in the tail , important for binding other partners of FtsZ , are required for the binding of SlmA . Thus , the conserved Z tail is required for interaction with at least six partners; FtsA , ZipA , MinC/MinD , ClpX , ZapD and SlmA . Although we did not isolate FtsZ tail mutants resistant to SlmA in our screen , we previously isolated FtsZ tail mutants resistant to MinC/MinD . We observed that one out of four of these mutants ( FtsZ-K380M ) also conferred a moderate level of resistance to SlmA providing in vivo evidence for the importance of the interaction between the FtsZ tail and SlmA . Since only one of these mutants conferred resistance to SlmA it argues , that although both inhibitors bind the same Z tail peptide , they bind the tail differently . Perhaps the interaction of the tail with SlmA too closely mimics one of the essential interactions with ZipA or FtsA whereas the binding to MinC/MinD is different enough that resistant mutants can be isolated without compromising an essential activity . The ability of SlmA to depolymerize FtsZ requires the tail of FtsZ which suggests that SlmA bound to DNA contacts FtsZ filaments anchored to the membrane . If so , SlmA bound to SBS sites must be at the periphery of the nucleoid so that it can interact with FtsZ filaments anchored to the membrane through interaction of the FtsZ tail with FtsA and ZipA . That some part of the nucleoid is in close proximity to the membrane is illustrated in Vibrio cholerae where the ToxR transcription regulator , an inner membrane protein , interacts directly with DNA to regulate the ToxR regulon [32] . The two FtsZ mutants we examined in detail were specifically resistant to SlmA as they displayed no resistance to SulA or MinC/MinD . Of the two , FtsZ-K190V was significantly more resistant than FtsZ-D86N . It not only displayed resistance to a higher level of SlmA but was synthetic sick with loss of Min . We do not know the basis of resistance for these mutants and suspect that the resistance of FtsZ-D86N may be indirect . Polymers of this mutant protein have an increased tendency to bundle in vitro as does FtsZ-D86K , which was reported earlier [33] , [34] . We observed that this latter mutant also displays a level of resistance similar to FtsZ-D86N and it is possible that this ability to bundle confers resistance . FtsZ-K190V confers significant resistance to SlmA . At the high levels of SlmA induction where the FtsZ-K190V mutant is killed , the killing is no longer dependent on the presence of the plasmid containing SBS sites and appears to be due to interference with DNA segregation as suggested earlier [17] . Interestingly , the K190 residue is located in the middle of the H7 helix , which is involved in conformational changes between the two sub-domains of the globular domain of FtsZ [35] . A mutation affecting the corresponding residue in Staphylococcus aureus FtsZ ( R191P ) confers resistance to the chemical inhibitor PC190723 , although it is not involved directly in binding the inhibitor [35] , [36] . One possibility is that SlmA stimulates a conformational change in FtsZ after binding to the tail of FtsZ by contacting a second region of FtsZ . If so , our mutant studies ( an arginine substitution does not provide resistance ) suggest that SlmA requires a positive charge at this residue of FtsZ to induce the change that destabilizes the filament . Evidence for a second interaction site between SlmA and FtsZ comes from SAXS studies where a weak interaction was detected between the globular domain of FtsZ and SlmA [19] . This interaction was independent of the tail of FtsZ , however , the resolution is too low to determine the residues in either protein that are involved . The initial model for SlmA action proposed upon discovery of SlmA was that SlmA bound to the DNA could compete with the membrane anchors for FtsZ and strip FtsZ filaments off the membrane [7] . Our finding that SlmA binds the tail of FtsZ is consistent with such a model , however , several factors suggest such a model is not sufficient . The first is that the number of SlmA molecules ( ∼400 ) in the cell is quite limited compared to the amount of FtsZ ( ∼5000 ) and its anchors ( FtsA ∼1000; ZipA ∼3500 ) and therefore unlikely to be sufficient to compete with the membrane anchors [7] , [37]–[39] . The second is the in vitro data showing that SlmA causes disassembly of FtsZ filaments . The third is the existence of the FtsZ mutants that we isolated , particularly FtsZ-K190V , which do not affect the tail of FtsZ yet are resistant to SlmA . If SlmA only interacted with the tail of FtsZ one would not expect it to exert a negative effect on polymerization , since the tail is not involved in polymerization . More recently , two models to account for SlmA action have been proposed . In one model SlmA bound to DNA activates SlmA to antagonize FtsZ assembly whereas in the second model FtsZ filaments bound to the SlmA/SBS complex are unable to assemble into a Z ring [17] , [20] . This latter model was proposed because SlmA was not observed to antagonize FtsZ assembly . Our in vitro results confirmed the previous finding from the Bernhardt lab that SlmA antagonizes FtsZ assembly . Furthermore , our finding that the tail of FtsZ is essential for this activity , even though the tail has no direct role in FtsZ polymerization , along with the resistance of the FtsZ-K190V mutant , indicates a more active role for SlmA than simple competition for the tail or sequestration . In our model SlmA bound to DNA is at the periphery of the nucleoid and comes into contact with FtsZ filaments tethered to the membrane by FtsA and ZipA ( Fig . 8 ) . Upon binding to a tail within the FtsZ filament SlmA makes an additional contact with FtsZ inducing a conformational change leading to breakage of the filament . This catalytic behavior of SlmA results in destruction of the filament . It will be of interest to see if this mechanism is used by spatial regulators of the Z ring in other organisms .
Strains and plasmids used in this study are listed in Tables S5 and S6 , respectively . Strains were grown in LB medium at 37°C unless otherwise indicated . When needed , antibiotics were used at the following concentrations: ampicillin = 100 µg/ml; spectinomycin = 25 µg/ml; kanamycin = 25 µg/ml; tetracycline = 25 µg/ml; and chloramphenicol = 20 µg/ml . The sequences of the various SBS DNA molecules are shown in Table S7 . The strain PS1603 ( W3110 slmA::cat ) was generated by S . Pichoff ( unpublished ) in which most of the slmA coding sequence was replaced with the cat gene expressing chloramphenicol resistance . The ΔminΔslmA double mutant strain DU5 ( W3110 min::kan , slmA::cat ) was generated by P1 transducing slmA::cat ( from PS1603 ) into the strain W3110 min::kan . Chloramphenicol and kanamycin resistant transductants were selected at 42°C . Strain DU11 ( W3110 ftsZ0 slmA<>frt recA::Tn10 ) /pKD3C was constructed in several steps . First strain S3 ( W3110 leu::Tn10 ) was transduced with P1 grown on TB85 ( MG1655 , slmA::kan ) [7] and kanamycin resistant transductants were selected . The purified transductant was named DU8 ( W3110 leu::Tn10 slmA::kan ) and transformed with plasmid pCP20 by selecting ampicillin resistance at 30°C . The transformants were then streaked on LB plates with tetracycline and incubated at 42°C to get eliminate the kan gene and plasmid pCP20 . The resultant strain was named DU9 ( W3110 leu::Tn10 slmA<>frt ) and confirmed by PCR using primers flanking the deleted region to confirm that the kan gene had been removed . Plasmid pKD3C was then transformed into DU9 and a purified transformant DU9/pKD3C was transduced with P1 grown on PB143 ( leu+ ftsZ0 recA::Tn10 ) by selecting for Leu+ at 30° on M9 minimum medium . The resultant transductants were screened for temperature sensitivity and tetracycline resistance and the desired transductant ( DU10/pKD3C ) should have a genotype leu+ ftsZ0 slmA<>frt with plasmid pKD3C [40] providing FtsZ . Finally , the recA::Tn10 allele from PB143 was transduced into DU10/pKD3C by selecting for tetracycline resistance on LB plates at 30°C . The resultant transductants were checked for UV sensitivity to confirm the inactivation of recA and the transductant was named DU11 ( W3110 leu+ ftsZ0 slmA<>frt recA::Tn10 ) /pKD3C . Strain SD139 and SD140 were constructed by transducing the parCTS allele from WM1033 ( MG1655 , parC281::Tn10 ) into strains W3110 and PS1603 respectively . The parCTS allele is linked to a Tn10 and tetracycline resistant transductants obtained at 30°C were checked for the TS phenotype at 42°C . Strains SD160 , SD163 and SD164 were constructed similarly by replacing the ftsZ84 allele on the chromosome of the parental strain PS106 with the ftsZ-K190V , ftsZ-D86N or ftsZ-K190V&D86N alleles using the lambda RED system [22] . PCR products of ftsZ fragments containing ftsZ-K190V , ftsZ-D86N or ftsZ-K190V&D86N mutations were electroporated into PS106/pKD46 induced with 0 . 04% arabinose for 3 hours at 30°C . The recombinants were selected on LB plates without salt at 42°C . 8 recombinants from the plates were randomly selected and then transformed with plasmid pSD133 and p2SBSK to check resistance to delocalized SBS bound SlmA . Recombinants resistant to SBS-SlmA were then checked for the presence of ftsZ-K190V , ftsZ-D86N or ftsZ-K190V&D86N by PCR and sequencing . SD161 and SD165 were constructed simply by introduction of the slmA::cat allele from PS1603 into strain SD160 and SD163 by P1 transduction . Similarly , strains SD162 and SD167 were created by P1 transduction to introduce the min::kan allele from S4 into strain SD160 and SD163 . Strains SD170 and SD171 were created in two steps . The first step was to remove the leu::Tn10 marker from SD160 and SD163 by transduction with P1 grown on PB143 ( leu+ ftsZ0 recA::Tn10 ) and then selecting for Leu+ transductants at 37°C on M9 minimum medium . Transdcutants were tested for tetracycline sensitivity and resistance to SlmA in the presence of the multicopy plasmid p2SBSK ( carries two SBS sites ) . The positive clones were named SD168 and SD169 and used as template for PCR to amplify the ftsZ gene and sequencing to make sure the colonies retained the ftsZ-K190V or ftsZ-D86N mutation . The second step was to introduce the parCTS allele into SD168 and SD169 obtained from the first step . SD168 and SD169 were transduced with P1 grown on WM1033 ( parCTS-Tn10 ) and tetracycline resistance transductants were selected at 30° . The colonies obtained were purified and tested for temperature sensitivity at 42°C and were named SD170 and SD171 . pUC18K was constructed by replacing the bla gene in pUC18 with kan . To do this , an XhoI site was first introduced into pUC18 ( pUC18blaX ) at the end of bla , using primers XhoI-5′: 5′-GTAACTGTCAGACCAAGTCTCGAGATATATACTTTAGATTG-3′ and XhoI-3′: 5′-CAATCTAAAGTATATATCTCGAGACTTGGTCTGACAGTTAC-3′ . The aph coding sequence from pKNT25 was amplified by using primers Kan-5′-SspI: 5′-CAGTAATATTCTGATCAAGAGACAGGATGAG-3′ and Kan-3′-XhoI: 5′-CAGTCTCGAGCATTTCGAACCCCAGAG-3′ . The PCR product was digested with SspI and XhoI and cloned into the same sites in puC18blaX ( XhoI ) to generate pUC18K . A derivative of pUC18K was made by introducing a fragment containing SBS12 and SBS17 to create p2SBSK . This fragment was obtained by PCR using primers SBS12-F-HindIII: 5′-GCATAAGCTTGCGAAGTGAACGCTAACTCACATCTAACAATGCGCTCATCG-3′ and SBS17-R-EcoRI: 5′-GCATGAATTCCGTTAGTGACCATTTACTTACTCAGGACGGGTGTGGTCGCCATG-3′ . The resulting PCR fragment contains a segment of pBR322 sandwiched between the SBS12 and SBS17 sites , and was digested with EcoRI and HindIII and ligated into pUC18K cut with same enzymes . Plasmid pSEB160 was created by S . Pichoff by inserting an SstI/HindIII digested fragment containing ftsZ into pBAD18 cut with the same enzymes ( unpublished data ) . pSEB160 derivatives containing ftsZ-360 , ftsZ-K190V , ftsZ-D86N , ftsZ-I374K and ftsZ-L378E were generated by site-directed mutagenesis . Plasmid pSD119 was created by replacing the ftsZ coding sequence of pSEB160 with sequence encoding 6× His tagged ftsZ amplified from pSEB160 using primers His-FtsZ-SstI: 5′-TTCGAGCTCAGGCGACAGGCACAAATCGGAGAGAAATATGCATCACCATCACCATCACTTTGAACCAATGGAACTTACC-3′ and His-FtsZ-HindIII: 5′-GCCAAAACAGAAGCTTCCTCGAAACCCAAATTCCAGTCAATTC-3′ . The amplified fragment was digested with SstI and HindIII and ligated to pSEB160 digested with the same enzymes . pSD119 derivatives for 6× His-ftsZ-320 and 6× His-ftsZ-360 expression were created by site directed mutagenesis by addition of two stop codons after codons FtsZ320 and FtsZ360 . Primers used are FtsZ320: 5′-GGCATGGACAAACGTTGATAAATCACTCTGGTGACC-3′ and FtsZ360: 5′-GCTAAAGTCGTGAATGACTGATAACCGCAAACTGCGAAAG-3′ . The plasmid pSD128 was constructed by inserting an EcoRI and HindIII fragment containing the slmA coding sequence into the EcoRI and HindIII double digested pBANG59 . The slmA containing fragment was amplified from chromosomal DNA using primers slmA-5′-EcoRI: 5′-AGTGAATTCTTTCAGGAGGATAATGTAACATGGCAGAAAAACAAACTG-3′ and slmA-3′-HindIII: 5′-GCGAAGCTTTTGGCGTTTAAAGAAACTC-3′ . The ribosome binding site for slmA translation was changed to the consensus sequence –AGGAGG- through this approach . The pSD128 derivatives containing different mutations were constructed by site-directed mutagenesis . Plasmid pSD133 containing slmA with its own ribosome binding site is otherwise similar to pSD128 and was constructed in a similar manner , but the slmA containing fragment was amplified from chromosomal DNA using different primer pairs: slmA-For: 5′-CGTGAATTCCGCCTGGCAAGTGCTTA-3′ and slmA-3′-HindIII . The plasmid pQE80-slmA was created by ligation of a BamHI-PstI fragment containing the slmA coding sequence and pQE80 ( Qiagen ) cut with the same enzymes . The fragment was amplified from chromosomal DNA using primers 5′-6×his-slmA: 5′-GTGGATCCGCAGAAAAACAAACTGCG-3′ and ttk-PstI-3′: 5′-GAAACTGCAGCGGCGTCATATTACTGC-3′ . Site-directed mutagenesis was used to introduce different slmA mutations into pQE80-slmA to obtain various derivatives . The plasmid pSD198 was created by ligation of a BamHI-HindIII fragment containing the zipA185–328 coding sequence and pQE80 ( Qiagen ) cut with the same enzymes . The fragment was amplified from chromosomal DNA using primers zipA185-5′-BamHI: 5′- GACTGGATCCGATAAACCGAAGCGCAAAG -3′ and zipA-3′-HindIII: 5′- GACTAAGCTTGGTTCGAAGAGGAGTTAAT-3′ . Plasmids pSlmA-T25 and pSlmA-T18 were constructed by inserting a BamHI/HindIII cut fragment containing the slmA coding sequence into the vectors pKNT25 and pUT18 , respectively , cut with the same enzymes . The fragment was amplified from chromosomal DNA using the primer pair slmA-BTHN-BamHI: 5′- GTCGGATCCTGCAACTGTGCCGCAAT-3′ and slmA-BTHN-HindIII: 5′- TGTAAGCTTGGCAGAAAAACAAACTG-3′ . Derivatives of pSlmA-T25 and pSlmA-T18 containing slmA mutations were created by site-directed mutagenesis . Plasmids pZT25 and pZT18 were made by inserting a BamH1/HindIII fragment containing the ftsZ coding sequence into pKNT25 and pUT18 , respectively . Derivatives of these plasmids containing various slmA mutations or ftsZ mutations were created by site-directed mutagenesis . Plasmid pSUMO-SlmA was constructed by ligation of a BsaI-XbaI fragment containing the slmA coding sequence and pE-SUMO-amp ( LiferSensors ) cut with the same enzyme . The fragment was amplified from plasmid pSD133 using primers slmA-SUMO-F: 5′-ACGTGGTCTCGAGGTGCAGAAAAACAAACTGCGAAAAG-3′ and SlmA-SUMO-R: 5′-CAGTTCTAGAGTCATCCGGCGTCATATTAC-3′ . The procedure was carried out as previously described for selection of MinCD resistant FtsZ mutants [15] . PCR random mutagenesis was used to introduce random mutations into the coding region of ftsZ gene using pBANG112 as the template and primers: 5′- GCCTCAGGCGACAGGCACAAATCGGAGAG and 5′-GCTGCAGATATTCGATATCACGCATGAAAC . The purified PCR fragments were then digested with EcoRI and EagI and ligated into pBANG112 digested with the same enzymes . The ligation product was then electroporated into DU11/pKD3C &pSD133 and transformants selected at 42°C on LB plates with ampicillin . All colonies that grew were pooled together and part of the pooled culture was subjected to plasmid extraction to make a stock of the FtsZ mutant library . To select for the SBS-SlmA resistant FtsZ mutants , the rest of the pooled cells was transformed with plasmid p2SBSK and colonies resistant to delocalized SBS-SlmA were selected with 20 µM IPTG at 30°C on plates containing ampicillin , spectinomycin and kanamycin . Plasmids were isolated from the colonies that grew up and the ftsZ gene in the plasmids was sequenced to identify the mutations . To detect SlmA-FtsZ and SlmA-SlmA interactions , appropriate plasmid pairs encoding FtsZ-T18 and SlmA-T25 or FtsZ-T18 and SlmA-T25 or their variants were co-transformed into BTH101 [41] . Single colonies were resuspended in 1 ml LB medium and 3 µl of each aliquot was spotted on LB plates containing 100 µg/ml ampicillin , 25 µg/ml kanamycin , 40 µg/ml X-gal and 250 µM IPTG . Plates were incubated at 30°C for 36 hours before analysis . His-SlmA and variants containing different mutations were expressed and purified from JS238/pQE80-slmA and its derivatives following the protocol used to purify 6×his-ZapA [23] . An overnight culture of each strain grown in LB with ampicillin ( 100 µg/ml ) and glucose ( 0 . 2% ) was diluted 1∶100 into 1 L fresh LB medium supplemented with ampicillin ( 100 µg/ml ) and incubated at 37°C until OD540 reached about 0 . 4 . IPTG was then added to the culture to a final concentration of 1 mM and incubated at 37°C for another 3 hours . Cells were collected by centrifugation , washed with 10 mM Tris-HCl ( pH 7 . 9 ) , and frozen at −80°C until used . On the day of purification , the cells were thawed and resuspended in 20 ml lysis buffer ( 20 mM Tris-HCl [pH 7 . 9] , 70 mM NaCl and 20 mM imidazole ) and passed through the French press twice ( 10 , 000 psi ) . The lysates were centrifuged at 12 , 000 rpm for 15 min at 4°C to remove cell debris . The supernatants were removed and loaded onto pre-equilibrated Ni-NTA resin ( Qiagen ) . The column was washed once with high salt wash buffer ( 20 mM Tris-HCl [pH 7 . 9] , 500 mM NaCl and 20 mM imidazole ) and once with the same buffer except with the imidazole concentration increased to 50 mM . The bound protein was eluted with elution buffer ( 20 mM Tris-HCl [pH 7 . 9] , 500 mM NaCl and 250 mM imidazole ) . The peak fractions were dialyzed against the storage buffer ( 25 mM Tris-HCl [pH 7 . 9] , 200 mM KCl , 1 mM EDTA and 10% glycerol ) overnight and stored at −80°C until use . The untagged version of SlmA was expressed and purified from BL21 ( λDE3 ) /pLysS cells containing pSUMO-SlmA . Purification of the H-SUMO-SlmA fusion protein was similar to purification of the 6×his-SlmA . After dialysis , the H-SUMO tag was cleaved with purified 6×His-tagged SUMO protease ( Ulp1 ) for 1 hour at 30°C in the protein storage buffer ( 25 mM Tris-HCl [pH 7 . 9] , 200 mM KCl , 1 mM EDTA and 10% glycerol ) with 1 mM DTT . The released tag and protease were removed by passing it through the pre-equilibrated Ni-NTA resin . Untagged SlmA was collected in the flow through , concentrated and stored at −80°C . N-terminal 6×His-tagged FtsZ , FtsZ320 and FtsZ360 were purified from JS238 cells containing plasmids pSD119 , pSD119-Z320 or pSD119-Z360 respectively . An overnight culture of each strain grown in LB with ampicillin ( 100 µg/ml ) and glucose ( 0 . 2% ) was diluted 1∶100 into 1 L fresh LB medium supplemented with ampicillin ( 100 µg/ml ) and incubated at 37°C until OD540 reached about 0 . 4 . Arabinose was then added to the culture to a final concentration of 0 . 2% and incubated at 37°C for another 3 hours . Cells were collected by centrifugation , washed with 10 mM Tris-HCl ( pH 7 . 9 ) , and frozen at −80°C until used . The subsequent procedures were similar to purification of 6×his-SlmA . Induction of wild type FtsZ , FtsZ-K190V and FtsZ-D86N was similar to induction of 6×His-tagged FtsZ in JS328 cells containing pSEB160 , pSEB160-360 , pSEB160-K190V , pSEB160-D86N , pSEB160-I374K and pSEB160-L378E respectively . After collecting the cells , FtsZ-WT , FtsZ-K190V and FtsZ-D86N as well as the other mutant proteins were purified according to the procedure described previously [15] , [42] . FtsZ polymerization reactions were in Pol buffer ( 50 mM HEPES-NaOH [pH 8 . 0] , 200 mM KCl and 10 mM MgCl2 ) . The SBS17 fragment ( 30 bp ) and SlmA or SlmA mutants were mixed together in a separate tube and incubated at room temperature for 10 minutes before addition to the polymerization reactions . Unless specified , the SlmA used was His tagged SlmA . The SBS17 probe used here was prepared by annealing two un-labeled complementary 30 base oligonucleotides SBS17-F and SBS17-R . FtsZ was added to a final concentration of 2 µM in a 50 µl reaction containing pre-formed SBS17-SlmA , or SBS17 alone , or SlmA or just DNA binding buffer . After 5 min incubation , GTP or GMPCPP was added to a final concentration of 1 mM and incubation at room temperature continued for another 5 min before the samples were loaded onto grids . 15 µl of 1% uranyl acetate was spotted on the grid for 1 min and blotted away . The grids were air-dried and imaged with a JEOL-JEM-1400 transmission electron microscope . The co-sedimentation assay was performed similarly as above except that the protein concentrations were 5 µM . After the addition of GMPCPP , the reactions were subjected to ultracentrifugation at 80 , 000 rpm for 15 min at 25°C in TLA100 . 2 rotor and a Beckman TL-100 centrifuge . Supernatants and pellets were then analyzed by SDS-PAGE . The assays were performed in 250 µl of 1× Pol buffer ( 50 mM HEPES-NaOH [pH 8 . 0] , 200 mM KCl , 10 mM MgCl2 ) using a biosensor system ( FortéBio ) at room temperature . The biotinylated SBS17 probe was prepared by annealing two complementary 30 base oligonucleotides , the biotinylated-SBS17-F and SBS17-R . FtsZ and SlmA proteins were diluted in 1× FtsZ polymerization buffer before the test . To measure the binding affinity of SlmA variants for the biotinylated SBS17 probe , streptavidin-coated biosensors tips were equilibrated with 1× Pol buffer to establish a baseline prior to biotinylated SBS17 immobilization . 250 µL of 1× Pol buffer containing 50 nM biotinylated SBS17 was incubated with the biosensor tips with shaking at 2 , 200 rpm for 5 minutes . After the immobilization , the biosensor tips were washed with 1× Pol buffer for 10 seconds . Association of SlmA-WT or SlmA mutants to the biosensors was monitored for 2 minutes in 250 µl 1× Pol buffer containing 4 µM SlmA with agitation at 2 , 200 r . p . m . Dissociation was initiated by dipping the biotinylated SBS17-SlmA coated biosensor tips into 250 µl of 1× Pol buffer , and the process was monitored continuously for 2 minutes while agitating at 2 , 200 rpm . Data were obtained automatically by the biosensor User Software ( FortéBio ) and were subsequently analyzed by global fitting using the GraphPad Prism 5 software . Binding of FtsZ to the biotinylated-SBS17-SlmA complex was performed similarly as above . After association of SlmA-WT or SlmA mutant to the biotinylated SBS17 coated biosensor tips , the tips were washed with 250 µl of 1× Pol buffer for 10 seconds . FtsZ was preincubated with 1 mM GDP for 5 minutes before the SBS17-SlmA complex coated biosensor tips were dipped into the solution . ZipA185–328 was added at different concentrations with GDP to see whether it blocked FtsZ binding to SBS-bound SlmA . Association was monitored for 1 minute in 250 µl of 1× FtsZ Pol buffer containing 4 µM FtsZ with agitation at 2 , 200 rpm followed by dissociation in the same buffer without FtsZ for 2 minutes . Data were collected and analyzed with Graphpad Prism 5 . In a reciprocal approach , 6×His-tagged FtsZ-FL , FtsZ320 or FtsZ360 was immobilized at the surface of Ni-NTA biosensors and untagged SlmA preincubated with or without SBS DNA was tested for binding to 6×His-tagged FtsZ variants . In these assays , 250 µL of 1× Pol buffer containing 1 µM 6×His-tagged FtsZ mutant was incubated with the biosensor tips with shaking at 2 , 200 r . p . m for 5 minutes . After the immobilization , the biosensor tips were washed with 1× Pol buffer for 10 seconds . Association of untagged SlmA preincubated with or without SBS DNA to the biosensors was monitored for 2 minutes in 250 µl 1× Pol buffer with agitation at 2 , 200 r . p . m . Dissociation was initiated by dipping the FtsZ-SBS-SlmA coated biosensor tips into 250 µl of 1× Pol buffer , and the process was monitored continuously for 2 minutes while agitating at 2 , 200 r . p . m . Data were generated automatically by the BLItz User Software version and were subsequently analyzed by global fitting using the GraphPad Prism 5 software .
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Bacteria divide in the middle of the cell by spatially regulating the position of the Z ring , a cytoskeletal element required for cytokinesis . In the model organisms , Escherichia coli and Bacillus subtilis , two negative regulatory systems contribute to this spatial regulation . Both systems contain antagonists of FtsZ assembly that are localized in the cell . In this study we isolated FtsZ mutants resistant to SlmA , which is positioned within the cell by binding to sites asymmetrically distributed around the chromosome . We confirm that SlmA is activated by DNA binding to antagonize FtsZ polymerization in vitro and that the newly isolated mutants are resistant . We also show that SlmA binds to the very conserved tail of FtsZ and that this is required to antagonize FtsZ assembly even though the tail is not required for polymerization . Together , these results highlight the importance of the tail of FtsZ and lead to a model in which SlmA binding to the tail of FtsZ results in further interactions that break the filament . This mechanism is shared with the other spatial regulator and raises the possibility that it may be a common mechanism among spatial regulators of Z ring assembly .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"microbial",
"growth",
"and",
"development",
"biology",
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"life",
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] |
2014
|
SlmA Antagonism of FtsZ Assembly Employs a Two-pronged Mechanism like MinCD
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Recently it has become clear that only a small percentage ( 7% ) of disease-associated single nucleotide polymorphisms ( SNPs ) are located in protein-coding regions , while the remaining 93% are located in gene regulatory regions or in intergenic regions . Thus , the understanding of how genetic variations control the expression of non-coding RNAs ( in a tissue-dependent manner ) has far-reaching implications . We tested the association of SNPs with expression levels ( eQTLs ) of large intergenic non-coding RNAs ( lincRNAs ) , using genome-wide gene expression and genotype data from five different tissues . We identified 112 cis-regulated lincRNAs , of which 45% could be replicated in an independent dataset . We observed that 75% of the SNPs affecting lincRNA expression ( lincRNA cis-eQTLs ) were specific to lincRNA alone and did not affect the expression of neighboring protein-coding genes . We show that this specific genotype-lincRNA expression correlation is tissue-dependent and that many of these lincRNA cis-eQTL SNPs are also associated with complex traits and diseases .
It is now evident that most of the human genome is transcribed to produce not only protein-coding transcripts but also large numbers of non-coding RNAs ( ncRNAs ) of different size [1] , [2] . Well-characterized short ncRNAs include microRNAs , small interfering RNAs , and piwi-interacting RNAs , whereas the large intergenic non-coding RNAs ( lincRNAs ) make up most of the long ncRNAs . LincRNAs are non-coding transcripts of more than 200 nucleotides long; they have an exon-intron-exon structure , similar to protein-coding genes , but do not encompass open-reading frames [3] . The recent description of more than 8 , 000 lincRNAs makes these the largest subclass of the non-coding transcriptome in humans [4] . Evidence is mounting that lincRNAs participate in a wide-range of biological processes such as regulation of epigenetic signatures and gene expression [5]–[7] , maintenance of pluripotency and differentiation of embryonic stem cells [8] . In addition , several individual lincRNAs have also been implicated in human diseases . A well-known example is a region on chromosome 9p21 that encompasses an antisense lincRNA , ANRIL ( antisense lincRNA of the INK4 locus ) . Genome-wide association studies ( GWAS ) have shown that this region is significantly associated with susceptibility to type 2 diabetes , coronary disease , and intracranial aneurysm as well as different types of cancers [9] and some of the associated SNPs have been shown to alter the transcription and processing of ANRIL transcripts [10] . Similarly , increased expression of lincRNA HOTAIR ( HOX antisense non-coding RNA ) in breast cancer is associated with poor prognosis and tumor metastasis [10] . Another example is MALAT-1 ( metastasis associated in lung adenocarcinoma transcript ) where the expression is three-fold higher in metastasizing tumors of non-small-cell lung cancer than in non-metastasizing tumors [11] . In addition , over the last decade , more than 1 , 200 GWAS have identified nearly 6 , 500 disease- or trait-predisposing SNPs , but only 7% of these are located in protein-coding regions [12] , [13] . The remaining 93% are located within non-coding regions [14] , suggesting that GWAS-associated SNPs regulate gene transcription levels rather than altering the protein-coding sequence or protein structure . Even though there is growing evidence to implicate lincRNAs in human diseases [15] , [16] , it is unknown whether disease-associated SNPs could affect the expression of non-coding RNAs . We hypothesized that GWAS-associated SNPs can affect the expression of lincRNA genes , thereby proposing a novel disease mechanism . To test this hypothesis , we performed eQTL mapping on 2 , 140 human lincRNA-probes using genome-wide gene expression and genotype data of 1 , 240 peripheral blood samples ( discovery cohort ) [17] . The lincRNA cis-eQTLs identified were then tested for replication in an independent cohort containing 891 peripheral blood samples ( replication cohort ) . Since lincRNAs are considered to be more tissue-specific than protein-coding genes [4] , we set-out to identify tissue-dependent cis-eQTLs for lincRNAs using data from another four different primary tissues from the subset of 85 individuals in our primary cohort [18] . Subsequently , we tested whether SNPs that affect the levels of lincRNA expression are associated with diseases or traits . Finally , we predicted the most likely function ( s ) of a subset of cis-eQTL lincRNAs by using co-regulation information from a compendium of approximately 80 , 000 expression arrays ( www . GeneNetwork . nl ) .
Whole-genome gene expression oligonucleotide arrays have played a crucial role in our understanding of gene regulatory networks . Even though most of the currently available commercial microarrays are designed to capture all known protein-coding transcripts , they still include subsets of probes that capture transcripts of unknown function ( sometimes abbreviated as TUF ) . We investigated whether the TUF probes present on the Illumina Human HT12v3 array , overlap with lincRNA transcripts that were recently described in the lincRNA catalog [4] . The lincRNA catalog contained a provisional set of 14 , 393 transcripts mapping to 8 , 273 lincRNA genes and a stringent set of 9 , 918 transcripts mapping to 4 , 283 lincRNA genes . We identified 2 , 140 unique probes that map to 1 , 771 different lincRNAs from the provisional set and 1 , 325 unique probes that map to 1 , 051 lincRNA genes from the stringent set . We chose 2 , 140 unique probes that mapped to lincRNAs from the provisional set for further eQTL analysis . It is known that in general lincRNAs are less abundantly expressed compared to protein-coding transcripts [4] . To test the expression levels of the 2 , 140 lincRNA probes in 1 , 240 peripheral blood samples ( discovery cohort ) , we compared the quantile-normalized , log scale transformed mean expression intensity as well as expression variation of the lincRNA probes to probes mapping to protein-coding transcripts . We indeed observed a significant difference in the expression levels , where lincRNA probes are less abundant ( mean expression = 6 . 67 ) than probes mapping to protein-coding transcripts ( mean expression = 6 . 92 , Wilcoxon Mann Whitney P<2 . 2×10−16; Figure S1 ) . We also observed a highly significant difference in the expression variation between lincRNA probes and probes mapping to protein-coding transcripts ( Wilcoxon Mann Whitney P<3 . 85×10−96 ) . Next , we tested whether the expression of these 2 , 140 lincRNA probes is affected by SNPs in cis , by performing eQTL mapping in these 1 , 240 peripheral blood samples for which genotype data was also available . We confined our analysis to SNP-probe combinations for which the distance from the center of the probe to the genomic location of the SNP was ≤250 kb . In the end , at a false-discovery rate ( FDR ) of 0 . 05 , we identified 5 , 201 significant SNP-probe combinations , reflecting 4 , 644 different SNPs; these affected the expression of 112 out of 2 , 140 different lincRNA probes . The 112 lincRNA probes mapped to 108 lincRNA genes and comprised 5 . 2% of all tested lincRNA probes , with a nominal significance ranging from P<2 . 8×10−4 to 9 . 81×10−198 in peripheral blood ( Table S1 ) . We then performed a replication analysis to test the reproducibility of the identified 112 lincRNA cis-eQTLs using an independent dataset of 891 whole peripheral blood samples . We took the 112 lincRNA-probes ( or 5 , 201 SNP-probe pairs ) that were significantly affected by cis-eQTLs in the discovery cohort and tested whether these eQTLs were also significant in the replication dataset ( at FDR 0 . 05 ) . We could replicate 45% of the 112 lincRNA cis-eQTLs at an FDR<0 . 05 , of which all the eQTLs had an identical allelic direction ( Figure S2 ) . The smaller sample size of the replication cohort compared to the discovery cohort makes it inherently difficult to replicate all the cis-eQTLs that we have detected in the discovery cohort . Our observation that 5 . 2% of all tested lincRNAs are cis-regulated ( Table S1 ) might seem disappointing , compared to our earlier observation that 25% of the protein-coding probes in this dataset are cis-regulated [18] . However , we reasoned that the generally lower expression levels of lincRNAs compared to protein-coding genes might make it more difficult to detect cis-eQTLs for lincRNAs , as the influence of background noise becomes substantial for less abundant transcripts , making accurate expression quantification difficult ( Figure S1A ) . Indeed , we found significantly higher expression levels for the 112 cis-eQTL lincRNA probes ( mean expression = 6 . 80 ) compared to the 2 , 028 non-eQTL lincRNA probes ( mean expression = 6 . 66 Wilcoxon Mann Whitney P = 3 . 88×10−15; Figure S3 ) and also observed a significant difference in expression variance between the 112 cis-eQTL lincRNAs compared to the 2 , 028 non-cis eQTL lincRNAs ( Wilcoxon Mann Whitney P = 1 . 067×10−8 ) , indicating that lower overall expression levels do make identification of cis-eQTLs more difficult . To further confirm the relationship between average expression levels of probes and the number of detectable cis-eQTLs , we first mapped cis-eQTLs for an equal set of 2 , 140 probes that were instead protein-coding and were the most abundantly expressed of all protein-coding probes . We also conducted cis-eQTL mapping for a set of 2 , 140 protein-coding probes that had been selected to have an identical expression intensity distribution as the 2 , 140 lincRNA probes ( i . e . matched for mean expression intensity and standard deviation ) , using the same 1 , 240 blood samples ( Figure 1A ) . We indeed observed a profound relationship between average expression levels of protein-coding transcripts and the number of detectable cis-eQTLs . Eighty percent of the 2 , 140 most abundantly expressed protein-coding probes showed a cis-eQTL effect , whereas only 10% of the protein-coding probes that had been matched for an expression intensity of the 2 , 140 lincRNA-probes were affected by cis-eQTLs ( Figure 1B ) . Hence it is possible that if we can accurately quantify all lincRNAs in large RNA-sequencing datasets , we will be able to identify cis-eQTLs for a larger proportion of all lincRNAs . It could be possible that the SNPs that affect lincRNA expression actually operate by first affecting protein-coding gene expression levels , which in turn affect lincRNA expression . If this were to be the case , our identified lincRNA cis-eQTLs would merely be a by-product of protein-coding cis-eQTLs . To ascertain this , we tested whether the 112 lincRNA-eQTL SNPs were also significantly affecting neighboring protein-coding genes . By keeping the same significance threshold ( at FDR<0 . 05 level , the P-value threshold was 2 . 4×10−4 ) , we observed that nearly 75% ( 83 out of 112 ) of the lincRNA-eQTLs were affecting only lincRNAs , even though the interrogated neighboring protein-coding genes were generally more abundantly expressed than the lincRNAs themselves ( Figure S4 ) . Genetic variants can thus directly regulate the expression levels of lincRNAs . We found 29 cis-eQTLs to be associated with the expression of both lincRNA and protein coding genes . For 50% of these 29 cis-eQTLs , we found that the expression of lincRNAs and protein-coding genes was in the opposite direction , whereas for the other 50% of cis-eQTLs , both types of transcripts were co-regulated in the same direction ( Figure S5 ) . We tested whether these 29 cis-eQTLs are the strongest eQTLs for both lincRNA and protein-coding genes . Although these 29 cis-eQTLs were the strongest eQTLs for lincRNAs , only 5 among 29 were also the strongest eQTLs for protein-coding genes . This observation further highlights the direct regulation of lincRNA expression through genetic variants . There is considerable interest in mapping eQTLs in disease-relevant tissue types . We reasoned that since expression of the lincRNAs seems to be much more tissue-specific than the expression of protein-coding genes [4] , mapping lincRNA-eQTLs in different tissues could reveal additional , tissue-specific lincRNA-eQTLs . To test this , we analyzed gene expression and genotype data of 74 liver samples , 62 muscle samples , 83 subcutaneous adipose tissue ( SAT ) samples , and 77 visceral adipose tissue ( VAT ) samples from our primary cohort of 85 unrelated , obese Dutch individuals [18] . Upon cis-eQTL mapping we detected 35 cis-eQTL-probes , of which 18 were specific in the four different non-blood tissues , resulting in a total of 130 lincRNA-eQTLs in the combined set of all five tissues ( Table S1 ) . Five cis-eQTLs identified in blood tissue were also significantly replicated in at least one other non-blood tissue ( Table S1 ) . While we could replicate 45% of the cis-eQTLs in the substantial whole peripheral blood replication cohort , the replication rate in the very small cohorts for fat , liver and muscle tissue was , as expected , much lower . We were able to observe tissue-specific lincRNA eQTLs in muscle ( 1 ) , liver ( 4 ) , SAT ( 9 ) and blood ( 107 ) ( Figure S6 ) . Since the four non-blood tissue expression levels were from the same individuals , these results do indeed provide evidence that some of the lincRNAs are regulated by genetic variants in a tissue-specific manner . As most of the GWAS-associated SNPs are located within non-coding regions , we tested whether the 130 lincRNA-eQTLs identified in five different tissues are also GWAS-associated variants . To do this , we intersected trait-associated SNPs ( at reported nominal P<9 . 9×10−6 , retrieved from the catalog of published genome-wide association studies per 26 July 2012 ) [14] with the 130 top lincRNA cis-eQTLs and their proxies ( proxies with R2>0 . 8 using the 1000Genome CEU population as reference ) . We identified 12 GWAS SNPs or their proxies , that were also a lincRNA cis-eQTLs of eight different lincRNA genes ( Table 1 ) . All except one of the 12 SNPs were exclusively associated with lincRNA expression and thus did not affect the expression levels of neighboring protein-coding genes ( Table 1 ) , suggesting a causative role of altered lincRNA expression for these phenotypes . Notably SNP rs13278062 at 8p21 . 1 , associated with exudative age-related macular degeneration ( AMD ) in the Japanese population , was reported to alter the transcriptional levels of TNFRSF10A ( Tumor necrosis factor receptor superfamily 10A ) protein-coding gene [19] . Here we identified SNP rs13278062 as a highly significant cis-eQTL of lincRNA XLOC_006742 ( LOC389641 ) ( P = 4 . 31×10−32 ) rather than for TNFRSF10A ( P = 4 . 21×10−4 ) protein-coding gene ( Figure S7 ) . Furthermore , SNP rs13278062 is located in exon 1 of lincRNA XLOC_006742 , which encompasses an ENCODE ( Encyclopedia of DNA elements ) enhancer region characterized by H3K27acetylation and DNaseI hypersensitive clusters [20] ( Figure S8 ) . Another interesting example is at 17q21 . 31 where three Parkinson's disease associated SNPs were in strong linkage disequilibrium ( R2>0 . 8 ) with top cis-eQTL SNP rs199439 , which affects lincRNA XLOC_012496 expression exclusively in SAT ( Table 1 ) . Weight loss due to body-fat wasting is a very common but poorly understood phenomenon in Parkinson's disease patients [21] . In this regard , it is intriguing to note that the Parkinson's disease associated SNPs affects lincRNA expression exclusively in fat tissue ( Table 1 ) . Hence , identifying lincRNA-eQTLs in disease-relevant tissue types using larger groups of individuals may open up new avenues towards achieving a better understanding of disease mechanisms . Our observations suggest a role for lincRNAs in complex diseases and other phenotypes . The next , rather daunting task is to elucidate the function of these ncRNAs . We recently developed a co-regulation network ( GeneNetwork , www . genenetwork . nl/genenetwork , manuscript in preparation ) , to predict the function of any transcript based on co-expression data extracted from approximately 80 , 000 Affymetrix microarray experiments ( see Methods ) . We interrogated the GeneNetwork database to predict the function of eQTL-affected lincRNAs . Among the 130 cis-eQTL lincRNAs that we had identified in the five different tissues , 43 were represented by expression probe sets on Affymetrix arrays for which we could predict the function ( Table S2 ) . These 43 probes include four out of eight disease-associated lincRNAs described above ( Table 1 ) and function prediction for these probes provided relevant biological explanations . It has been reported that some transcribed long ncRNAs function as enhancers that regulate the expression of neighboring genes [3] and may thereby contribute to the disease pathology . We found that the AMD-associated lincRNA XLOC_006742 ( LOC389641 ) ( by virtue of SNP rs13278062 which exhibits a significant eQTL effect ) ( Figure S7 ) is in strong co-expression with TNFRSF10A based on our GeneNetwork database ( Table S3 ) . AMD is a leading cause of blindness among elderly individuals worldwide and recent studies , both in animal models and in humans , provide compelling evidence for the role of immune system cells in its pathogenesis [22] . The gene TNFRSF10A , which encodes TRAIL receptor 1 ( TRAIL1 ) , has been implicated as a causative gene for AMD [19] . It has been shown that binding of TRAIL to TRAILR1 can induce apoptosis through caspase 8 activation [23] and using GeneNetwork we also predict a role in apoptosis for lincRNA XLOC_006742 ( Table S2 ) . Another trait-associated SNP , rs11065766 , is the top cis-eQTL of lincRNA XLOC_009878 ( ENSG00000185847 or RP1-46F2 . 2 or LOC100131138 ) and it is in strong linkage disequilibrium with two SNPs associated with alcohol drinking behavior ( Table 1 ) . We found that the lincRNA XLOC_009878 is strongly co-expressed with the neighboring protein-coding gene MYL2 ( Table S4 ) and , according to our predictions , lincRNA XLOC_009878 is involved in striated muscle contraction ( P = 1 . 22×10−26 ) . Chronic alcohol abuse can lead to striking changes in skeletal muscle structure , which in turn plays a role in the development of alcoholic myopathy and/or cardiomyopathy [24] . It has also been reported that alcohol can reduce the content of skeletal muscle proteins such as titin and nebulin to affect muscle function in rats [25] . We found lincRNA XLOC_009878 to be co-expressed with titin and many other skeletal muscle proteins necessary for the structural integrity of the muscle ( Table S4 ) . Thus , it needs to be tested whether deregulation of lincRNA XLOC_009878 expression might alter an individual's ability to metabolize alcohol due to changes in the muscle functional property . We found that more than 70% of the lincRNA cis-eQTLs from both blood and non-blood tissues were located in intergenic regions with respect to protein-coding genes ( Figure 2A ) . We also found high frequencies of lincRNA cis-eQTLs to be located around transcriptional start site ( Figure 2B ) , suggesting that these cis-eQTLs may affect the expression of lincRNAs through similar gene regulatory mechanisms as those seen for protein-coding cis-eQTLs . Thus , in order to understand the mechanism of how lincRNA cis-eQTLs affect lincRNA expression , we intersected the location of top 112 lincRNA cis-eQTLs and their proxies ( r2 = 1 ) in blood with regulatory regions using the HaploReg database [26] . The results suggested that indeed most of the lincRNA cis-eQTLs ( 69% ) were located in functionally important regulatory regions ( Figure S8 ) , which contained DNAse I regions , transcription factor binding regions , and histone marks of promoter and enhancer regions . Furthermore , these cis-eQTLs were found to be located more often within blood cell-specific enhancers ( K562 and GM12878 ) ( Figure 3A ) , suggesting that some of these cis-eQTLs regulate lincRNA expression in a tissue-specific manner through altering these enhancer sequences . Since we observed enrichment of cell-specific enhancers for lincRNA cis-eQTLs within blood cells ( K562 and GM12878 ) , we compared the fold enrichment of enhancers in these two cell types to see whether lincRNA cis-eQTLs are more often located in functionally important regions than any random set of SNPs . We found a significant difference in the enrichment of enhancers in which more than a 4-fold enrichment was seen for real cis-eQTLs both in K562 cells ( P = 0 . 0004 ) and GM12878 cells ( P = 0 . 011 ) compared to permuted SNPs . These findings suggest that some of the identified lincRNA cis-eQTLs are indeed functional SNPs .
Even though it may have been expected that lincRNA expression would be under genetic control , this is the first study , to our knowledge , to comprehensively establish this link . We were able to identify cis-eQTLs in five different tissues and have demonstrated that common genetic variants regulate the expression of lincRNAs alone . It is intriguing that around 75% of lincRNA cis-eQTLs are specific to lincRNAs alone , but not to protein-coding genes . Recent data from the ENCODE project suggests that combinations of different transcription factors are involved in regulating gene-expression in different cell types and non-coding RNAs tend to be regulated by certain combinations of transcription factors more often than others [27] . Thus , it could still be possible that some transcription factors specifically regulate lincRNA expression . We also observed a strong relationship between whether or not a transcript is affected by cis-eQTLs and its expression levels , where highly abundant transcripts were more often affected by cis-eQTLs . This relationship was comparable between lincRNA and protein-coding probes , although protein-coding probes ( matched for expression levels of lincRNA probes ) tend to show more cis-eQTLs ( Figure 1B; 5 . 2% versus 10% ) . Although this difference is not drastic , it may suggest that lincRNAs exhibit another layer of gene regulation which is more tissue-specific . Thus , we may expect to identify many more lincRNA cis-eQTLs once larger datasets of different tissues become available . One limitation of our study is the lack of probes to comprehensively map eQTLs to all the reported lincRNAs , as we relied upon microarrays . Future analyses using RNA-sequencing datasets will undoubtedly provide much more insight into how genetic variants affect lincRNA expression . So far , two landmark RNA-sequencing based eQTL studies have been published using 60 ( Montgomery et al ) [28] and 69 samples ( Pickrell et al ) [29] , respectively . While Pickrell et al did not mention lincRNAs with a cis-eQTL effect , Montgomery et al identified six cis-regulated lincRNAs ( at a slightly higher FDR of 0 . 17 ) . We re-analyzed these two datasets and found that we could replicate one of the 112 cis-eQTL lincRNAs effects that we detected using arrays ( with an identical allelic direction; Figure S10 ) . These results indicate that cis-eQTL lincRNAs detected using conventional microarrays can be replicated in sequencing-based datasets . However , it also indicates that sample size is currently a limiting factor in finding many more cis-eQTL lincRNAs in sequencing-based datasets . Nevertheless , our results clearly indicate that there is a strong genotype-lincRNA expression correlation that is tissue-dependent . A considerable number of the observed lincRNA cis-eQTLs are disease- or trait-associated SNPs . Since lincRNAs can regulate the expression of protein-coding genes either in cis [3] or in trans [8] , lincRNA-eQTLs represent a novel link between non-coding SNPs and the expression of protein-coding genes . Our examples show that this link can be exploited to understand the process of gene-regulation in more detail , which may assist us in characterizing lincRNAs as another class of disease biomarkers .
This study was approved by the Medical Ethical Board of Maastricht University Medical Center ( four non-blood tissues ) , and local ethical review boards ( 1 , 240 peripheral blood samples ) in line with the guidelines of the 1975 Declaration of Helsinki . Informed consent in writing was obtained from each subject personally . The subject information is provided in Table S5 . A detailed mapping strategy of Illumina expression probe sequences has been described previously [17] . We extracted 43 , 202 expression probes mapping to single genomic locations ( hg18 build ) and excluded those that did not map or that mapped to multiple different loci . LincRNA chromosomal coordinates ( hg19 build ) were obtained from the lincRNA catalog ( http://www . broadinstitute . org/genome_bio/human_lincrnas/ ? q=lincRNA_catalog ) and converted to hg18 coordinates using UCSC's LiftOver application ( http://genome . ucsc . edu/cgi-bin/hgLiftOver ) . Subsequently , we extracted probes mapping to lincRNA exonic regions by employing BEDtools [30] . The blood dataset and a detailed eQTL mapping strategy have been described previously [17] . Briefly , 1 , 240 peripheral blood samples from unrelated , Dutch control subjects were investigated ( Table S5 ) . Genotyping of these samples was performed according to Illumina's standard protocols ( Illumina , San Diego , USA ) , using either the HumanHap370 or 610-Quad platforms . Because the non-blood samples ( see below ) were genotyped using Illumina HumanOmni1-Quad BeadChips , we applied IMPUTE v2 [31] to impute the genotypes of SNPs that were covered by the Omni1-Quad chip but that were not included on the Hap370 or 610-Quad platforms [31] . Anti-sense RNA was synthesized using the Ambion Illumina TotalPrep Amplification Kit ( Ambion , New York , USA ) following the manufacturer's protocol . Genome-wide gene expression data was obtained by hybridizing complementary RNA to Illumina's HumanHT-12v3 array and subsequently scanning these chips on the Illumina BeadArray Reader . We used a dataset comprising peripheral blood samples of 891 unrelated individuals from the Estonian Genome Centre , University of Tartu ( EGCUT ) biobank cohort of 53 , 000 samples for replication . Genotyping of these samples was performed according to Illumina's standard protocols , using Illumina Human370CNV arrays ( Illumina Inc . , San Diego , US ) , and imputed using IMPUTE v2 [31] , using the HapMap CEU phase 2 genotypes ( release #24 , build 36 ) . Whole peripheral blood RNA samples were collected using Tempus Blood RNA Tubes ( Life Technologies , NY , USA ) , and RNA was extracted using Tempus Spin RNA Isolation Kit ( Life Technologies , NY , USA ) . Quality was measured by NanoDrop 1000 Spectrophotometer ( Thermo Fisher Scientific , DE , USA ) and Agilent 2100 Bioanalyzer ( Agilent Technologies , CA , USA ) . Whole-Genome gene-expression levels were obtained by Illumina Human HT12v3 arrays ( Illumina Inc , San Diego , US ) according to manufacturers' protocols . Previously we described tissue-dependent eQTLs in 74 liver samples , 62 muscle samples , 83 SAT samples and 77 VAT samples from a cohort of 85 unrelated , obese Dutch individuals ( all four tissues were available for 48 individuals ) [18] ( Table S5 ) . These samples were genotyped according to standard protocols from Illumina , using Illumina HumanOmni-Quad BeadChips ( Omni1 ) . Genome-wide gene expression data of all samples was assayed by hybridizing complementary RNA to the Illumina HumanHT-12v3 array and then scanning it on the BeadArray Reader . The method for normalization and principal component analysis-based correction of expression data , along with the methods to control population stratification and SNP quality , were described previously [17] , [18] . The cis-eQTL analysis was performed on probe-SNP combinations for which the distance from the center of the probe to the genomic location of the SNP was ≤250 kb . Associations were tested by non-parametric Spearman's rank correlation test and the P values were corrected for multiple testing by false-discovery rate ( FDR ) at P<0 . 05 , in which the distribution was obtained from permuting expression phenotypes relative to genotypes 100 times within the HT12v3 dataset and comparing those with the observed P-value distribution . At FDR = 0 . 05 level , the P-value threshold was 2 . 4×10−4 for significantly associated probe-SNP pairs in blood , 1 . 5×10−5 in SAT , 5 . 21×10−6 in VAT , 6 . 3×10−6 in liver and 1 . 8×10−6 in muscle . To predict the function ( s ) for lincRNAs , we interrogated the GeneNetwork database ( www . genenetwork . nl/genenetwork ) that has been developed in our lab ( manuscript in preparation ) . In short , this database contains data extracted from approximately 80 , 000 microarray experiments that is publically available from the Gene Expression Omnibus; after extensive quality control , it contains data on 54 , 736 human , 17 , 081 mouse and 6 , 023 rat Affymetrix array experiments . Principal component analysis was performed on probe-set correlation matrices of each of four platforms ( two human platforms , one mouse and one rat platform ) , resulting in 777 , 377 , 677 and 375 robust principal components , respectively . Jointly these components explain between 79% and 90% of the variance in the data , depending on the species or platform . Many of these components are well conserved across species and enriched for known biological phenomena . Because of this , we were able to combine the results into a multi-species gene network with 19 , 997 unique human genes , allowing us to utilize the principal components to accurately predict gene function by using a ‘guilt-by-association’ procedure ( a description of the method is available at www . genenetwork . nl/genenetwork ) . Predictions were made based on pathways and gene sets from Gene Ontology , KEGG , BioCarta , TransFac and Reactome . We employed the HaploReg web tool [26] to intersect SNPs ( and their perfect proxies , r2 = 1 using the CEU samples from the 1000 Genomes project ) with regulatory information and also to calculate the fold enrichment of cell-type specific enhancers . In order to ascertain whether this enrichment was higher than expected , we took eQTL results from 100 permutations ( shuffling the gene expression identifier labels ) : for each permutation we determined the top 112 eQTL probes and took the corresponding top SNPs and their perfect proxies ( r2 = 1 ) . We extracted the fold enrichment of enhancers from HaploReg for these 100 sets of SNPs as well , which then permitted us to estimate the significance of enrichment of the real eQTL analysis , determined by fitting a normal distribution on the 100 log-transformed permutation enrichment scores .
|
Large intergenic non-coding RNAs ( lincRNAs ) are the largest class of non-coding RNA molecules in the human genome . Many genome-wide association studies ( GWAS ) have mapped disease-associated genetic variants ( SNPs ) to , or in , the vicinity of such lincRNA regions . However , it is not clear how these SNPs can affect the disease . We tested whether SNPs were also associated with the lincRNA expression levels in five different human primary tissues . We observed that there is a strong genotype-lincRNA expression correlation that is tissue-dependent . Many of the observed lincRNA cis-eQTLs are disease- or trait-associated SNPs . Our results suggest that lincRNA-eQTLs represent a novel link between non-coding SNPs and the expression of protein-coding genes , which can be exploited to understand the process of gene-regulation through lincRNAs in more detail .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"genome-wide",
"association",
"studies",
"gene",
"expression",
"genetics",
"biology",
"genetics",
"of",
"disease",
"genetics",
"and",
"genomics",
"gene",
"function"
] |
2013
|
Human Disease-Associated Genetic Variation Impacts Large Intergenic Non-Coding RNA Expression
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Yellow fever ( YF ) is an acute viral hemorrhagic disease transmitted by Aedes mosquitoes . The causative agent , the yellow fever virus ( YFV ) , is found in tropical and subtropical areas of South America and Africa . Although a vaccine is available since the 1930s , YF still causes thousands of deaths and several outbreaks have recently occurred in Africa . Therefore , rapid and reliable diagnostic methods easy to perform in low-resources settings could have a major impact on early detection of outbreaks and implementation of appropriate response strategies such as vaccination and/or vector control . The aim of this study was to develop a YFV nucleic acid detection method applicable in outbreak investigations and surveillance studies in low-resource and field settings . The method should be simple , robust , rapid and reliable . Therefore , we adopted an isothermal approach and developed a recombinase polymerase amplification ( RPA ) assay which can be performed with a small portable instrument and easy-to-use lyophilized reagents . The assay was developed in three different formats ( real-time with or without microfluidic semi-automated system and lateral-flow assay ) to evaluate their application for different purposes . Analytical specificity and sensitivity were evaluated with a wide panel of viruses and serial dilutions of YFV RNA . Mosquito pools and spiked human plasma samples were also tested for assay validation . Finally , real-time RPA in portable format was tested under field conditions in Senegal . The assay was able to detect 20 different YFV strains and demonstrated no cross-reactions with closely related viruses . The RPA assay proved to be a robust , portable method with a low detection limit ( <21 genome equivalent copies per reaction ) and rapid processing time ( <20 min ) . Results from real-time RPA field testing were comparable to results obtained in the laboratory , thus confirming our method is suitable for YFV detection in low-resource settings .
Yellow fever ( YF ) has been one of the most feared diseases during the past centuries , its historical impact ranking next to plague and smallpox . Unfortunately , unlike smallpox , YF virus ( YFV ) cannot be eradicated as its transmission by mosquitoes includes a sylvatic cycle . Despite the use of an effective vaccine since the 1930s , the World Health Organization ( WHO ) estimates that the disease affects more than 200 , 000 persons causing 30 , 000 deaths per year [1] . YF remains an important public health problem for the populations of 44 countries , 33 in Africa and 11 in Central and South America , where altogether almost 900 million people are at risk . In recent years , the number of YF cases has increased [2] , and there is great concern that the disease might be introduced into new areas [3] . Recently , severe outbreaks have occurred in regions of Africa that have long been free of the virus , such as Darfur in Sudan or South Omo in Ethiopia which experienced the worst YF outbreak in Africa in 20 years in 2012 [4] . YFV is the prototype of the genus Flavivirus ( family Flaviviridae ) which comprises more than 80 positive-sense , single-stranded RNA viruses , including other human pathogens such as dengue , West Nile virus , Usutu virus , Zika virus , Japanese encephalitis virus and Tick-borne encephalitis virus [5] . Diagnosis of YFV infection is very challenging as the early symptoms caused by YFV are not specific . Laboratory confirmation is therefore essential for the differential diagnosis of YF with leptospirosis , malaria , viral hepatitis and other hemorrhagic diseases . Laboratory testing is also challenged by the short duration of the YF viremia in humans , the low-level laboratory infrastructure in most endemic areas and cross-reactions when using serological methods which lack specificity [6]–[8] . Alternatively , molecular diagnostic methods represent essential tools for early diagnostics as they are able to detect infections during the viremic phase . Early detection of cases is crucial to provide efficient patient management , rapid outbreak response and emergency vaccination measures . For this reason , considerable efforts are made to develop accessible direct detection methods based on molecular detection which allow a rapid and highly sensitive detection of YFV . Several molecular methods for YFV detection based on polymerase chain reaction ( PCR ) , such as real-time RT-PCR , have been established , but these methods require the use of complex instruments and well-equipped laboratories [9]–[13] . However , in the case of direct detection methods for YFV , it is essential to be able to provide a portable , simple and robust method suitable for low-resource settings and field diagnosis , especially for outbreak response . For this reason , new molecular methods based on isothermal amplification have been developed for YFV detection , such as real-time reverse-transcription loop-mediated isothermal amplification ( RT-LAMP ) [14] and helicase-dependent amplification assays ( HDA ) [15] . In this study , we describe the establishment of a reverse-transcriptase recombinase polymerase amplification ( RPA ) assay for YFV detection . During RPA reaction , YFV RNA is first transcripted to DNA by a reverse-transcriptase . Secondarily , a phage derivated recombinase forms a nucleoprotein complex with the oligonucleotide primers which is able to scan for homologous sequences in the DNA template . RPA reaction can be performed between 25 and 42°C since denaturation of the DNA template is not required . If the target is present , the oligonucleotides are extended by strand displacing polymerases [16] . Real-time signal detection of the amplification can be performed within 15 minutes by using TwistAmp™ Exo probes ( TwistDx , Cambridge , UK ) and a ESEQuant Tube Scanner ( QIAGEN Lake Constance GmbH , Stockach , Germany ) , a small easy-to-use fluorescence detection system which can perform eight measurements simultaneously . In low-resource settings where no power supply is available , the Tube Scanner device can be powered by a car adaptor , a small rechargeable battery or a battery charged by solar panels [17] . The RPA assay can also be integrated into a semi-automated system , using a GeneSlice microfluidic cartridge ( HSG-IMIT , Freiburg , Germany ) installed in a “SONDE” player device . As an alternative to real-time measurement , RPA results may be visualized after amplification on lateral-flow stripes ( LFS ) by using a different probe , TwistAmp™ Nfo ( TwistDx , Cambridge , UK ) , during the RPA reaction . The reaction system can be stabilized in a dried formulation transportable without a cold chain .
Virus strains used were provided by the Robert Koch Institute in Berlin , the Bernhard-Nocht-Institute in Hamburg in Germany , and the Pasteur Institute of Dakar in Senegal . All virus strains were derived from cell culture , inactivated and stabilized . YFV strains are listed in Table 1 and other viral strains in Table 2 . Pools of mosquitoes , some of them infected with YFV , were provided by the Pasteur Institute of Dakar . The mosquito sampling protocol was extensively described by Diallo and colleagues [18] . Viral RNA was isolated from 140-µl aliquots of cell culture supernatants or 100-µl aliquots of mosquito pools , using the QIAamp Viral Mini Kit ( QIAGEN Lake Constance GmbH , Stockach , Germany ) according to the manufacturer's instructions . RNA was eluted in 100 µl of elution buffer and stored at −80°C until further use . In order to use an energy-free method in the field trial , RNA extraction was performed with the innuPREP MP Basic Kit A ( Jena Analytik , Jena , Germany ) with a magnetic bead separation rack combined with proteinase K treatment according to the manufacturer's instructions . The nucleic acids were eluted in 100 µl of nuclease-free distilled water , and 5 µl were subjected to PCR or RPA , respectively . RNA was extracted from 10-fold serial dilutions of YFV preparation and stored in aliquots at −80°C until use to assess the sensitivity of the extraction method . Human plasma samples spiked with low concentrations of YFV were used as a model for assay validation with clinical samples . All of the 79 YFV full-length sequences covering the 5′-UTR region available in the database ( NCBI ) were aligned using Geneious 5 . 0 software . According to Piepenburg and colleagues , primers of 30 nt to 35 nt in length are recommended for RPA [16] . One set of degenerate generic primers ( YFV RF/RR ) was designed according to the alignment for amplification of different YFV strains ( Table 1 ) . The primer sequences were identical for both lateral-flow strip RPA ( LFS RT-RPA ) and real-time RT-RPA primers , except for an additional biotinylation at the 5′ end of the LFS reverse primer . RPA exo probe for fluorogenic detection and RPA nfo probe for detection of dual-labeled amplicon were designed according to RPA guidelines from TwistDx ( Cambridge , United Kingdom ) and synthesized by TIB MOLBIOL ( Berlin , Germany ) . YFV-specific primer YFV FP/RP and probe YFV LNA2 were used to detect and quantify genomic RNA of YFV as described previously [9] . The assay was performed in a one-step format on the ABI 7500 instrument using the QuantiTect Virus Kit ( QIAGEN Lake Constance GmbH , Stockach , Germany ) . LFS-RPA assay was performed using the TwistAmp™ nfo RT kit from TwistDx ( Cambridge , United Kingdom ) according to the manufacturer's instructions . Briefly , 29 . 5 µl of rehydration solution were mixed with 7 . 2 µl of PCR water , 2 . 1 µl of each primer ( 10 µM ) and 0 . 6 µl of the target-specific RPA nfo probe ( 10 µM ) . Then 5 µl of RNA template was added to the 41 . 5 µl master mix . The template/master mix solution was added to the dry reagent pellet and mixed by pipetting up and down . Finally , the reaction was triggered by adding 3 . 5 µl of magnesium acetate ( Mg ( OAc ) 2 , 280 mM ) to the 46 . 5 µl reaction mix . The reaction mix was placed into the heating block at 39°C for 20 min , with brief mixing and centrifugation after 3–4 min of incubation . After amplification at 39°C for 20 min , 2 µl of amplification product was diluted in 100 µl of PBST buffer , and 10 µl of diluted amplicon was dropped on the sample pad of a HybriDetect lateral flow stripe ( LFS ) ( Milenia Biotec , Giessen , Germany ) . Strips were then placed into tubes containing 100 µl of PBST buffer . The final result was read visually after 5 min of incubation . A test was considered positive when the detection line as well as the control line was visible . A test was considered negative when only the control line was visible . Real-time RT-RPA assay was performed using the TwistAmp™ exo RT kit according to the manufacturer's instructions . The TwistAmp™ exo RT kit contains an additional RT-enzyme enabling the DNA amplification of RNA targets . Briefly , 37 . 7 µl of rehydration solution were mixed with 2 . 1 µl of each primer ( 10 µM ) and 0 . 6 µl of the target-specific RPA exo probe ( 10 µM ) . Then 5 µl of RNA template was added to the 42 . 5 µl master mix . The template/master mix solution was added to the dry reagent pellet and mixed by pipetting up and down . Finally , the reaction was triggered by adding 3 . 5 µl of Mg ( OAc ) 2 ( 280 mM ) to the 47 . 5 µl reaction mix . The reaction tubes were mixed , centrifuged and then placed into the ESE Quant Tube Scanner for real-time monitoring of fluorescence . Reaction was performed at 39°C for 20 min , with brief mixing and centrifugation of reaction tubes after 3–4 min of incubation . This reaction temperature was determined optimal in terms of sensitivity . For data analysis , the Tube Scanner requires to be connected to a computer installed with the ESEQuant Tube Scanner software Version 1 . 0 . Threshold values were determined by slope validation , i . e . slope ( mV/min ) values were compared in order to distinguish positive results from negative results . Further development and standardization of the method would allow using the device on its own with a direct display of positive or negative results for each sample . To test whether our assay is able to detect a wide variety of YFV strains , we utilized a panel of 20 different YFV strains described in Table 1 . The analytical specificity was tested with a panel of 13 arboviruses and hemorrhagic fever viruses of which 9 are flaviviruses genetically related to YFV ( Table 2 ) . RT-RPA analytical sensitivity was evaluated by testing RNA extracts from 10-fold serial dilutions of YFV preparations comparatively to real-time RT-PCR used as the reference method . RNA was extracted from the YFV Asibi strain and RNA concentrations ranged from 2×105 to 8 genome equivalent copies per reaction ( GC/rxn ) . Repeatability of the method was assessed by testing each dilution 10 times with real-time RT-RPA and 5 times with LFS-RT-RPA . Centrifugal microfluidic cartridges [19] , termed GeneSlice ( HSG-IMIT , Lab on a Chip Design- and Foundry Service , Freiburg , Germany ) , were used to demonstrate process automation of real-time RT-RPA in a small and portable processing device , the “SONDE” player , that may be used in the field with minimum manual interaction ( Fig . 1B ) . The GeneSlice contains a microfluidic channel network that allows to aliquot an initial reaction mixture into 8 subvolumes by applying centrifugal forces . Each subvolume is then transferred into a separated amplification chamber ( Fig . 1A ) [20] , [21] . The reaction mixture was composed of 73 µl rehydration solution , 4 . 2 µl forward/reverse primer ( 10 µM each ) , 1 . 2 µl probe ( 10 µM ) , 7 µl of Mg ( OAc ) 2 ( 280 mM ) and 10 µl of the DNA/RNA template . Three lyophilized pellets from the TwistAmp™ exo RT kit were resuspended in the 90 µl-reaction mixture . The reaction mixture is aliquoted into eight 10 µl volumes and transferred into amplification chamber by centrifuge force . Excess mixture is collected into a waste chamber . The “SONDE” player heats the samples at 41°C and RPA reaction is initiated in each amplification chamber . The fluorescence signal produced by the amplification is monitored for 20 minutes by the integrated detection unit . Amplification results were analyzed using IsoAmp Software ( QIAGEN Lake Constance GmbH , Stockach , Germany ) . Real-time RT-RPA assay combined with a magnetic bead-based extraction method was tested under field conditions in Senegal . Inactivated YFV virus and YFV RNA controls were prepared in dry-stabilized format using DNAstable Blood and RNAstable reagents ( Biomatrica , San Diego , USA ) , respectively . These controls were stored at ambient temperature until further use in the field . For the field trial of real-time RT-RPA , all reagents and instruments required were packed and transported by car from Dakar ( 14°43′12″N 17°28′48″W ) to Mbour ( 14°25′19″N 16°57′51″W ) at ambient temperature . At the Mbour city health center , the RPA setup was deployed and RNA was extracted from dry-stabilized virus controls using innuPrep MP basic kit . Subsequently , the extracted RNAs were tested with real-time RT-RPA for YFV . In order to reproduce field conditions where no power supply is available , the Tube Scanner was powered by a battery charged by solar panels .
By analyzing the alignment of all available full genome sequences of YFV , the conserved 5′-non-coding region ( NCR ) of the YFV genome was chosen for primer and probe design ( Table 3 ) . The primer set YFV RF/RR efficiently amplified YFV RNA in LFS RT-RPA and real-time RT-RPA assays . The analytical specificity testing revealed that all the 20 different YFV strains were detected by both LFS and real-time RT-RPA assays . The testing results of the panel of 13 viruses other than YFV showed no cross-reactions , as all results were negative for both assays ( Table 2 ) . However , concerns with specificity were encountered with the LFS RT-RPA assay , as a faint band was observed in the negative controls when running time exceeded 5 minutes , thus potentially generating false-positive results . The analytical sensitivity of RT-RPA assays was evaluated by testing the RNA extracts from 10-fold serial dilutions of YFV preparations and by comparing real-time RT-RPA and real-time RT-PCR test results . The real-time RT-PCR showed linear results for the quantification of RNA standards over a range of 10 to 106 genome copies . Real-time RT-PCR detected as low as 8 GC/rxn while real-time and LFS RT-RPA assays could detect as low as 44 GC/rxn in YFV RNA extracts and 21 GC/rxn for the testing of YFV-spiked human plasma samples ( Figure 2 ) . The amplification curves of the YFV RNA extracts from 10-fold serial dilutions are shown in Figure 3-A for real-time RT-RPA results and Figure 3-B for real-time RT-PCR results . Thirty-four samples of monospecific pools of wild-caught mosquitoes collected from Kedougou , southern Senegal were included in this study . The RNA extracts from these samples were tested in parallel with real-time RT-PCR and RT-RPA . Fourteen mosquito samples out of 34 ( 41 . 2% ) resulted negative in real-time RT-PCR and 20 were positive ( 58 . 8% ) with Ct values ranging from 24 . 65 to 35 . 51 ( data not shown ) . Of the 20 samples detected positive in real-time RT-PCR , 16 were tested positive by real-time RT-RPA assay , providing a sensitivity of 80% ( 95% CI: 56 . 3% to 94 . 1% ) . Of the 14 samples tested negative in real-time RT-PCR , all were also tested negative by real-time RT-RPA assay , providing a specificity of 100% ( 95% CI: 76 . 7% to 100% ) . The overall agreement between the two assays was 88 . 4% ( 30/34 ) ( Table 4 ) . Twenty-seven RNA samples of mosquito pools were included in this part of the study . Thirteen mosquito samples out of 27 ( 48 . 1% ) had negative results in real-time RT-PCR and 14 were positive ( 51 . 9% ) , with Ct values ranging from 27 to 35 . 5 ( data not shown ) . Of the 14 samples tested positive with real-time RT-PCR , 10 were tested positive by real-time RT-RPA , providing a sensitivity of 71 . 4% ( 95%CI: 41 . 9% to 91 . 4% ) . All of the 13 samples that tested negative in real-time RT-PCR were also tested negative by real-time RT-RPA assay , providing a specificity of 100% ( 95% CI: 75% to 100% ) . The overall agreement between the two assays was 85 . 2% ( 23/27 ) ( Table 4 ) . The virus and RNA controls were stabilized with DNAstable Blood and RNAstable reagents and tested in the laboratory using real-time RT-PCR and real-time RT-RPA . These results were compared to the testing results of the same amount of control samples without stabilizer , stored at −20°C . Results were comparable and proved the stabilization process to be effective . The average cycle threshold ( Ct ) and time threshold ( Tt ) values for all samples were 31 . 08 ( SD = 0 . 74 ) and 5 . 5 ( SD = 0 . 22 ) , respectively . When stabilized controls and non-stabilized controls at −20°C were tested on real-time RPA during the field trial , the mean of Tt values of these samples was 5 . 3 . These results are comparable to the values detected previously in the laboratory , indicating good reproducibility of the complete experimental workflow in the field .
In this study , we describe the development of a RT-RPA assay for YFV detection which can be performed without complex equipment in a basic laboratory setting , a rural health care center or an outbreak field investigation . We designed a set of primers and probe and developed a real-time methodology which enables to detect down to 21 GC/rxn . This detection limit is slightly higher than the 8 GC/rxn detected by real-time PCR [9] . Nonetheless , this level of sensitivity is sufficient to detect wild-type YFV in natural infections or serious adverse events ( SAEs ) following YFV immunization which produce viremia levels up to 108 PFU/ml [22]–[24] . Test results for spiked human plasma samples indicated that serum does not affect significantly the assay sensitivity . Therefore , we can assume that the test can be applied for laboratory case confirmation of suspected YFV cases . However , there is further need to validate intensively the assay using YF clinical samples from various endemic countries and from patients at different stages of the disease . The LFS-RPA assay experienced specificity problems , as a faint nonspecific band appeared in the negative controls when running time exceeded 5 minutes . Such faint bands have not been observed neither for the very low dilutions of YFV RNA nor during testing of other viruses . Therefore , these false-positive results are not due to contamination but rather to the clotting of proteins or primers which could not bind to any template . Unequivocal interpretation of LFS may be provided by an ESEQuant Lateral Flow Reader ( QIAGEN Lake Constance GmbH , Stockach , Germany ) . However , at this point , we recommend particular caution during LFS operation and interpretation and further optimization of the assay before use under field conditions . Real-time RT-RPA results demonstrated an optimal specificity . Testing results of the mosquito pools demonstrated an analytical specificity of 100% on both the Tube Scanner and the microfluidic GeneSlice cartridge . Real-time RT-RPA on the microfluidic GeneSlice cartridge showed a statistically similar sensitivity ( 71 . 4% and 80% respectively ) as the confidence intervals of both sensitivity values overlap . The lower sensitivity value of the GeneSlice method might be due to the complexity of the microfluidic unit operations which comprises release of liquid reagents , reconstitution of lyophilized reagents , aliquoting the sample into eight independent reaction cavities and mixing of reagents with the RNA samples . Nevertheless , the performance of the GeneSlice is satisfying , and no cross-contamination between wells was observed . Moreover , this semi-automated and downscaled system leads to a significant reduction in costs , manual work and waste , making it an attractive method for point-of-care applications such as the screening for hemorrhagic fevers in Africa . However , the real-time RT-RPA on the Tube Scanner was used for further evaluation including in field conditions because of its higher sensitivity . During the field study , real-time RT-RPA has demonstrated similar performance to that during previous testing under laboratory conditions . Based on our results , the assay proves to have great potential as a point-of-care molecular diagnostic method for various reasons: all reagents are lyophilized with the main RPA reagents provided in a single dried pellet , which simplifies assay preparation and allows long-term storage at room temperature; amplification is performed at constant temperature; ESEQuant Tube Scanner device is significantly lighter , smaller and cheaper than all other available mobile PCR cyclers or turbidimeter devices for LAMP assays; the assay has a low energy consumption; reaction times are short and the system is simple , robust and portable . The cost is approximately 4 euros per test for real-time RPA and 5 euros per test for real-time RT-PCR in lyophilized form . At this stage , costs per sample for both techniques are comparable . However RT-RPA is a newly developed technique and prices are likely to decrease in the future while availability and throughput will increase . Furthermore , the detection device for real-time RPA is approximately 10 times cheaper than a real-time PCR machine . An external quality assessment study on diagnostic methods for YFV infections launched in 2011 revealed that the main weakness observed for molecular methods was the inability of some assays to detect the YFV genome of wild-type strains , whereas the vaccine strain was always detected [25] . This specificity problem has not been observed for the YFV RT-RPA assay , as all YFV strains were detected . Furthermore , our assay revealed no cross-reactions with other closely related viruses . Recently , another isothermal amplification method for YFV detection was developed based on reverse transcription loop-mediated isothermal amplification ( RT-LAMP ) technology [14] . In contrast to RPA , LAMP requires a larger set of six primers , a higher temperature ( 62°C ) and a longer run time . Sensitivity is not comparable , as results of RT-LAMP were expressed as PFU instead of GC detected , but RT-LAMP usually presents equal or lower sensitivity than RPA [26] , [27] . In fact LAMP uses nonspecific intercalating fluorophores for detection while RPA uses specific detection probes . In summary , we have developed a very rapid and sensitive isothermal RPA assay in real-time and lateral-flow stripe format for the detection of YFV . Both of these assays can be easily applied in low-resource settings as an alternative to traditional laboratory-based molecular diagnostic assays . However , the LFS format needs further optimization to exclude all risks of false-positive results . The real-time RT-RPA assay , using the transportable Tube Scanner device combined with the RNA extraction method based on magnetic beads , and the use of lyophilized reagents which can be stored at ambient temperature allowed us to apply our RPA assay under field conditions in Senegal with performance similar to that of cutting-edge laboratory settings .
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Despite the use of a safe and effective vaccine , yellow fever virus is still causing hundreds of thousands of infections and tens of thousands of deaths every year . The disease is widespread in South America and Africa where several outbreaks have occurred in the past years . As the disease is difficult to distinguish from other illnesses during its early stage , it is necessary to develop reliable , rapid and simple diagnostic methods to confirm YF cases to be able to respond effectively to outbreaks through vaccination and vector control . In this study , we describe the development a diagnostic method for YFV , using an isothermal technology called recombinase polymerase amplification which allows detection of the virus within 20 minutes , using a portable and easy-to-use device . The YFV RPA assay proved to be a specific and sensitive detection method during testing in the laboratory and under field conditions in Senegal .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"applied",
"microbiology",
"virology",
"emerging",
"viral",
"diseases",
"biology",
"microbiology",
"viral",
"disease",
"diagnosis"
] |
2014
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Rapid Molecular Assays for the Detection of Yellow Fever Virus in Low-Resource Settings
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The bile fluid contains various lipids that are secreted at the canalicular membrane of hepatocytes . As the secretion mechanism is still a matter of debate and a direct experimental observation of the secretion process is not possible so far , we used a mathematical model to simulate the extraction of the major bile lipids cholesterol , phosphatidylcholine and sphingomyelin from the outer leaflet of the canalicular membrane . Lipid diffusion was modeled as random movement on a triangular lattice governed by next-neighbor interaction energies . Phase separation in liquid-ordered and liquid-disordered domains was modeled by assigning two alternative ordering states to each lipid species and minimization of next-neighbor ordering energies . Parameterization of the model was performed such that experimentally determined diffusion rates and phases in ternary lipid mixtures of model membranes were correctly recapitulated . The model describes the spontaneous formation of nanodomains in the external leaflet of the canalicular membrane in a time window between 0 . 1 ms to 10 ms at varying lipid proportions . The extraction of lipid patches from the bile salt soluble nanodomain into the bile reproduced observed biliary phospholipid compositions for a physiologi-cal membrane composition . Comparing the outcome of model simulations with available experi-mental observations clearly favors the extraction of tiny membrane patches composed of about 100–400 lipids as the likely mechanism of biliary lipid secretion .
One central function of the liver is the production of the bile which is indispensable for the efficient digestion of dietary lipids , elimination of hydrophobic xenobiotics and removal of cholesterol from the body . The bile is formed in the biliary canaliculi , i . e . the extracellular space that faces the canalicular membrane of hepatocytes . About 80% of the bile content is bile salts ( BS ) , while the other components are phospholipids ( ≈ 15% ) and cholesterol ( ≈ 5% ) . The secretion rate and composition of the bile are important factors in metabolic regulation , malfunctioning leading to hepatocyte damage , hypercholesterolemia , advanced levels of high-density lipoproteins or formation of atherosclerotic plaques [1] . Different models have been proposed to account for the canalicular secretion of hepatocyte-born lipids into the bile [2–6] . One possible mechanism of lipid secretion consists in the BS driven extraction of single lipids into the lumen of the canaliculus followed by assembly of these lipids and BS in mixed-micelles ( ‘single-lipid extraction’ ) . An alternative model developed on the basis of ultrastructural investigations suggests that lipid vesicles highly enriched in phosphatidylcholine are formed via BS facilitated exo-vesiculation of microdomains present in the exoplasmic hemi-leaflet of the canalicular membrane [7 , 8] . These BS extractable microdomains appear to coexist with sphingolipid-enriched microdomains which cannot be solubilized by BS and thus represent potential localized target areas for the clustering of proteins involved in bile formation as , for example , ABC transporters , aquaporins and P-type ATPases [9 , 10] . One may hypothesize a mechanism of lipid secretion where both BS extractable and BS non-extractable microdomains of different lipid composition coexist in the exoplasmic leaflet of the canalicular membrane . The first ones represent membrane patches that can be easily intercalated by BS , protruded into the canalicular space and finally be released , the latter ones containing most of the proteins required to enrich the outer leaflet with specific lipids like phosphatidylcholine and conferring stability of the membrane against detergents . In both models the solubilization of membrane lipids is mediated by BS that are actively pumped into the canalicular lumen . They rely on the coexistence of BS soluble and BS insoluble membrane areas as the canalicular membrane has to meet two opposing conditions: ( i ) Maintenance of integrity in the presence of high concentrations of BS which are powerful detergents and ( ii ) at the same time allowing the secretion of membrane lipids . The formation of microdomains goes along with the segregation into liquid ordered and liquid disordered phases . The formation of different lipid phases is largely determined by the saturation profile of the fatty acid tails of the phospholipids and of sphingomyelin [11] . The tight interaction between cholesterol and sphingomyelin side chains usually representing long and saturated fatty acids allows for the formation of liquid ordered phases [12 , 13] , whereas the high content of unsaturated fatty acids of phospholipids usually leads to a lower interaction between these membrane lipids and thus entails a liquid-disordered fraction of the membrane . Phosphatidylcholine species found in the rat liver canalicular membrane and bile have a fairly hydrophilic fatty acid composition with palmitate ( 16:0 ) in sn1-position and an unsaturated fatty acid ( mostly 18:1 , 18:2 , 20:4 ) in the sn2-position [14] . Most findings on microdomains have been obtained in in vitro experiments with lipid mixtures [15 , 16] and giant unilamellar vesicles [17] . Depending on the number , type and relative abundance of lipids used to constitute these artificial membrane-like systems , one may observe tiny unstable nanodomains ( ≈ 10 nm ) [18–20] or much larger ( > 200 nm ) and stable microdomains with life-times of several seconds containing up to 100 , 000 lipids . The problem is that microdomains of this size and life-time have never been observed in the membranes of living cells . Instead , the existence of much smaller ( ≈ 10 nm ) and very short-lived ( < 0 . 1 ms ) microdomains has been inferred from donor-quenching FRET analysis [21 , 22] , atomic-force microscopy [23] or deuterium-based nuclear magnetic resonance [24] . Possible reasons for this remarkable instability of microdomains in membranes of living cells are thermodynamic variations and mechanical perturbations exerted by cell-cell and cell-matrix interactions . In order to distinguish these tiny and very unstable microdomains from their counterparts present in model membranes we will refer to them later on as nanodomains [11] . As the processes of nanodomain formation and lipid transfer from the external leaflet of the canalicular membrane into the lumen of the bile canaliculus cannot be directly monitored by experimental means we have developed a mathematical model to simulate the formation of nanodomains in the canalicular membrane and the extraction of the major bile lipids cholesterol ( CH ) , phosphatidylcholine ( PC ) and sphingomyelin ( SM ) from BS soluble nanodomains . The model enables dynamic simulations of the transit from an initially random to a highly structured lipid distribution on a time scale of several milliseconds . With the model we address the problems of membrane self-organization , biliary phospholipid secretion and composition as well as membrane integrity .
We simulated the lipid dynamics by using a Potts model approach [25] . The membrane is represented by a triangular lattice with periodic boundary conditions . Each lattice site is occupied by exactly one lipid . The model comprises the membrane lipids CH , PC and SM which represent the prevailing membrane lipids in the canalicular membrane of hepatocytes . Note that the model variable PC actually represents also other phospholipids of the exoplasmic leaflet ( e . g . ≈ 11% phosphatidylethanolamine ) as well as different fatty acid tail compositions . This is a necessary simplification of the model as experimental information on the impact of glycerophospholipids other than PC on domain formation and lipid diffusion is not available . We introduced next-neighbor interaction energies w for each pair of membrane lipids . Furthermore , similar as in [26] we assumed that each lipid may be either in a low or high ordered internal state . In the low-ordered state the bulky conformation of the fatty acid chains allows high flexibility and thus rapid movement while in the high-ordered state the fatty acid chains are arranged in a way that the hydrophobic interactions with adjacent lipids are strong and thus restricting lipid mobility . We model the property of lipids to cooperatively synchronize their ordering states by assigning a coupling strength j ( X i σ , X k σ ) between the ordering states σ of the lipid species X resident in neighboring lattice sites i and k . The ordering states ho and lo are represented by σ = −1 and σ = +1 respectively . The coupling j ( X i σ , X k σ ) of lipid pairs contributes to the total ordering energy of the membrane with a positive sign if the two neighboring lipids possess identical ordering states and with negative sign if the ordering states are different: J = − ∑ i = 1 N ∑ k ∈ n ( i ) j ( X i σ , X k σ ) σ i σ k . The first sum runs over all lattice sites N and the second over the 6 neighbors of lattice site i . Self-organization of lipid domains comprising lipids that are predominantly present in the lo or ho state is achieved by minimizing this total ordering energy . Our approach to enforce a phase separation of lipids is similar to the well-known Ising model of ferromagnetism in statistical mechanics describing the formation of phases with different atomic spin states ( –1 , +1 ) across a 2-dimensional lattice [27] . Furthermore , we introduce next-neighbor interaction energies for each pair of membrane lipids and describe the dynamics of membrane lipids as a process driven by minimization of the total interaction energy of the lattice . As the lipids may occur in two different ordering states , we assign different interaction energies , who ( Xi , Xk ) and wlo ( Xi , Xk ) , to adjacent lipids of species X at lattice site i and k depending on whether these two lipids are both in the ho state or lo state , respectively . The total interaction energy of the membrane is W = ∑ i = 1 N ∑ k ∈ n ( i ) w σ ( X i , X k ) . In cases where the ordering states σ at sites i and k are different we assign to this lipid pair the mean of the two interaction energies . Movement of lipids on the lattice is restricted to their pair-wise interchange of next neighbors . The dynamics of membrane lipids and the distribution of their mobility states are governed by the minimization of the total energy E which is a linear combination of the ordering energy J and the interaction energy W: E = W + γ ⋅ J = ∑ i = 1 N ∑ k ∈ n ( i ) ( w σ ( X i , X k ) + γ ⋅ j ( X i σ , X k σ ) σ i σ k ) . The scaling factor γ relates the ordering energy J to the interaction energy W . The values of wσ ( Xi , Xk ) and j ( X i σ , X k σ ) represent Gibb’s free energies which arise from a multitude of electrostatic , Van der Waals and hydrophobic interactions between head groups and fatty acid tails of neighboring membrane lipids [28] . In our thermodynamic-based approach the behavior of the lattice in the equilibrium state is fully determined by the changes of the free energy associated with either switching of neighbored lipids or changing the ordering state of lipids . For the stochastic simulations of lipid movement we applied the Gillespie algorithm [29] . The core of this algorithm consists in assigning to each possible elementary process pij of lipid switch between i and j , a rate r ( i , j ) that depends upon the local interaction energies at positions i and j where the process pij is executed: r ( i , j ) = exp ( β ( wi +wj ) ) . Here , wi = Σk∈n ( i ) wσ ( Xi , Xk ) is the interaction energy of a lipid of species Xi at site i with all its neighbors with species Xk and β = 1/kBT the inverse temperature . The probability P ( Δt ) that during the time span Δt no elementary process occurs is related to the elementary rates by P ( Δt ) = exp ( –rtotΔt ) , where rtot = ΣPij r ( i , j ) is the total rate , defined as the sum of the elementary rates . This relation is used to randomly generate elementary time steps , Δt = -ln η/rtot , where η are equally distributed random numbers between 0 and 1 . After having randomly chosen the time step for the next elementary process to occur , the elementary process to be executed has to be specified . This is done by randomly choosing an elementary process , i . e . lipid switch , with its corresponding probability . So far we neglected the process of changes in the ordering state . From the molecular-dynamics point of view , a change in the conformation of the fatty acid tail should occur much more frequently compared with a switch of neighbored lipids . As a consequence , the elementary process “change the ordering state of a selected lipid” occurs much more frequently than the elementary process “switch adjacent lipids” . Hence , it is reasonable to assume that a large number of changes in the ordering states of lipids will occur between two subsequent lipid switches so that at any time point the conformational energy J becomes minimal . The rate with which a membrane lipid flips between two alternative ordering states is not known . Considering that such a flip requires only a change in the conformation of the fatty acid tails it is reasonable to assume that flips of the ordering state occur with much higher rates than changes in the spatial position of the membrane lipid . We thus refrained from executing explicitly the elementary process “change the ordering state of a selected lipid” . Instead , we make the steady-state ( or equivalently: partial fast-equilibrium ) assumption that the ordering energy is minimal and thus the ordering states of the lipids are in equilibrium at any time point . This also alleviates us from knowing the exact value of the scaling factor γ , as it now does not occur in the algorithm itself . Adopting the basic concept of multi-scale stochastic simulation of systems comprising a fast-equilibrium subsystem [30 , 31] we split the simulation into two alternating steps: ( 1 ) A dynamic simulation governed by the interaction energy W and carried out over a critical time which is determined by the condition that each lipid has to change its position on the lattice NW times on average . During this dynamic simulation , the ordering states of the lattice sites are not changed , i . e . the ordering state is a fixed property of the lattice site and not of the lipid just occupying the site . The dynamic simulation step is followed by ( 2 ) the minimization of the total ordering energy J . This minimization step is carried out by the Metropolis algorithm [32] whereby the ordering states of all lattice sites are NJ times updated . A change of the ordering state occurs with probability P ( lo ↔ ho ) = { 1 exp ( − β Δ J ) if Δ J ≤ 0 if Δ J > 0 depending on the difference ΔJ between new and old ordering energy . The updated ordering states of the lipids are assigned to the harboring lattice sites and the simulation is continued with step ( 1 ) as depicted in Fig . 1A . The whole simulation is either stopped at a fixed time point ( this termination of the simulation was applied in the simulations of bile formation ) or if the statistical properties of the lattice defined through frequency of lipid-lipid contacts , the relative share of lipids in lo states and ho states and the numerical value of the diffusion coefficient do not change over a sufficiently long time interval ( this termination of the simulation was applied in the parameterization of the model based on experimental data with ternary lipid mixtures ) . To ensure independence of the simulation results from the combination of the two linked optimization algorithms ( see flowchart in Fig . 1A ) the number of spin updates NJ has to be high enough to minimize J . Likewise the number of lipid switches NW should be sufficiently low to ensure that the spin updates occur frequently enough . On the other hand it is desirable to keep NJ low and NW high to minimize the computational effort . To find optimal values satisfying both requirements the control parameters NJ and NW were varied and the dependence of the statistical properties of the model membranes was monitored . Fig . 1B shows an example demonstrating how the statistical properties of the simulated model configurations are influenced by the control parameters NJ and NW . According to these results , we put NJ = 100 and NW = 10 in the stochastic simulations . The next step was to determine the interaction energies and the spin energies used in the model . With the three membrane lipids CH , PC and SM the symmetric matrices wlo and who of the interaction energies are 3×3 matrices comprising six independent unknown parameters wσ ( CH , CH ) , wσ ( CH , PC ) , wσ ( CH , SM ) , wσ ( PC , PC ) , wσ ( PC , SM ) , and wσ ( SM , SM ) , with σ = lo , ho state . The matrix j of the ordering energies is a 6×6 matrix comprising 36 elements . The entries in the ordering matrix j describe the ordering energy of a given lipid ( CH in the first column , PC in the second column , SM in the third column ) with a neighboring lipid being in a given ordering state σ . The ordering state of the lipid itself is not of importance since in the used metropolis algorithm only energy differences are of importance , i . e . the calculation of ΔJ leads to the same result if one puts j ( X i lo , X k lo ) = j ( X i lo , X k ho ) and j ( X i ho , X k lo ) = j ( X i ho , X k ho ) . Therefore the dimension of the matrix is reduced to 3×6 . The difference in the ordering energies for a given lipid with a neighboring lipid in either phase determines the tendency of the lipid to adopt either ordering state , with the lower value representing the favored and the higher value representing the disfavored ordering state . These pairs of values are block by block symmetric in the matrix which further reduced the free parameters from 18 to 6 . Thus , in total our model comprises 2·6+6 = 18 parameters with unknown numerical values . We calibrated the interaction between the different lipids in different ordering states such that the diffusion coefficients would match those from experiment for the reported phases . Our model allows to track the stochastic movement of individual lipids along with their ordering state and thus to determine mean squared displacements ( MSDs ) for the different phases . MSDs were calculated by first letting the simulation run until the resulting membrane configuration had reached an equilibrium state . At this point , we tagged the position of all N phospholipids i0 and let the simulation continue for a certain number of steps z . Next we calculated the individual displacement after the z steps for each lipid: Δ x ( z , X i , σ i ) = | i z − i 0 | For the calculation of the displacements of the different lipid species X in the different phases only those random walks were taken into account for which the tracked lipid had not passed a phase border , i . e . had not changed its ordering state σi . Given the displacements Δx and choosing an arbitrary timescale t corresponding to the z steps the simulated diffusion coefficient D m , σ sim for the phase σ of the m-th model membrane can be derived from the MSDs with the corresponding ordering state in the respective lipid composition: 〈 Δ x ( t ) 2 〉 = 4 D m , σ sim t . The MSDs are only determined up to an overall scaling factor α: α = ∑ m D m , σ exp D m , σ sim ∑ m ( D m , σ exp ) 2 . Here the index m designates the different lipid compositions of the GUVs , D m , σ exp denotes the measured and D m , σ sim the simulated diffusion coefficient for lipid composition m . The numerical values of the unknown elements of the matrices wlo and who were estimated by minimizing the difference ε between model-based lateral lipid diffusion rates and experimental values determined in giant unilamellar vesicles ( GUVs ) containing CH , PC and SM in 25 different proportions [33]: ε = ∑ m = 1 25 ( D m , σ exp − α D m , σ sim ) 2 → minimum . calculated for a lattice having the same lipid composition m as the GUVs . Simulated diffusion coefficients that differ from the experimental ones by a global constant factor can be transformed by rescaling of α or alternatively by a rescaling of the time t . Therefor α relates the time scale used in the model simulations to the time scale of the in vitro experiments . The same value of the scaling factor α was used for fitting the unknown elements of the two matrices wlo and who . To solve this minimization problem , the numerical values of the 12 unknown parameters were varied on a discrete hypercube under the additional constraint of reproducing known interactions between the different lipid species . The condition for mixing of lipid species X and Y can be formulated as 2wσ ( X , Y ) − wσ ( X , X ) − wσ ( Y , Y ) < 0 while the condition for de-mixing is 2wσ ( X , Y ) − wσ ( X , X ) − wσ ( Y , Y ) > 0 [34] . The only constraints applied were that the lipid species CH and SM would mix in the ho state [35] . We determined the points of this hypercube that fulfilled the condition and where ε attained its minimal value for the ho or the lo state respectively . Around these points we again varied the unknown parameters on a finer hypercube and determined ε . The procedure was repeated with successively decreasing sizes of hypercubes until no further significant reduction of ε was possible . This corresponds to a discretized version of a downhill simplex method . The calibration yielded the following numerical values for the lipid—lipid interactions w ho = ( w ho ( CH , CH ) w ho ( CH , PC ) w ho ( CH , SM ) w ho ( PC , PC ) w ho ( PC , SM ) w ho ( SM , SM ) ) = ( − 0 . 70 + 0 . 55 − 1 . 70 − 0 . 60 + 0 . 45 − 0 . 80 ) in the high ordered state and w lo = ( w lo ( CH , CH ) w lo ( CH , PC ) w lo ( CH , SM ) w lo ( PC , PC ) w lo ( PC , SM ) w lo ( SM , SM ) ) = ( − 0 . 55 − 0 . 23 + 0 . 43 − 0 . 22 − 0 . 23 − 0 . 55 ) in the low ordered state . For the interpretation of the numerical values of the interaction matrices we apply them to the mixing and de-mixing properties of the previous section and compare the results to known membrane properties . In the ho state the interaction matrix features a strong tendency for CH and SM to mix and a strong tendency for PC to de-mix from CH and from SM . This is in agreement with works from Silvius [35] , van Duyl [36] and Frazier [37] . In the lo state PC has only a weak tendency to de-mix from CH and from SM , which is in agreement with work from Silvius [35] and Tsamaloukas [38] . Contrary to the ho state CH and SM have a tendency to de-mix in the lo state . For this pairing no reliable data could be found since the two species occur in the ho state rather than in the lo state . The unknown parameters of the ordering matrix j were chosen such that the occurrence of monophasic and biphasic lipid distributions matched those observed in the 25 different variants of GUVs . To this end we defined lipid distributions with more than 90% of all lipids resident in the ho state as monophasic liquid-ordered ( Lo ) , with more than 90% of all lipids resident in the lo state as monophasic liquid-disordered ( Ld ) and with more than 10% of all lipids resident in both ordering states as biphasic . For the minimization of J the lattice was initialized with all lipids in lo state . A searching of the parameter space yielded parameter values j = ( j ( CH lo , CH ) j ( CH lo , PC ) j ( CH lo , SM ) j ( CH ho , CH ) j ( CH ho , PC ) j ( CH ho , SM ) j ( PC lo , CH ) j ( PC lo , PC ) j ( PC lo , SM ) j ( PC ho , CH ) j ( PC ho , PC ) j ( PC ho , SM ) j ( SM lo , CH ) j ( SM lo , PC ) j ( SM lo , SM ) j ( SM ho , CH ) j ( SM ho , PC ) j ( SM ho , SM ) ) = ( 0 . 50 0 . 90 0 . 50 1 . 00 0 . 50 1 . 90 0 . 90 0 . 90 0 . 90 0 . 50 0 . 50 0 . 50 0 . 50 0 . 90 0 . 50 1 . 90 0 . 50 0 . 55 ) that allowed to match 21 phases of the 25 model membranes . The values thus obtained are by no means unique but this is not to be expected since the data described by them are only semi-quantative and the relative size of the ordering pairs for a given lipid to adopt either state is more important than the precise values . With these values the calculated diffusion coefficients and the occurrence of monophasic and biphasic lipid distributions of our model simulations were in agreement with experimental data obtained with GUVs [33] ( see Fig . 2 ) . The calibration of the model with measured diffusion coefficients allows the definition of an absolute time scale and thus offers the possibility to use the model for real-time dynamic simulations of domain formation . We used the parameterized model to compute lipid distributions for the whole possible range of lipid compositions ( Fig . 2B ) . We used the calibrated model to simulate the self-organization of nanodomains and the release of lipids from the outer leaflet of the canalicular hepatocyte membrane into the bile canaliculus . We presupposed a situation where the amount and composition of lipids in the outer leaflet is on the average kept constant ( quasi steady state ) , i . e . the transport rate of lipids to the canalicular membrane equals the net transport rate from the inner to the outer leaflet and the release rate into the canalicular lumen . As the life-time of nanodomain structures , i . e . the simulation time during which an initially random distribution of lipids self-organizes into a domain structure that is representative for the outer leaflet of the canalicular membrane , we chose τ = 0 . 1 , 1 and 10 ms to cover a range around the estimated nanodomain life-time of ≈ 1 ms [39] . We tested two alternative mechanisms of lipid secretion: extraction of single lipids or extraction of lipid patches . An extractable lipid patch is defined as a hexagonal piece of membrane that is fully embedded in a Ld nanodomain . With this definition , extraction of single lipids is identical with extraction of patches with size of 1 lipid . We defined the extractable membrane fraction ( EMF ) as the fraction of the membrane that can be covered by extractable patches . The flow of lipids into the bile is determined by the detachment rate of patches . This rate depends on the concentration and chemical properties of the BS species present in the canalicular lumen and the size and number of patches present in the outer leaflet . Hence , at fixed concentration of BS , the lipid secretion rate ( LSR ) is up to a constant unknown factor proportional to the number of the extractable patches npatch ( r ) with radius r multiplied by their lipid content nlipids ( r ) and divided by the time span τ required for the formation of nanodomains: LSR ( r ) = n patch ( r ) n lipids ( r ) / τ . The lipid composition of the bile is given by the average lipid composition of all extractable patches .
First , we carried out model simulations with a physiologically normal lipid composition of the canalicular membrane [8] with CH = 37 . 8% , PC = 46 . 5% and SM = 15 . 7% . The simulation was started with a fixed lipid composition but random distribution of lipids across the lattice with their ordering states calculated for the given random lipid distribution . Model simulations persistently resulted in a bi-phasic quasi-stationary lipid distribution comprising Ld nanodomains rich in PC and Lo nanodomains enriched in CH and SM . Typical lipid patterns obtained for three different life-times are depicted in Fig . 3 . With increasing life-time , the nanodomains tend to merge to form larger domains . Accordingly , the maximal size of patches that can be extracted from the Ld nanodomains increases as well . The predicted lipid composition of the patches and thus of the bile micelles was ≈ 13 . 5 CH , ≈ 85 . 5% PC and ≈ 1% SM in good agreement with reported experimental values of ≈ 15% CH , ≈ 85% PC and < 1% SM [40] . The lipid composition of patches was remarkably invariant against variations of the patch sizes and life-times ( see Table 1 ) . As seen in Fig . 3D–F , the calculated LSRs are non-monotone with respect to the patch size . This is due to the fact that the number of lipids that are simultaneously extracted from the leaflet increases with the patch size whereas the number of patches fitting into Ld nanodomains decreases with increasing patch size . The largest LSR was attained for patches containing 37 , 169 and 631 lipids for the three different simulation times τ = 0 . 1 , 1 and 10 ms . This has to be compared with the size of sandwich-like micelles which primarily derive from mixed dispersions of egg PC and the BS deoxycholate [41] and quasi-elastic light scattering studies of native bile from the dog [42] consistently comprising about 100–400 lipids . Since this is close to the calculated average patch size at τ = 1 ms and as a life-time of 1 ms is also in good agreement with several measurements on nanodomains we choose τ = 1 ms as the average life-time in further simulations . The lipid composition of the canalicular membrane has been shown to strongly influence the relative share of membrane lipids in the bile [43] . Thus , we performed simulations where the relative fraction of either CH or PC was varied ( see Fig . 4 ) . A decrease in the relative fraction of CH at otherwise constant PC:SM ratio increased the share of lipids in the Lo state and the average size of Ld nanodomains . As a consequence , the average size of membrane patches that can be solubilized from Ld nanodomains and the LSR increased with decreasing CH content of the external leaflet . At a low fraction of CH = 18% the model simulations predict a steep increase of the average patch size to about the 10-fold of the reference state . Such an increase of the BS-solubilizable membrane area should result in a BS-induced rupture of the membrane . Increasing the CH content of the exoplasmic leaflet promoted the transition from the Ld to the Lo phase and thus reduced the LSR . On the other hand , the CH content of the extractable membrane patches became successively larger . The net effect of these two opposing tendencies was an increase of the extractable fraction of CH up to a critical CH content which amounts to about 36% for extraction of patches with sizes of 100–400 lipids and to 56% for the mechanism of single-lipid extraction . In a further series of simulations we studied the impact of varying concentrations of PC on the lipid flow . With decreasing PC content at constant CH:SM ratio the simulations revealed a non-linear decline of the average size of extractable patches resulting in reduced LSRs of all lipid species . The composition of the patches remained almost constant although there was a slight shift towards a higher share of CH and a lower share of PC . Intriguingly , the lower limit of the membranous PC content below which the flow of PC into the bile practically ceased depended strongly on the size of membrane patches supposed to carry the lipid flow into the bile . For example , lipid extraction stopped at a lowered membranous PC content of 32% for patches with a size of 631 lipids , at 10% for 169 lipid patches while the extraction of single lipids did not stop until a PC content of 0% . Studies on mice with a homozygous knock-out of the PC transporter mdr2 found a complete abolishment of PC release into the bile [44] . Compared with our model simulation this finding again suggests lipid secretion to precede via extraction of patches rather than of single lipids . Increasing the PC content resulted in an increased EMF and strongly increased LSRs .
Importantly , at physiologically realistic lipid composition of the outer leaflet , our simulation consistently predicted the formation of two distinct types of nanodomains differing significantly in their lipid composition and phase behavior ( Fig . 3 ) . The Ld nanodomain was strongly enriched in PC while the Lo nanodomain was rich in CH and SM . These model-based findings are in good agreement with experiments clearly indicating a compartmentalization of lipids within the canalicular membrane [51] . Using either Triton X-100 or Lubrol WX as detergents , Slimane et al . [52] extracted two different membrane fractions . The Triton insoluble fraction was highly enriched in sphingolipids and CH [9] . The proteins mediating the trans-membrane lipid transport and the release of BS into the canalicular lumen ( BS export pump , multidrug resistance protein 2 , multidrug resistance associated protein 2 , Abcg5 ) were found to be predominantly located in the Triton X-100 soluble fraction [51] . Experiments with model membranes devoid of proteins have provided evidence for the spontaneous formation of nano-scale lipid domains [19] . Whether spontaneous lipid de-mixing is also the primary mechanism for domain formation in biological membranes is a matter on ongoing debate ( reviewed , for example , in [53] ) as lipid—protein interactions may contribute not only to the stabilization of such domains but may even induce their formation . The fact that our lipid-based model of nanodomain formation in the canalicular membrane of hepatocytes indeed recapitulates a number of experimental findings on the size and lipid composition of bile micelles lends support to the view that spontaneous formation of pure Lo and Ld lipid domains without further assistance of membrane proteins is sufficient to enable the extraction of tiny membrane fragments from Ld domains in the presence of solubilizing agents . Whereas Ld domains are disrupted by the process of bile micelle formation and thus have to be permanently recreated , it is likely that the Lo lipid domains once formed are stabilized by the insertion of membrane proteins involved in the active transport for the various bile components and asymmetric distribution of lipids between the internal and external leaflet . Intriguingly , Ld nanodomains obtained in our simulations contained PC , SM and CH in relative fractions that perfectly matched their relative abundance in the bile . This finding suggests that the three major lipids of the bile are not independently solubilized from the membrane but secreted in a concerted manner just in proportions present in the Ld nanodomains . In our simulations the size of nanodomains increased with increasing life-times in a sub-linear fashion . Spectroscopic measurements suggest the life-times of nanodomains in biological membranes to be not longer than a few milliseconds . For this time window our simulations predict a maximal size of Ld nanodomains of only a few hundred lipids . Our lattice model allows calculating the size and geometry of nanodomains which represent important factors determining the rate with which membrane patches can be solubilized and extracted from the external leaflet . These simulations suggest that the LSR has a maximum for critical patch sizes of 100–400 lipids . Remarkably , the predicted optimal size of lipid patches is in good agreement with the size of micelles that are usually extracted from artificial membranes [28 , 48] . Of note , even the largest patches that in our simulations were found to be extractable in a time window of a few microseconds were at least one order of magnitude smaller than bile vesicles observed by means of ultra-rapid cryofixation [7] . We suppose that these vesicles may derive from a fusion and rearrangement of smaller nano-micelles as those suggested by our simulations ( micelle-to-vesicle transition , [54] ) . Such a mechanism would also better explain the formation of bilayered vesicles by pinch-off from a monolayer . The fact that some of the larger bile vesicles were found in direct contact with the canalicular membrane does not necessarily imply that they have originated from exocytosis , as suggested in [7] . Rather , they may represent vesicles that after their formation from micelles back-fuse with the canalicular membrane to be endocytosed [55 , 56] . Since altered phospholipid composition of the canalicular membrane can result in impaired bile formation and cellular damage we carried model simulations where the CH and PC content of the canalicular membrane was varied over a wide range ( Fig . 4 ) . A reduced PC content of the outer leaflet of the canalicular membrane can result from impaired mdr2 activity . mdr2 selectively transports PC to the outer membrane depending on BS concentration . Experimental studies on changes of bile flow and bile lipid composition in mice being homozygous for a disruption of the MDR2 gene , the analog of the human MDR3 [57 , 58] revealed an only moderate decline of the PC flow into the bile in the heterozygous animals whereas in the homozygous mice the flow of PC and CH was almost completely abolished ( lower than 5% of the normal ) . In our simulations a PC content of less than 30% completely prevented the extraction of patches with a size of about 600 lipids . In contrast , extraction of single lipids is predicted to continue—albeit with decreasing activity—if the PC content goes to zero . Hence , these simulations lend further support to the existence of a patch-extraction mechanism of membrane lipids . Unfortunately the residual PC content of the canalicular membrane has not been determined in the mdr2 knockout experiments so that a comparison with the predicted threshold value of about 30% PC content is not possible . However , considering that PC is an indispensable phospholipid of the plasma membrane and that besides mdr2 other transporters of PC exist , for example , the relatively unspecific MDR1 encoded P-glycoprotein [59] , a residual PC content of 30% is not unlikely . Finally we examined the dependence of the biliary phospholipid composition on the CH content of the outer canalicular membrane . Experimental data implicate that the heterodimer of the two half-transporters ABCG5 and ABCG8 translocates CH to the outer leaflet of the canalicular membrane [60 , 61] . Mice with knockout of both transporters ( Abcg5+/g8+ ) displayed strongly reduced biliary CH excretion [62] . This is reproduced by our simulations . The fraction of biliary CH shows a strong correlation with the CH content of the membrane . On the other hand the solubilizable fraction of the canalicular membrane decreases with increasing CH concentration demonstrating the ordering and stabilizing effect of CH [43] . Sufficient CH is required for stability of the canalicular membrane and protects cells from BS induced damage . Taken together , our model-based calculations provide further evidence for the emergence of short-lived nanodomains in the external leaflet of the canalicular hepatocyte membrane . The best overall agreement between model simulations and experimental facts is achieved if we assume that the lipid transfer into the bile is mediated by small patches of 100–400 lipids which are extracted from the Ld nanodomains of the external leaflet by BS and which contain the main lipids CH , PC and SM in proportions as also found in the bile . Likely , the primary nano-micelles further maturate to larger lipid vesicles ( see Fig . 5 ) .
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Formation of the bile is one of the central functions of the liver . The bile fluid aids in the digestion of edible fats and removal of drugs and toxins from the body . The bile fluid is mainly composed of bile salts ( BS ) , phosphatidylcholine ( PC ) and cholesterol ( CH ) in a fairly fixed proportion that prevents liver impairment by gallstone formation or cholestasis . During bile formation , BS are actively pumped out of the hepatocyte into the extracellular space where they extract PC and CH from the canalicular membrane . This extraction process bears the risk for the canalicular membrane to be destructed . Hence , only a certain fraction of the membrane should be accessible to the solubilizing activity of BS . We have developed a mathematical model that describes the temporal formation of CH-enriched ordered and PC-enriched disordered nanodomains in the canalicular membrane . Model simulations reveal that the disordered nanodomains exhibit a composition of PC and CH similar to that also found in the bile . From this finding and the good concordance of model simulations with experimental data we conclude that PC and CH are mainly secreted into the bile from the disordered nanodomain . Our work adds a new layer of physiological importance to the spontaneous formation of lipid domains in biological membranes .
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[
"Abstract",
"Introduction",
"Material",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Computer Simulations Suggest a Key Role of Membranous Nanodomains in Biliary Lipid Secretion
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The biology and behavior of adults differ substantially from those of developing animals , and cell-specific information is critical for deciphering the biology of multicellular animals . Thus , adult tissue-specific transcriptomic data are critical for understanding molecular mechanisms that control their phenotypes . We used adult cell-specific isolation to identify the transcriptomes of C . elegans’ four major tissues ( or “tissue-ome” ) , identifying ubiquitously expressed and tissue-specific “enriched” genes . These data newly reveal the hypodermis’ metabolic character , suggest potential worm-human tissue orthologies , and identify tissue-specific changes in the Insulin/IGF-1 signaling pathway . Tissue-specific alternative splicing analysis identified a large set of collagen isoforms . Finally , we developed a machine learning-based prediction tool for 76 sub-tissue cell types , which we used to predict cellular expression differences in IIS/FOXO signaling , stage-specific TGF-β activity , and basal vs . memory-induced CREB transcription . Together , these data provide a rich resource for understanding the biology governing multicellular adult animals .
Animals progress through many stages of development before reaching adulthood , and as adults , they exhibit metabolic and behavioral differences from developing animals . Studies in the nematode C . elegans demonstrate this phenomenon well: both biological responses and gene expression differ significantly in different stages [1 , 2] . Therefore , to understand the biology underlying tissue-specific adult behavior , it is critical to identify adult , tissue-specific transcriptomes . The advent of whole-genome gene expression approaches allowed the identification of a cell’s full set of mRNA transcripts , ushering in a new era of understanding biological dynamics [3] . The ongoing development of new methods to isolate and sequence individual cells in order to approximate their metabolic and biochemical state has refined our understanding of single cells [4] . The next frontier in this work is the gene expression analysis of whole animals on a tissue-by-tissue and cell-by-cell basis . While tissue-specific expression has been measured in other organisms , the combination of extremely small tissue size and adult cuticle impermeability have previously prevented the analysis of adult worm tissue expression , which is necessary in order to understand adult processes , including systemic aging , tissue-specific aging , and cell non-autonomous control of aging . More broadly speaking , adult tissue-specific expression can be used to better understand signaling and cell autonomous processes and to compare expression to that in other adult organisms . The complexity of tissue autonomous and non-autonomous mechanisms of aging and disease requires the understanding of tissue-specific expression . The delineation of adult tissue expression presented here , combined with the genetic and molecular tools available in the worm , provide a unique chance to more directly model aging and disease compared to more complex organisms . C . elegans is the simplest multicellular model system , with only 959 somatic ( non-germline ) cells in the fully developed adult animal . Four tissues—muscles , neurons , intestine , and the epidermis ( or “hypodermis” ) —comprise the bulk of the animal’s somatic cells and are largely responsible for the animal’s cell autonomous and non-autonomous biological regulation . Until recently , most transcriptional analyses of C . elegans adults utilized whole worms , but the need to identify tissue-specific transcripts in order to better understand both tissue-specific and non-autonomous signaling has become apparent . Several tissue profiling techniques that rely on PAB-mediated RNA immunoprecipitation have been widely used , but these methods often introduce very high non-specific background [5] and studies have not focused specifically on adult animals [1 , 6 , 7] . Recent spliced-leader RNA-tagging methods [8] that avoid this problem are also limited , since only 50–60% of C . elegans genes exhibit SL1-based trans-splicing [9] . Furthermore , tools used to isolate embryonic and larval stage C . elegans cells using cell sorting [1 , 10–13] have allowed the transcriptional profiling of specific tissues and cell types , shedding light on larval development processes , but lack information specific to adult tissues . Much of worm behavioral analysis , and all aging studies—for which C . elegans is a premier model system—[14] are , not is performed in adults , which are less amenable to standard isolation approaches due to their tough outer cuticle . Therefore , we developed a method to disrupt and isolate adult tissues [2] . That work revealed that the adult neuronal transcriptome differs significantly from earlier embryonic and larval stages , and that the adult neuronal transcriptome best reveals genes involved in behavior and neuronal function . The other major tissues—muscle , intestine , and hypodermis—are likely to provide insight into important adult-specific processes that are widely studied in C . elegans as models of human biology , such as pathogenesis , reproduction , age-related decline , and others . Here we have performed cell-specific transcriptional analysis and characterization of the four major somatic tissues isolated from adult worms . As examples of the utility of these data , we used the highly enriched tissue gene sets to identify transcriptional parallels between worm and human tissues and to determine the tissue specificity of DAF-16 transcriptional targets . Additionally , our sequencing method allowed the identification of tissue-specific alternatively spliced gene isoforms , which we have used to explore tissue-specific collagen isoform expression . Finally , we present a tool that predicts gene expression in 76 different sub-tissue cell types , and demonstrate its utility in the characterization of individual genes , gene classes , and potential cellular differences in gene expression for several different signaling pathways . Together , these data provide a rich resource for the examination of adult gene expression in C . elegans .
To identify the transcriptomes of adult C . elegans tissues , it is necessary to break open the outer cuticle and release , filter , and sort cells while minimizing cell damage [2] . We collected 27 Day 1 adult tissue samples ( 7 neuron , 5 intestine , 7 hypodermis , 8 muscle ) , utilizing strains with fluorescently-marked neurons ( Punc-119::gfp ) , muscle ( Pmyo-3::mCherry ) , hypodermis ( pY37A1B . 5::gfp ) , and intestine ( Pges-1::gfp; Fig 1A; see Methods for details ) . Multidimensional scaling analysis ( Fig 1B ) suggests that the samples cluster best with their respective tissue types , and that muscle and hypodermis are most closely related , while neuronal and intestine samples are more distinct from one another . Subsampling analysis [15] , which determines whether sequencing has been performed to sufficient depth , suggests that this estimate of gene expression is stable across multiple sequencing depths ( S1A Fig ) , and thus gene expression differences represent true differences between tissues . We obtained reads across the whole transcript length ( rather than selecting the 3’ end of mRNA via the polyA tail ) in order to analyze tissue-specific isoform expression ( see below ) . To assess RNA degradation in each sample , we determined the gene body coverage for all 20 , 389 protein-coding genes [16]; the transcripts have consistent , uniform coverage , with best coverage within the gene bodies ( S1B Fig ) . “Expressed” genes are defined as those with both ( 1 ) an average log ( rpkm ) greater than 2 , and ( 2 ) with each replicate of that tissue having a log ( rpkm ) greater than 1 , resulting in the detection of 8437 neuron , 7691 muscle , 7191 hypodermis , and 9604 intestine protein-coding genes ( Fig 1C , S1 Table ) ; 5360 genes are expressed in all sampled tissues . Hierarchical clustering of the top 2000 differentially-expressed genes per sample across the four tissue types shows that intra-group tissue samples are most similar , specific genes characterize particular tissue types ( especially neurons ) , and that there is a subgroup of genes expressed in all tissues ( Fig 1D ) . As expected , Gene Ontology ( GO ) analysis of the ubiquitously-expressed gene set shows that basic cell biological and metabolic processes are shared , including such terms as intracellular transport , protein metabolism , catabolism , glucose metabolism , ribosome biogenesis , translation elongation , maintenance of cell polarity , and microtubule-based process ( Fig 1E; S2 Table ) . Additionally , terms associated with protection of the cell , such as response to stress , autophagy , protein folding , gene silencing by RNAi , and determination of adult lifespan appear in the ubiquitous category .
OH441: otIs45[Punc-119::GFP] , CQ163: wqEx34[Pmyo-3::mCherry] , CQ171: [Py37a1b . 5::GFP] , BC12890: [dpy-5 ( e907 ) I; sIs11337 ( rCesY37A1B . 5::GFP + pCeh361 ) , SJ4144: zcIs18 ( Pges-1::GFP ) , CQ236: Pcrh-1g::GFP + Pmyo-2::mcherry . Worm strains were maintained at 20°C on HGM plates using E . coli OP50 . Strains were synchronized using hypochlorite treatment prior cell isolation and grown to day 1 of adulthood on HGM plates with E . coli OP50 . Synchronized day 1 adult worms with GFP-labeled neurons , muscle , hypodermis , and intestine ( Punc119::GFP , Pmyo-3::mCherry , pY37A1B . 5::GFP , and Pges-1::GFP ) were prepared for cell isolation , as previously described [2] . Cells were briefly subjected to SDS-DTT treatment , proteolysis , mechanical disruption , cell filtering , FACS , RNA amplification , library preparation , and single-end ( 140 nt ) Illumina sequencing , as previously described [2] . Neuron cell suspensions were passed over a 5 μm syringe filter ( Millipore ) . Muscle and hypodermal samples were gently passed over a 20 mm nylon filter ( Sefar Filtration ) . Intestinal cells were passed through a 35 mm filter and by spinning at 500 x g for 30s in a tabletop centrifuge . The filtered cells were diluted in PBS/2% FBS and sorted using a either a FACSVantage SE w/ DiVa ( BD Biosciences; 488nm excitation , 530/30nm bandpass filter for GFP detection ) or a Bio-Rad S3 Cell Sorter ( Bio-Rad; 488nm excitation ) . Gates for detection were set by comparison to N2 cell suspensions prepared on the same day from a population of worms synchronized alongside the experimental samples . Positive fluorescent events were sorted directly into Eppendorf tubes containing Trizol LS for subsequent RNA extraction . For each sample , approximately 50 , 000–250 , 000 GFP or mCherry positive events were collected , yielding 5–25 ng total RNA . Both sorters were used for each tissue , and the type of sorter did not affect the distribution of samples by multidimensional scaling analysis ( Fig 1B ) , suggesting that the sorter did not contribute to the variability between samples of a given tissue . RNA was isolated from FACS-sorted samples as previously described [2] . Briefly , RNA was extracted using standard Trizol/ chloroform/ isopropanol method , DNase digested , and cleaned using Qiagen RNEasy Minelute columns . Agilent Bioanalyzer RNA Pico chips were used to assess quality and quantity of isolated RNA . 10 to 100 ng of the isolated quality assessed RNA was then amplified using the Nugen Ovation RNAseq v2 kit , as per manufacturer suggested practices . The resultant cDNA was then sheared to an average size of ~200 bp using Covaris E220 . Libraries were prepared using either Nugen Encore NGS Library System or the Illumina TruSeq DNA Sample Prep , 1 μg of amplified cDNA was used as input . RNA from a subset of samples was amplified using the SMARTer Stranded Total RNA kit-pico input mammalian , as per manufacturer suggested practices . No differences were observed between the two methods , and samples amplified by different methods clustered well ( Fig 1B ) . The resultant sequencing libraries were then submitted for sequencing on the Illumina HiSeq 2000 platform . 35–200 million reads ( average of 107 , 674 , 388 reads ) were obtained for each sample and mapped to the C . elegans genome . Sequences are deposited at NCBI BioProject PRJNA400796 . FASTQC was used to inspect the quality scores of the raw sequence data , and to look for biases . The first 10 bases of each read were trimmed before adapter trimming , followed by trimming the 3’ end of reads to remove the universal Illumina adapter and imposing a base quality score cutoff of 28 using Cutadapt v1 . 6 The trimmed reads were mapped to the C . elegans genome ( Ensembl 84/WormBase 235 ) using STAR [72] with Ensembl gene model annotations ( using default parameters ) . Count matrices were generated for the number of reads overlapping with the gene body of protein coding genes using featureCounts [73] . The per-gene count matrices were subjected to an expression detection threshold of 1 count per million reads per gene in at least 5 samples . EdgeR [74] was used for differential expression analysis and the multidimensional scaling ( MDS ) analysis . MDS is a method that aims to visualize proximity data in such a way that best preserves between-sample distances and is a commonly used technique ( similar to PCA ) to transform higher-dimension dissimilarity data into a two-dimensional plot . Here , we used the log-fold-change of expression between genes to compute distances . Genes at FDR = 0 . 05 were considered significantly differentially expressed . DEXSeq [75] was used for differential exon usage ( splicing ) analysis . Count matrices of the aligned sequencing data were down-sampled using subSeq [15] . Reads were down-sampled at proportions using 10^x , starting at x = -5 and increasing at 0 . 25 increments to 0 . The down-sampled count matrices were used to assess stability of number of expressed genes detected at multiple depths ( S1A Fig ) . Because of minimum library sizes for tractable differential exon usage analysis , reads with down-sampled proportions using 10^x , from x = -2 , increasing at 0 . 25 increments to 0 were used for assessment of power in detecting differential splicing ( S1B Fig ) . Hypergeometric tests of Gene Ontology terms were performed on tissue-enriched gene lists; GO terms reported are a significance of q-value < 0 . 05 unless otherwise noted . REVIGO was used to cluster and plot GO terms with q-value < 0 . 05 . RSAtools [76] was used to identify the -1000 to -1 promoter regions of the tissue enriched genes and perform motif analysis . Matrices identified from RSAtools were analyzed using footprintDB [77] to identify transcription factors predicted to bind to similar DNA motifs . Alternatively , motifs were analyzed using gProfiler [78] . Hypodermal genes appearing in metabolic GO terms were selected from the top of the tissue-enriched list ( aldo-2 , gpd-2 , sams-1 , cth-2 , pmt-1 , idh-1 , and fat-2 ) or the expressed list ( far-2 and gpd-3 ) and knocked down using RNAi and compared to a vector ( L4440 ) control . On day 1 of adulthood , all worms were stained in Oil Red O for 6–24 hours and then imaged using a Nikon Eclipse Ti microscope at 20x magnification [79] . Images were analyzed for mean intensity in fat objects using CellProfiler [80] . Additional genes from the hypodermal unique list were also selected and tested for fat ( Oil Red O ) levels . Human orthologs [30] of genes in our tissue-enriched gene lists were compared with curated tissue-specific gene annotations from the Human Protein Reference Database [31] for significant overlap ( hypergeometric test ) . ‘Tissue-enriched’ genes are highly enriched relative to all other tissues , defined as genes that are highly expressed ( logRPKM > 5 ) and significantly differentially expressed relative to the average expression across all of the other tissues ( FDR ≤ 0 . 05 , logFC > 2; S8 Table ) . ‘Unique’ tissue-specific genes are strongly expressed ( logRPKM > 5 ) and significantly differentially expressed in comparison to the expression of each of the three other tissues ( FDR ≤ 0 . 05 , logFC > 2 for each comparison; S9 Table , S1E Fig ) . The expression level ( expressed defined as log ( rpkm ) >2 ) for previously published IIS/FOXO targets ( Tepper et al . , 2013 , cut-off 5% FDR ) were identified for each tissue . Tissue overlaps were graphed in Venn diagrams using the Venn diagram package in R . To construct these models , we needed a large data compendium and high quality examples of tissue expression . We assembled 273 C . elegans expression datasets ( comprised of both adult and developmental expression data ) , representing 4 , 372 microarray and RNA-seq samples , including our tissue-ome library . All other datasets were downloaded from the Gene Expression Omnibus ( GEO ) data repository , ArrayExpress Archive of Functional Expression Data , and WormBase . Samples from each dataset were processed together ( duplicate samples were collapsed , background correction and missing value imputation were executed when appropriate ) . Within each dataset , gene expression values were normalized to the standard normal distribution . All datasets were then concatenated , and genes that were absent in only a subset of datasets received values of 0 ( in datasets in which they were absent ) . The predictions that were used to analyze the tissue-ome dataset were generated using a data compendium that excluded the tissue-ome library . Gene annotations to tissues and cell types were obtained from curated anatomy associations from WormBase [81] ( WS264 ) and other small-scale expression analyses as curated by Chikina et al . ( 2009 ) . Only annotations based on smaller scale experiments ( e . g . , single-gene GFP , in situ experiments ) were considered for the gold standard , excluding annotations derived from SAGE , microarray , RNA-seq , etc . Annotations from both adult and developing worm were considered . Annotations were mapped and propagated ( up to each of its ancestor terms , e . g . , a gene directly annotated to dopaminergic neuron would thus be propagated up to ancestor terms such as neuron and nervous system and included in the corresponding gold standards ) based on the WormBase C . elegans Cell and Anatomy Ontology , where a stringent cutoff was used for which tissues and cell types were retained ( >50 direct annotations and >150 propagated annotations ) . We defined a “tissue-slim” based on system-level anatomy terms in the WormBase anatomy ontology ( immediate children of “organ system” and “sex specific entity , ” under “functional system” ) . The nine resulting terms are: alimentary system , coelomic system , epithelial system , excretory secretory system , hermaphrodite-specific , male-specific , muscular system , nervous system , and reproductive system . For each of the 76 tissues that were retained , a tissue-gene expression gold standard was constructed in which genes annotated ( directly or through propagation , i . e . , the gene has been associated with either the particular tissue or a part of that tissue in a smaller scale experiment ) to the tissue were considered as positive examples . Genes that were annotated to other tissues , but not in the same tissue system , were considered negative examples . Thus , genes were assigned as positive or negative examples of tissue expression while taking into account the tissue hierarchy represented in the Cell and Anatomy Ontology . Our tissue-gene expression predictions and similarity profiles have all been made accessible at a dynamic , interactive website , http://worm . princeton . edu . From this interface , users can explore the predicted expression patterns of their gene ( s ) of interest . To facilitate this exploration , we have designed an interactive heatmap visualization that allows users to view hierarchically clustered expression patterns or sort by any gene or tissue model of interest . In addition , we also provide suggestions of genes with similar tissue expression profiles , which users can immediately visualize alongside their original query . All predictions and visualizations are available for direct download . For each of the 76 tissues and cell types , we used the expression data compendium and corresponding gold standard as input into a linear support vector machine ( SVM ) to make predictions for every gene represented in our data . Specifically , given the vector of gene expression data ( xi ) and training label ( yi:{-1 , 1} ) for gene i , hyperplanes described by w and b , and constant c , the SVM’s objective function is: minw , ξ12wTw+c∑iξi , subjecttotheconstraints:yi ( w⋅xi−b ) ≥1−ξi , ξi≥0 . SVM parameters were optimized for precision at 10% recall under 5-fold cross validation . Resulting SVM scores were normalized to the standard normal distribution for any comparisons across tissues . Feature weights for each of the tissue SVM models were also retained for ranking and analysis of samples .
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C . elegans is the simplest multi-cellular model system , with only 959 somatic cells in the fully-developed adult . This work describes the isolation and RNA-seq analysis of the worm’s major adult tissues . Previously , the isolation of adult tissues has been hampered by the worm’s tough outer cuticle , but identification of the transcriptomes of adult tissues is necessary to understand the biology of adults , which differs substantially from that of embryonic and larval cells . We recently developed a method to isolate and RNA-sequence adult tissues , and applied it here to characterize the muscle , neuron , intestine , and epidermis adult transcriptomes and isoform profiles . The data reveal interesting new characteristics for adult tissues , particularly the hypodermis’ metabolic function , which we have functionally tested . The tissue transcriptomes were also used to identify relevant human tissue orthologs in an unbiased manner . Finally , we present a new prediction tool for gene expression in up to 76 tissues and cell types , and we demonstrate its utility not only in predicting cell-specific gene expression , but in diagnosing expression changes in different genetic pathways and contexts .
|
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2018
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Transcriptome analysis of adult Caenorhabditis elegans cells reveals tissue-specific gene and isoform expression
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Chronic pain is a debilitating problem , and insights in the neurobiology of chronic pain are needed for the development of novel pain therapies . A genome-wide association study implicated the 5p15 . 2 region in chronic widespread pain . This region includes the coding region for FAM173B , a functionally uncharacterized protein . We demonstrate here that FAM173B is a mitochondrial lysine methyltransferase that promotes chronic pain . Knockdown and sensory neuron overexpression strategies showed that FAM173B is involved in persistent inflammatory and neuropathic pain via a pathway dependent on its methyltransferase activity . FAM173B methyltransferase activity in sensory neurons hyperpolarized mitochondria and promoted macrophage/microglia activation through a reactive oxygen species–dependent pathway . In summary , we uncover a role for methyltransferase activity of FAM173B in the neurobiology of pain . These results also highlight FAM173B methyltransferase activity as a potential therapeutic target to treat debilitating chronic pain conditions .
Chronic pain is a major clinical problem and affects approximately 20% of the population [1–3] . Inflammation , tissue , and nerve damage induce long-lasting changes in the nociceptive circuitry , causing pain and exaggerated responses to noxious and innocuous stimuli [4 , 5] . Although many efforts have been undertaken to elucidate the molecular pathways driving chronic pain , a complete understanding of the mechanisms leading to chronic pain is missing , hampering the development of highly needed therapeutic approaches to treat debilitating pain conditions . At the mechanistic level , the activation of spinal cord glial cells is thought to drive persistent pain . In various rodent models of chronic pain , including neuropathic and persistent inflammatory pain , spinal cord microglia have an activated phenotype and produce inflammatory mediators that trigger or maintain the long-lasting changes in nociceptive circuitry , thereby contributing to persistent pain [6–10] . Many efforts have been undertaken to elucidate how peripheral sensory neurons drive the engagement of these glial cells in chronic pain conditions . Sensory neurons engage spinal glial cells through the release of soluble factors [6 , 11 , 12] . However , the intracellular pathways in sensory neurons upstream of the release of glia-activating factors are still unknown . Another driving force of pathological pain is the formation of reactive oxygen species ( ROS ) [13] . ROS are derived from electrons leaking from the mitochondrial electron transport chain and can initiate proinflammatory cascades and activate microglia in the central nervous system [14] . Importantly , increased ROS levels in the dorsal root ganglia ( DRG ) and/or spinal cord contribute to chronic pain development in several rodent models [13 , 15–18] , and altered ROS levels are associated with chronic pain development in humans [19–21] . Further understanding of the mechanism that drives pathological pain is needed . The identification of novel “pain genes” that lie at the root of the transition from acute to persistent pain , possibly through glial cell engagement and ROS formation , aids in this understanding and could identify highly needed novel targets for therapeutic pain interventions . Several genome-wide association studies ( GWAS ) in humans have offered a glimpse of the genetic contributions to pain syndromes . Nevertheless , very few have pinpointed new pain genes that provided novel insights in pain neurobiology . Recently , specific single nucleotide polymorphisms ( SNPs ) have been identified in patients with chronic widespread pain in a large-scale GWAS [22] . Two top intronic SNPs on chromosome 5p15 . 2 were shown to be associated with a 30% higher risk of developing chronic widespread pain . This genomic region encodes Chaperonin Containing TCP1 Subunit 5 ( CCT5 ) and the hitherto functionally uncharacterized FAM173B protein , indicating potential novel pain genes . The 2 top SNPs found in the GWAS are linked to a nonsynonymous SNP ( rs2438652 ) in the FAM173B gene and to 1 intronic SNP in FAM173B ( rs2445871 ) that has a predicted effect on FAM173B expression levels [22 , 23] . However , the molecular function of FAM173B and its potential role in the neurobiology of chronic pain have not been revealed . Here , we identify FAM173B as a lysine-specific protein methyltransferase that resides in the mitochondrial cristae and show that neuronal FAM173B methyltransferase activity controls the development of chronic pain through an ROS-dependent pathway resulting in the activation of glial cells .
To determine whether FAM173B is involved in chronic pain , we down-regulated Fam173b expression in vivo by lumbar intrathecal injections of a nuclease-resistant antisense oligodeoxynucleotide ( ODN ) , a method that has been shown to reduce mRNA expression and protein translation [24] . We injected mouse Fam173b antisense ODN ( mFam173b-AS ) intrathecal into the lumbar enlargement because , through this application route , antisense ODNs mainly target the lumbar DRGs [25–28] . Five daily intrathecal injections of mFam173b-AS reduced mFam173b mRNA expression in vivo in lumbar DRG in the complete Freund’s adjuvant ( CFA ) model of persistent inflammatory pain [29] and in vehicle-treated mice ( S1B Fig ) , without affecting spinal cord mFam173b mRNA expression ( Fig 1A ) . Intrathecal injection of a fluorescently labeled mFam173b-AS targeted almost all sensory neurons and some other cells , including ionized calcium binding adaptor molecule 1 ( Iba1 ) and glial fibrillary acidic protein ( GFAP ) -positive cells in the DRG ( S1A Fig ) . Intrathecal administration of mFam173b-AS at day 5 until 10 in the CFA model of persistent inflammatory pain abrogated thermal and mechanical hyperalgesia ( Fig 1B/1C ) . These results were confirmed by using another mFam173b-AS targeted to a different region of mFam173b mRNA ( S1B–S1D Fig ) , indicating the ODN-induced effects are likely not due to off-target effects . Intrathecal injections of mFam173b-AS from day 1 until 9 also attenuated the development of neuropathic pain in the spared nerve injury model [30] . Mechanical thresholds in the contralateral paw were not affected by mFam173b-AS treatment ( Fig 1D ) . To test if FAM173B in sensory neurons is central to the inhibitory effect of intrathecal mFam173b-AS on chronic inflammatory pain , we performed a rescue experiment . We expressed human FAM173B ( hFAM173B ) in sensory neurons in vivo using herpes simplex virus ( HSV ) -mediated gene transfer in mice treated intrathecally with mFam173b-AS that does not recognize human FAM173B mRNA . HSV selectively infects primary sensory neurons , and intraplantar or intrathecal HSV amplicons encoding for hFAM173B and green fluorescent protein ( GFP ) transferred GFP ( S1E Fig ) and hFAM173B into sensory neurons in the DRG ( Fig 2A and S1F Fig ) but not to other cells in the DRG such as F4/80-positive macrophages ( S1F Fig ) . Intraplantar HSV-hFAM173B injections induced protein expression of hFAM173B detected by western blot in the lumbar DRG ( S1G Fig ) . Furthermore , GFP was detected in peripherin-positive sciatic nerve fibers and peripherin-positive nerve endings in the skin of the injected hind paw , indicating gene transfer to sensory neurons ( S1H/S1I Fig ) . This sensory neuron selective expression of proteins using HSV is consistent with previous literature [27 , 31 , 32] . Intraplantar ( to target sensory neurons innervating the hind paw ) ( Fig 2B/2C ) or intrathecal ( S1J/S1K Fig ) administration of HSV-hFAM173B completely prevented the mFam173b-AS–mediated attenuation of persistent thermal and mechanical hypersensitivity in the CFA model , indicating that sensory neuron FAM173B is required for persistent inflammatory pain . Next , we tested whether increasing sensory neuron hFAM173B is sufficient to promote the transition of transient inflammatory pain into persistent pain . Intraplantar injection of 5 μl of 1% carrageenan induced transient hyperalgesia [27 , 33] that resolved within 4 to 6 days ( Fig 2D/2E ) . Intraplantar ( Fig 2D/2E ) or intrathecal ( S1L/S1M Fig ) administration of HSV-hFAM173B prior to the induction of transient inflammatory pain markedly prolonged carrageenan-evoked thermal and mechanical hyperalgesia as compared to mice treated with control HSV empty vector ( HSV-EV ) . A single carrageenan injection in one paw induces a reduction in weight bearing of the affected paw that normalizes within 9 days . However , in mice overexpressing hFAM173B in sensory neurons , the reduction in weight bearing remained for at least 19 days after carrageenan ( Fig 2F ) . Moreover , sensory FAM173B expression induced spontaneous pain , measured using a conditioned place preference ( CPP ) test [34 , 35] , that was present 1 month after intraplantar carrageenan injection ( Fig 2G ) . Overall , these results indicate that FAM173B in sensory neurons promotes development of chronic pain . Next , we tested whether endogenous mFam173b mRNA expression levels are increased in the DRG during the persistent phase of CFA-induced inflammatory pain . At 1 week after intraplantar CFA injection , mFam173b mRNA expression in the DRG was increased compared to naive animals . In contrast , during acute inflammation at day 1 and 3 after CFA injections , mFam173b expression levels were indistinguishable from controls ( S1N Fig ) , consistent with our previous findings [22] . Bioinformatic analysis of FAM173B protein sequences show that FAM173B harbors characteristic motifs involved in binding of the methyl donor S-adenosyl-L-methionine ( SAM ) . Moreover , it shows similarities for a subclass of methyltransferases characterized by a topology of 7 β-strands ( 7BS ) ( Fig 3A/3B ) [36] . Human and mouse FAM173B are ubiquitously expressed ( S2A/S2B Fig ) . An archaeal lysine-specific methyltransferase shows some homology with human FAM173B [37] , therefore we explored whether hFAM173B specifically methylated lysine residues . To this end , we incubated a radioactive methyl donor , [3H]-SAM , with protein extracts of human embryonic kidney 293 cells ( HEK293 ) together with purified recombinant hFAM173BΔ55 ( without its putative transmembrane domain ) and detected methyltransferase activity by fluorography . These experiments revealed hFAM173B-mediated methylation of high–molecular weight proteins ( Fig 3C ) . To assess specificity of the enzyme , we evaluated homopolymers of lysine and arginine , the 2 most commonly methylated amino acid residues in proteins , as artificial substrates . When incubating recombinant hFAM173BΔ55 ( Fig 3D ) or full-length hFAM173B ( S2C Fig ) with [3H]-SAM and lysine or arginine homopolymers , hFAM173B displayed significant methyltransferase activity on poly-L-lysine but not on poly-L-arginine ( Fig 3D ) . Importantly , a putatively enzymatically inactive mutant of hFAM173B ( hFAM173B-D94A ) , generated by mutating a key conserved residue ( Asp94 ) in the SAM-binding Motif I of hFAM173B ( Fig 3B ) [38] , did not show significant methyltransferase activity ( Fig 3E ) . The D94A mutation did not affect expression ( S2D Fig ) . To determine the subcellular localization of FAM173B , we expressed C-terminally GFP-tagged hFAM173B and mFam173b in Neuro2a ( N2A ) , a neuronal cell line . Confocal imaging of GFP-tagged hFAM173B indicated that FAM173B colocalized with the mitochondrial dye MitoTrackerRedCMXROS but not with the endoplasmic reticulum marker protein disulfide-isomerase ( PDI ) or the Golgi scaffolding protein PGM130 ( Fig 4A ) . The subcellular localization of mouse Fam173b-GFP and the methyltransferase-inactive mutant hFAM173B-D94A were also confined to mitochondria because they also colocalized with MitoTrackerRedCMXROS ( S2E Fig ) . The localization of FAM173B and the methyltransferase death mutant FAM173B-D94A in mitochondria was further confirmed by western blot analysis of mitochondrial and cytosol fractions of N2A cells ( S2F/S2G Fig ) . Electron microscopy of immunogold labeling of GFP-tagged hFAM173B showed that hFAM173B was predominantly present in the cristae of mitochondria when expressed in HEK293 ( Fig 4B ) or N2A cells ( S2H Fig ) . Finally , endogenous mFam173b is located in mitochondria in cultured primary sensory neurons ( Fig 4C ) . To determine whether FAM173B modulates mitochondrial function , we assessed mitochondrial membrane potential ( ΔΨm ) [39] . Knockdown of mFam173b in N2A cells with mFam173b-AS ( S3A Fig ) reduced accumulation of the ΔΨm-sensitive dye MitoTrackerRedCMXROS compared to cells treated with control mismatch ODN ( MM-ODN ) ( Fig 5A and S3B Fig ) , while overexpression of hFAM173B in N2A cells ( S3D Fig ) increased accumulation of MitoTrackerRedCMXROS ( Fig 5B and S3C Fig ) . These data indicate that FAM173B promotes mitochondrial hyperpolarization . Similarly , overexpression of hFAM173B using HSV-hFAM173B amplicons in cultured primary sensory neurons ( S3E Fig ) or in N2A cells increased the difference in tetramethylrhodamine methyl ester ( TMRM; a dye sequestered by active mitochondria in a ΔΨm-dependent manner [39] ) fluorescence before and after the administration of the respiratory uncoupler carbonyl cyanide p-trifluoromethoxyphenylhydrazone ( FCCP ) ( sensory neurons: Fig 5C; N2A: S3F Fig ) . This indicates that hFAM173B expression in sensory neurons hyperpolarizes mitochondria . Mitochondrial hyperpolarization has been reported to cause increased ROS formation [40 , 41] . Therefore , overexpression of hFAM173B may increase ROS formation in sensory neurons . Human FAM173B overexpression in N2A and HEK293 cells increased fluorescence of the ROS-sensitive dye dihydroethidium ( DHE ) [42] , indicating that FAM173B promotes ROS formation in these cells ( S3G/S3H Fig ) . Similarly , overexpression of hFAM173B in primary sensory neurons in vitro increased DHE fluorescence ( Fig 5D ) . Stimulation of sensory neurons with the prototypic inflammatory mediator tumor necrosis factor α ( TNFα ) for 6 hours , known to promote ROS formation [43] , enhanced DHE fluorescence , which was further increased when hFAM173B was expressed in sensory neurons with HSV-FAM173B ( Fig 5D ) . Next , we addressed whether increased sensory neuron ROS formation also occurs during the hFAM173B-mediated switch from transient to persistent inflammatory pain in vivo . Expression of hFAM173B in sensory neurons increased DHE fluorescence in small ( <25 μm ) -diameter neurons that are central in inflammatory pain [44] , but not in medium- and/or large-diameter neurons ( >25 μm ) , 5 days after intraplantar carrageenan injection ( Fig 5E ) . Next , we assessed whether FAM173B promotes mitochondrial superoxide production in vitro and in vivo . Overexpression of hFAM173B significantly increased fluorescence of the mitochondrial superoxide sensor MitoSox in N2A cells ( S3I Fig ) . In vivo , HSV-mediated expression of hFAM173B in sensory neurons increased MitoTrackerRedCM-H2XROS fluorescence in small ( <25 μm ) -diameter neurons 3 and 6 days after intraplantar carrageenan injection ( Fig 5F and S3J/S3K Fig ) , indicating that hFAM173B expression in sensory neurons promotes ongoing mitochondrial superoxide production in vivo . To assess whether the increased ROS production in sensory neurons contributes to hFAM173B-mediated prolongation of inflammatory pain , we administered the ROS scavenger phenyl-N-t-butylnitrone ( PBN ) during hFAM173B-induced persistent inflammatory hyperalgesia . PBN administration at day 5 after intraplantar carrageenan completely reversed the persistent carrageen-induced mechanical hyperalgesia ( Fig 5G ) in mice expressing hFAM173B in sensory neurons . PBN administration did not affect mechanical thresholds in mice treated with control HSV ( Fig 5G ) . These data indicate that sensory neuron FAM173B-mediated prolongation of inflammation-induced hypersensitivity is maintained through an ROS-dependent pathway . Microglia/macrophage activation and the production of proinflammatory mediators in the spinal cord/DRG play a key role during persistent pain , including persistent inflammatory pain [7 , 10 , 12 , 45 , 46] . ROS formation can initiate proinflammatory cascades and activate microglia in the central nervous system [14] . As a next step , we evaluated whether FAM173B expression in primary sensory neurons promotes the ability of sensory neurons to activate glial cells in vitro in an ROS-dependent manner . Primary sensory neuron cultures were stimulated with 100 ng/ml TNFα [47] for 6 hours with or without the ROS scavenger PBN . After the 6 hours , cells were washed extensively to remove TNFα and then further cultured overnight for 15 hours to capture sensory neuron–derived factors that could drive glial cell activation . The supernatants of unstimulated sensory neurons with or without overexpressing hFAM173B did not trigger microglia to release detectable levels of interleukin 6 ( IL6 ) and TNFα ( Fig 6A ) . However , incubation of primary spinal microglia with the supernatant of these TNFα-stimulated sensory neurons for 24 h promoted microglia to release IL6 , which was strongly enhanced by overexpression of hFAM173B in sensory neurons and completely abolished by incubating sensory neurons with the ROS scavenger PBN during TNFα stimulation ( Fig 6A ) . Overexpression of hFAM173B in sensory neurons also increased TNFα release by microglia ( S4A Fig ) . IL6 and TNFα were not detectable in the conditioned medium or in supernatants of unstimulated microglia , indicating that IL6 and TNFα were released by microglia and not already present in sensory neuron cultures . These in vitro data indicate that hFAM173B expression in TNFα-stimulated sensory neurons promotes the release of glial cell–activating factors in an ROS-dependent manner . To test whether in vivo sensory neuron FAM173B promotes the engagement of microglia and subsequent TNFα release to drive ongoing inflammatory pain , we inhibited TNFα signaling and microglia activity in the spinal cord and DRG by intrathecal injection of a neutralizing anti-TNFα antibody and glial cell inhibitor minocycline , respectively . Intrathecal injection of the neutralizing anti-TNFα antibody at day 7 after intraplantar carrageenan inhibited the sensory neuron–specific , hFAM173B-mediated persistent inflammatory pain ( Fig 6B and S4B Fig ) . Intrathecal injection of minocycline at day 7 after intraplantar carrageenan completely inhibited hFAM173B-induced persistent inflammatory hyperalgesia ( Fig 6C and S4C Fig ) . To further validate the contribution of microglia to FAM173B-mediated prolongation of inflammatory pain , we investigated whether in vivo overexpression of hFAM173B engages glial cells after induction of inflammatory pain . Expression of hFAM173B specifically in sensory neurons increased the Iba1-positive immunofluorescence in DRG and spinal cord at 5 and 10 days after carrageenan treatment compared to mice treated with empty HSV amplicons ( Fig 6D–6F , S4D Fig ) . This neuronal , FAM173B-mediated spinal microglia activation in vivo was attenuated after scavenging ROS with PBN ( S4E Fig ) . Conversely , ODN-mediated knockdown of mFam173b prevented activation of glial cells during CFA-induced persistent pain as shown by the reversion of the CFA-induced increase in Iba1-positive area and mRNA expression in DRG ( Fig 7A–7C ) and spinal cord ( Fig 7D–7F ) . mFam173b-AS treatment during CFA-induced persistent hyperalgesia did not affect the astroglial GFAP mRNA expression in the spinal cord and DRG ( S4F/S4G Fig ) . The reduced signs of glia activation were associated with reduced expression of inflammatory mediators in the spinal cord and DRG known to play a role in persistent pain states [8] . Knockdown of mFam173b at day 5 to 11 after intraplantar CFA prevented the CFA-induced increase in TNFα and IL1β mRNA expression in the spinal cord ( Fig 7G ) . In the DRG , mFam173b knockdown prevented the CFA-induced expression of the chemokine ( C-C motif ) ligand 2 ( CCL2 ) but not of the growth factor Brain-derived neurotrophic factor ( BDNF ) ( Fig 7H ) . Overall , these data indicate that neuronal FAM173B drives the persistence of inflammatory hyperalgesia through an ROS-dependent activation of glial cells . We next determined whether the methyltransferase activity of FAM173B in sensory neurons is required to regulate chronic inflammatory pain through ROS- and glial cell–dependent mechanisms . Intraplantar ( Fig 8A/8B ) or intrathecal administration of HSV amplicons encoding for the methyltransferase-deficient mutant hFAM173B-D94A ( S5A/S5B Fig ) did not prolong carrageenan-induced thermal and mechanical hyperalgesia , while expression of wild-type ( WT ) hFAM173B prolonged transient inflammatory hyperalgesia ( Fig 8A/8B and S5A/S5B Fig ) . In vivo overexpression of hFAM173B-D94A in sensory neurons prior to induction of inflammatory hyperalgesia did not increase Iba1-positive area in the DRG and spinal cord at day 5 after carrageenan injection ( Fig 8C/8D and S5C Fig ) , indicating the requirement of FAM173B methyltransferase activity in sensory neurons to promote chronic pain and glial cell activity . In vitro , overexpression of hFAM173B-D94A did not affect ΔΨm , in contrast to WT hFAM173B , which increased ΔΨm ( Figs 8E and 5A/5C ) . In addition , expression of WT hFAM173B but not hFAM173B-D94A increased the fluorescence of the ROS-sensitive dye DHE in small ( <25 μm ) -diameter neurons at day 5 during carrageenan-induced inflammatory hyperalgesia , indicating that FAM173B-mediated increase in ΔΨm and ROS production is also methyltransferase dependent ( Fig 8F and S5D Fig ) . Finally , culturing spinal microglia with supernatants of TNFα-stimulated sensory neurons expressing WT FAM173B increased IL6 ( Fig 8G ) and TNFα ( S5E Fig ) release by microglia , while overexpressing hFAM173B-D94A had no such effect . Overall , these results indicate that the methyltransferase activity of FAM173B , and not the protein per se , is important to control the development of chronic pain through an ROS-dependent mechanism involving the activation of glial cells ( Fig 9 ) .
The precise mechanisms that lead to the development of persistent pain states remain to be fully uncovered . Here , we establish an important and completely novel role for FAM173B in sensory neurons in the development of chronic pain , identify its enzymatic function , and demonstrate a novel link between chronic pain and protein lysine methylation . First , insights came from a recent GWAS that identified a genomic region associated with chronic widespread pain and that included the FAM173B gene , which was functionally uncharacterized [22] . We show that mFam173b mRNA expression is increased in DRG during chronic inflammatory pain and knockdown of mFam173b expression abrogated persistent inflammatory and neuropathic pain . The localization of FAM173B in mitochondria and its effect on sensory neuron ΔΨm and ROS production highlights a unique lysine-methyltransferase–dependent pathway that regulates inflammation-induced hyperalgesia and spontaneous pain . In addition , we show that neuronal FAM173B methyltransferase activity promotes persistent ROS formation in sensory neurons after a transient peripheral inflammation leading to the engagement of microglia/macrophages in the spinal cord/DRG and persistent pain . Therefore , these data provide a mechanism by which FAM173B contributes to a novel pain pathway in chronic pain . The 7BS class of methyltransferases represents a large group of enzymes that target a wide range of substrates , and several of these enzymes in humans have recently been established as lysine-specific protein methyltransferases [48 , 49] . We show here that FAM173B harbors motifs characteristic of a 7BS methyltransferase and methylates lysine residues to promote chronic pain . A well-studied 7BS methyltransferase in relation with pain is catechol-O-methyltransferase ( COMT ) , which inactivates biological active catechols; reduced COMT enzymatic activity contributes to reduced opioid analgesia and increased pain sensitivity [50 , 51] . Other methyltransferases , such as DNA and histone methyltransferases , modify neuronal morphology , activity , and synaptic plasticity to induce pain hypersensitivity in chronic pain conditions via epigenetic modifications [52 , 53] . FAM173B is different from known pain-promoting methyltransferases because it localizes to mitochondrial cristae and methylates lysine residues in high–molecular weight proteins . Therefore , FAM173B belongs to a unique class of 7BS mitochondrial lysine-specific methyltransferase and promotes ROS production in neurons leading to persistent pain . Mitochondria are essential for adenosine triphosphate ( ATP ) generation , calcium buffering , and ROS generation in sensory neurons [13] . Mitochondrial dysfunction plays a role in many neurological disorders such as Parkinson disease , Alzheimer disease , and Huntington disease [54–56] , but the role of mitochondria in pain is relatively little explored [13] . Mitochondrial dysfunction contributes to painful peripheral neuropathies evoked by diabetes , chemotherapy , and trauma-induced nerve injury in humans and rodents [13 , 15 , 57 , 58] . Recent studies also highlight a link between sensory neuron mitochondrial abnormalities and chronic inflammatory pain development . A data-independent acquisition mass spectrometry of the DRG proteome during CFA-induced inflammatory pain showed differential expression of a multitude of proteins involved in mitochondrial functioning . Inhibition of mitochondrial functioning in vivo during CFA-induced inflammatory pain using rotenone , a mitochondrial complex I inhibitor , diminished the inflammation-induced hyperalgesia [59] . Moreover , neuropathic and inflammatory pain is associated with increased mitochondrial oxygen consumption in the sciatic nerve and increased superoxide production in the spinal cord , respectively [57 , 60] . Interestingly , signs of mitochondrial dysfunction and ROS production are also observed in patients with complex regional pain syndrome and fibromyalgia , including individuals with chronic widespread pain [19 , 20] . Although ROS are thought to be central in chronic pain conditions , clinical trials with antioxidant therapies have been disappointing [61 , 62] . The exact reasons why they fail are not known , but antioxidant treatments likely do not scavenge ROS directly at the intracellular source , preventing full inhibition of ROS-dependent pathways . Therefore , there is a need to identify critical upstream processes of ROS production in chronic pain that may represent better targets to inhibit these ROS-dependent processes leading to pain . Here , we identified FAM173B as a methyltransferase that , when overexpressed , hyperpolarizes mitochondria and promotes mitochondrial and neuronal ( cytosolic ) ROS production after peripheral inflammation , leading to the engagement of microglia and persistence of inflammatory pain . The question remains whether the observed increase in cytosolic ROS formation after hFAM173B overexpression is a consequence of the FAM173B-induced mitochondrial superoxide production or whether it is caused by other cytosolic sources such as oxidants producing peroxisomes or endoplasmic reticula [63 , 64] . FAM173B may represent an important upstream factor of persistent ROS production in sensory neurons leading to pain . As such , FAM173B could represent the long-sought therapeutic target upstream of ROS production to treat persistent pain . However , FAM173B is ubiquitously expressed , thus potentially dampening its potential as therapeutic target . Nevertheless , FAM173B expression increases in sensory neurons through yet unknown mechanisms during inflammatory pain . Moreover , a recent , large , whole-genome sequencing study of an Icelandic population demonstrated that individuals deficient for FAM173B were healthy , suggesting that targeting FAM173B may be feasible [65] . The requirement of methyltransferase activity of FAM173B in chronic pain development demonstrates that inhibiting FAM173B activity is a potential strategy to inhibit chronic pain . It will be important to identify the substrate ( s ) that is/are methylated by FAM173B to modulate mitochondrial functioning , including mitochondrial respiration , ΔΨm , and mitochondrial superoxide production in sensory neurons . The GWAS pointed to a role of FAM173B in chronic widespread pain , and our findings show that FAM173B plays a critical role in inflammatory and neuropathic pain . Currently , no animal models exist for chronic widespread pain . However , chronic widespread pain may have features of both inflammatory and neuropathic pain [66–70] . Therefore , our data indicating that FAM173B is involved in inflammatory and neuropathic pain pathways are likely to also have relevance for chronic widespread pain . Further studies are required to develop animal models of chronic widespread pain and test for the role of FAM173B activity in these models before clinical translation to chronic widespread pain patients should be considered . We show here that sensory neuron FAM173B methyltransferase activity causes the engagement of spinal microglia in a model of transient inflammatory pain . The contribution of microglia to persistent pain states is well established [7 , 10] , and several neuron-derived signals contributing to spinal cord microglia activation in persistent pain models have been identified , including fractalkine , ATP , monocyte chemoattractant protein 1 ( MCP1 ) , colony-stimulating factor 1 , and several neurotransmitters [6 , 11 , 12] . However , the molecular determinants in sensory neurons that trigger these cells to release substances to engage microglia are not well known . Here , we show that FAM173B methyltransferase activity in sensory neurons determines whether spinal cord microglia are engaged during peripheral inflammatory conditions in vivo . In vitro , the expression of FAM173B in sensory neurons promoted the release of glial cell–activating factors in an ROS-dependent manner after stimulation of sensory neurons with the proinflammatory cytokine TNFα . In conclusion , we propose that the mode of action by which FAM173B promotes chronic pain is through its lysine-specific methyltransferase activity in mitochondria , promoting ROS production in sensory neurons , resulting in glial cell engagement . These data provide a conceptual framework to explain a potential role of FAM173B as a chronic pain protein in humans and open the possibility for inhibitors of FAM173B methyltransferase activity to treat chronic pain .
All experiments were performed in accordance with international guidelines and approved by the experimental animal committee of University Medical Center Utrecht ( 2012 . I . 05 . 068 , 2014 . I . 06 . 042 ) or approved by the national Central Authority for Scientific Procedures on Animals ( CCD ) and the local experimental animal welfare body ( AVD115002015323 ) . Mice were maintained in the animal facility of the University of Utrecht . Experiments were conducted using both male and female ( aged 8–12 weeks ) C57BL/6 mice ( Harlan Laboratories , Indianapolis , IN , US ) because we did observe not overt sex differences during pain behavior measurements . Mice were housed in groups under a 12:12 light dark cycle , with food and water available ad libitum . The home cages contained environmental enrichments , including tissue papers and shelter . Mice were acclimatized for at least 1 week prior to the start of experiment . Sample sizes were calculated with power analysis at the time of the design of experiments . Mice received an intraplantar injection unilateral or in both hind paws of 5 μl λ-carrageenan ( 1% w/v , Sigma-Aldrich , St . Louis , MO , US ) to induce transient inflammatory pain [27] or 20 μl CFA ( Sigma-Aldrich , St . Louis , MO , US ) to induce persistent inflammatory pain [29] . SNI was performed as described previously [30 , 71] . Heat withdrawal latency times were determined using the Hargreaves test ( IITC Life Science , Woodland Hills , CA , US ) [72 , 73] . Mechanical thresholds were determined using the von Frey test ( Stoelting , Wood Dale , IL , US ) with the up-and-down method as we described [72 , 74] . Changes in weight bearing were evaluated using a dynamic weight bearing ( DWB ) apparatus ( Bioseb , Vitrolles , France ) as described [75] . The weight bearing of the affected paw was calculated as ratio of the weight between the affected paw and total weight and expressed relative to baseline . To assess persistent nonevoked pain behavior , we used the CPP test as described previously [34 , 35] . In short , CPP ( Stoelting , Wood Dale , IL , US ) was calculated by subtracting the mean time spent in the white room during preconditioning ( days 1 and 2 ) from the time spent in the white room ( day 5 ) after 2 days of conditioning ( day 3–4 ) with intraperitoneal injections of gabapentin ( 100 mg/kg , Sigma-Aldrich , St . Louis , MO , US ) as has been described before . CPP was applied 1 month after induction of a transient inflammation , and hyperalgesia was followed prior to CPP using Hargreaves and Von Frey tests . In experiments in which mice received intraplantar injections , latency times and 50% thresholds of left and right paws were considered as an independent measure , while in experiments with intrathecal or intraperitoneal drug administration , the average of the left and right paw were considered as an independent measure . To minimize bias , animals were randomly assigned to the different groups prior to the start of experiment , and all experiments were performed by experimenters blinded to treatment . After pain behavior assessments , mice were brought back to their home cages to minimize discomfort . At the end of the experiments , mice were euthanized by cervical dislocation . Full-length mFam173b ( NM_ 026546 . 1 ) and hFAM173B ( NM_199133 . 3 ) were cloned into several vectors , including pAcGFP-N1 , pIRES2-AcGFP1 , bacterial expression vector pET28a , and pCMV6 containing a myc-tag at the C-terminal of human or mouse FAM173B ( Origene , Rockville , MD , US ) . pIRES2-AcGFP vectors were used for functional experiments , and GFP expression was used to verify successful transfection . The pCMV6 and pAcGFP-N1 vectors were used for identification of cellular and subcellular localization of FAM173B , and pET28a was used for the production of recombinant FAM173B in Escherichia coli . We generated a bicistronic HSV construct by cloning hFAM173B or hFAM173B-D94A in which residue ( Asp94 ) is mutated to alanine in order to generate enzymatically inactive protein [38] , under control of the α4 promotor and with GFP under control of the α22 promoter [27] . Control HSV-EV only expresses GFP . HSV was produced as previously described [76] . Mice were inoculated twice ( day −3 and day −1 prior to carrageenan or at day 5 and 7 after CFA ) with 2 . 5 μl of 1 . 4 × 107 pfu/ml ( intraplantar ) or 5 μl 5 × 106 pfu/ml ( intrathecal ) . For behavioral analysis , mice received an intraperitoneal injection ( day 5 after carrageenan ) with 100 μl PBN ( 100 mg/kg , Sigma-Aldrich , St . Louis , MO , US ) . For spinal cord analysis , mice received 2 PBN injections ( 2 hours apart ) at 1 month after carrageenan . Spinal cords were collected 2 hours after the last PBN administration . Intrathecal injections ( 5 μl ) with minocycline ( 6 μg/μl , Sigma-Aldrich , St . Louis , MO , US ) , neutralizing TNFα antibody ( 20 μg/μl , Enbrel ) , and ( Cy3-labeled , set1 ) ODN ( 3 μg/μl day 5 , 6 , 7 , 9 , and 10 , Sigma Aldrich , St . Louis , MO , US ) were performed under light isoflurane anesthesia as described [72 , 77] . The following phosphorothioated ODN sequences that specifically target mFam173b and not hFAM173B were used: Set1Fam173b:CCCgCCTgTCTTTCTTCCTCMM:CgCCTCCgTTCCTTTCTCCTSet2Fam173b:gggTCCTCTTCTgTgTCgCAMM:gTgCTCgTCTTgCCgACgCT HEK293 and mouse neuroblastoma N2A cells were kept in Dulbecco’s Modified Eagle medium ( DMEM ) with Glutamax-l containing 4 . 5 g/L D-Glucose , pyruvate , and 10% fetal calf serum . FAM173B expression was down-regulated ( 100 μM ODN ) or overexpressed with plasmids as described above using Lipofectamin 2000 ( Life Technologies , Waltham , MA , US ) according to manufacturer’s instructions . For measuring ΔΨm , the cells were incubated for 20 to 30 minutes with 50 nM MitoTrackerRedCMXROS ( Life Technologies , Waltham , MA , US ) or 50 nM TMRM ( Sigma-Aldrich , St . Louis , MO , US ) 2 days after transfection and following manufacturer’s instructions . Cells were fixed with 4% paraformaldehyde ( PFA ) after MitoTrackerRedCMXROS or directly imaged without fixation ( TMRM experiments ) . For the TMRM experiments , fluorescence was captured before and after the addition of the respiratory uncoupler FCCP that abolishes ΔΨm without affecting cell membrane potential [39] . The ΔTMRM fluorescence was calculated by measuring difference in the TMRM fluorescence before and after FCCP administration . Fluorescence was captured using AxioCAM MRm from Zeiss Axio Observer microscope and analyzed with ImageJ software . DRG were collected , and primary sensory neurons were cultured as described [25] . Twenty-four hours after plating , sensory neuron cultures were inoculated with HSV ( 10 , 000 pfu ) for 3 days . The antimitotic fluoro-deoxyuridine ( FDU; 13 . 3 μg/ml , Sigma-Aldrich , St . Louis , MO , US ) was added to inhibit satellite glial cell growth in the neuronal cultures . Sensory neurons were stimulated with 100 ng recombinant TNFα ( Peprotech , Rocky Hill , NJ , US ) with or without PBN ( 2 mM , Sigma-Aldrich , St . Louis , MO , US ) . Six hours after neuronal TNFα stimulation ( +/− PBN ) , the cultures were washed 3 times with media ( DMEM ) , and new media was added; after 15 hours , supernatants were collected . The collected supernatants were diluted 1:1 with DMEM and added to spinal microglia cultures for 24 hours . Spinal microglia were cultured as described previously [78] . After collection of the supernatants , IL6 and TNFα contents were determined by ELISA according to manufacturer’s protocol ( R&D Systems , Minneapolis , MN , US ) . The detection limit of IL6 was 15 pg/ml and of TNFα 31 pg/ml . HEK293 and N2A cells were grown in 6-well plates and transfected with pCMV6-FAM173Bmyc as described above . The cells were treated as described previously [79] . Briefly , cells were chemically fixed using 2% formaldehyde ( FA ) , 0 . 2% glutaraldehyde in 0 . 1 M phosphate buffer pH 7 . 4 ( Pi ) for 2 hours , and stored overnight in 1% FA in Pi . After rinsing with PBS ( 3 times ) and PBS 0 . 15 M glycine , a 1% gelatin solution was put on the cells , and the cells were removed from the Petri dish using a cell scraper , transferred to an Eppendorf vial , and spun down . The 1% gelatin was removed , and the cells were suspended in 12% gelatin at 37°C . After 10 min , the cells were spun down and the gelatin was allowed to solidify at 0°C . Small ( 0 . 5 × 0 . 5 × 0 . 5 mm ) blocks were prepared and transferred to 2 . 3 M sucrose . After overnight infiltration of sucrose in a rotator , the blocks were mounted on specimen holders and frozen in liquid nitrogen . Ultrathin sections ( 70 nm ) were prepared on a Leica UC7/FC7 ( Leica , Vienna , Austria ) at −120°C . Immunolabeling was performed with Rabbit anti-GFP ( Acris Antibodies , Herford , Germany ) and protein A-Gold ( CMC , Utrecht , the Netherlands ) . The immunogold labeled sections were examined with a Tecnai 12 or 20 ( FEI , Eindhoven , the Netherlands ) . In vivo , DHE—to measure ROS formation ( 50 μM , 5 μl , Life technology , Waltham , USA ) —or MitoTrackerRedCM-H2XROS , which fluoresces upon oxidation—to measure mitochondrial superoxide production ( 10 μl of 100 μM , Life Technologies , Waltham , MA ) [80]—was injected intrathecal respectively at day 4 or day three/six after intraplantar carrageenan administration . Twenty-four hours later , mice were perfused with PBS and 4% PFA as described below , and DRGs were collected [18] . DHE and MitoTrackerRedCM-H2XROS fluorescence were analyzed in small-diameter neurons <25 μm and medium- and/or large-diameter neurons >25 μm . For ROS or mitochondrial superoxide production measurements in vitro , primary sensory neurons or N2A were incubated with 10 μM DHE or 5 μM MitoSoX ( Life Technologies , Waltham , MA ) in HBSS for 20 minutes . After HBSS washes , cells were fixed with 4% PFA after DHE incubations or directly imaged without fixation ( MitoSox experiments ) . Fluorescence was captured using AxioCAM MRm from Zeiss Axio Observer microscope and analyzed with ImageJ software . Mice were deeply anesthetized with an overdose of sodium pentobarbital and transcardially perfused with PBS followed by 4% PFA , and spinal cords and DRGs were collected . Tissues were postfixed , cryoprotected in sucrose , embedded in OCT compound ( Sakura , Zoeterwoude , the Netherlands ) , and frozen at −80°C . Cryosections ( 10 μm ) of lumbar DRG and lumbar spinal cord segments L3–L5 were stained with anti-Iba1 ( 1:500 , Wako Chemicals , Wako , Japan ) . DRGs were stained with anti-NF200 ( 1:200 , Millipore , Bellerica , MA , US ) , biotinylated anti-IB4 ( 1:25 , Vector Laboratories , Burlingame , CA , US ) , anti-F4/80 ( 1:500 , Cedarlane , Burlington ) , and anti-GFAP ( 1:2000 , Dako , Santa Clara , CA , US ) . N2A cells were stained with anti-PD1 ( 1:100 , Enzo Life Sciences , Farmingdale , NY ) and anti-pGM130 ( 1:100 , BD Transduction Laboratories , San Jose , CA ) . Primary sensory neurons were stained with anti-FAM173B ( 1:500 , biorbyt ) and anti-COXIV ( 1:100 , ThermoFisher Scientific , Waltham , MA ) . For the DRG , sciatic nerves , and hind paw stainings for FAM173B ( 1:500 , Biorbyt , Cambridge , UK ) , GFP ( 1:3000 , Abcam , Cambridge , UK ) , and peripherin ( 1:100 , Sigma Aldrich , St . Louis , MO ) , tissues were fresh frozen , cut , and post-fixed in PFA prior for staining . Stainings were visualized by using alexafluor 488- ( streptavidin ) or 594-conjugated secondary antibodies . Nuclei were stained with 4′ , 6-diamidino-2-phenylindole ( DAPI ) . Photographs were captured with a confocal laser scanning microscope LSM700 ( colocalization experiments ) or with a Zeiss Axio Observer microscope ( Zeiss , Oberkochen , Germany ) using identical exposure times for all slides within one experiment . Fluorescence intensity was analyzed with ImageJ software . Homo sapiens FAM173A ( NP_076422 . 1 ) and FAM173B ( NP_954584 . 2 ) , Mus musculus Fam173a ( NP_663385 . 2 ) and Fam173b ( NP_080822 . 1 ) , and the homolog of FAM173 proteins ( FAM173hom ) from the archaeal Sulfolobus islandicus ( gi|227827841 ) were used for the alignment . The alignment was generated using the MUSCLE algorithm embedded in Jalview [81 , 82] , and prediction of protein secondary structure was performed with Jpred 3 [83] . Human full-length FAM173B , WT FAM173BΔ55 ( without the putative transmembrane domain to avoid the formation of inclusion bodies ) , and FAM173BΔ55-D94A ( enzymatically inactive ) were cloned into pET28a and expressed as N-terminally hexahistidine tagged proteins in E . coli BL21-CodonPlus ( DE3 ) -RIPL cells ( Agilent , Santa Clara , CA ) and purified using nickel-nitrilotriacetic acid-agarose ( Qiagen , Hilden , Germany ) according to manufacturer’s instructions and as described [38] . Eluted proteins were buffer exchanged [38] , and protein purity was assessed by SDS-PAGE and Coomassie blue staining . Protein concentrations were measured using the Pierce BCA protein assay kit ( Thermo Fisher Scientific , Waltham , MA ) . Methyltransferase reactions contained 10 μg of homopolymers or equivalent amounts of cell extracts from adenosine dialdehyde ( AdOx ) -treated HEK293 cells [84] , [3H]-SAM ( 2 μCi ) , and recombinant hFAM173B ( 100 pmol ) in 50-μl reactions and were incubated for 1 hour at 37°C , as described [49 , 85] . Radioactivity in 10% trichloroacetic acid precipitated material was measured by scintillation counting , or proteins were resolved by SDS-PAGE and subjected to fluorography [49] . Isolation of mitochondria from N2A cells was performed with the Mitochondria Isolation Kit for Cultured Cells ( ThermoFisher Scientific , Waltham , MA ) according to manufacturer’s protocol . Protein concentrations of the total cell lysates or mitochondrial/cytosol fractions were determined using a Bradford assay ( Bio-Rad , Hercules , CA ) . Protein samples ( 20 μg ) were separated by 12% SDS-PAGE and transferred to a PVDF membrane ( Immobilon-P , Millipore , Bellerica , MA ) . Membrane was stained with 1:1000 goat anti-FAM173B , 1:1000 mouse anti-COXIV ( Invitrogen , Paisley , UK ) , or 1:1000 goat anti–β-actin , followed by incubation with 1:5000 donkey anti goat-HRP ( others all Santa Cruz Biotechnology , Santa Cruz , CA ) . Specific bands were visualized by chemiluminescence ( ECL , Advansta , Menlo Park , CA ) and imaging system Proxima ( Isogen Life Sciences , De Meern , the Netherlands ) . Total RNA from freshly isolated DRGs and spinal cords was isolated using TRizol and RNeasy mini kit ( Qiagen , Hilden , Germany ) . cDNA was synthesized using Reverse Transcriptase ( Bio-Rad , Hercules , CA ) . Quantitative real-time PCR reaction was performed with an I-cycler iQ5 ( Bio-Rad , Hercules , CA ) as described [22] . We used the following primers: mFam173bforward:TggTgTgCCCCAgATgATreverse:TgCCCTCTCCAgTggTgTTNFαforward:gCggTgCCTATgTCTCAgreverse:gCCATTTgggAACTTCTCATCIL1βforward:CAACCAACAAgTgATATTCTreverse:gATCCACACTCTCCAgCTgCAGFAPforward:ACAgACTTTCTCCAACCTCCAgreverse:CCTTCTgACACggATTTggTIba1forward:ggATTTgCAgggAggAAAAgreverse:TgggATCATCgAggAATTgBDNFforward:CACATTACCTTCCAgCATCTreverse:ACCATAgTAAggAAAAggATggCCL2forward:ggTCCCTgTCATgCTTCTgreverse:CATCTTgCTggTgAATgAgTAgGAPDHforward:TgAAgCAggCATCTgAgggreverse:CgAAggTggAAgAgTgggAg , HPRTforward:TCCTCCTCAgACCgCTTTTreverse:CCTggTTCATCATCgCTAATC Data were normalized for GAPDH and HPRT expression . cDNA was synthesized from 1 μg total RNA ( Clontech , Mountain View , CA ) , and PCR was performed using Phusion polymerase ( ThermoFisher Scientific , Waltham , MA ) following manufacturing instructions . Human and mouse FAM173B were detected in a tissue panel ( Clontech , Mountain View , CA ) using the following primers: hFAM173Bforward:gTAgCCACgCCgTTTgTAACreverse:CATCATCTgAggCACACCgAβ−actinforward:CCTggCACCCAgCACAATreverse:GggCCggACTCgTCATACTmFam173bforward:TggTgTgCCCCAgATgATreverse:TgCCCTCTCCAgTggTgTHPRTforward:TCCTCCTCAgACCgCTTTTreverse:CCTggTTCATCATCgCTAATC All data are presented as mean ± SEM and were analyzed with GraphPad Prism version 7 . 02 using unpaired two-tailed t tests , one-way or two-way ANOVA , or as appropriate two-way repeated measures ANOVA , followed by post-hoc Holm-Sidak multiple comparison tests . A P value less than 0 . 05 was considered statistically significant , and each significance is indicated with * for P < 0 . 05 , ** for P < 0 . 01 , and *** for P < 0 . 001 .
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Pain is an evolutionarily conserved physiological phenomenon necessary for survival . Yet , pain can become pathological when it occurs independently of noxious stimuli . The molecular mechanisms of pathological pain are still poorly understood , limiting the development of highly needed novel analgesics . Recently , genetic variations in the genomic region encoding FAM173B—a functionally uncharacterized protein—have been linked to chronic pain in humans . In this study , we identify the role and function of FAM173B in the development of pathological pain . We used genetic , biochemical , and behavioral approaches in mice to show that FAM173B is a mitochondrial lysine methyltransferase—a protein that transfers methyl group to donor proteins . By genetically silencing or overexpressing FAM173B in sensory neurons , we showed that FAM173B methyltransferase activity promotes the development of chronic pain . In addition , we discovered that FAM173B methyltransferase activity in the mitochondria of sensory neurons promotes chronic pain via a pathway that depends on the production of reactive oxygen species and on the engagement of spinal cord microglia—engulfing cells of the central nervous system . These data point to an essential role of FAM173B in the regulation of pathological pain .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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2018
|
Identification of FAM173B as a protein methyltransferase promoting chronic pain
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Helminths are highly prevalent metazoan parasites that infect over a billion of the world’s population . Hosts have evolved numerous mechanisms to drive the expulsion of these parasites via Th2-driven immunity , but these responses must be tightly controlled to prevent equally devastating immunopathology . However , mechanisms that regulate this balance are still unclear . Here we show that the vigorous Th2 immune response driven by the small intestinal helminth Trichinella spiralis , is associated with increased TGFβ signalling responses in CD4+ T-cells . Mechanistically , enhanced TGFβ signalling in CD4+ T-cells is dependent on dendritic cell-mediated TGFβ activation which requires expression of the integrin αvβ8 . Importantly , mice lacking integrin αvβ8 on DCs had a delayed ability to expel a T . spiralis infection , indicating an important functional role for integrin αvβ8-mediated TGFβ activation in promoting parasite expulsion . In addition to maintaining regulatory T-cell responses , the CD4+ T-cell signalling of this pleiotropic cytokine induces a Th17 response which is crucial in promoting the intestinal muscle hypercontractility that drives worm expulsion . Collectively , these results provide novel insights into intestinal helminth expulsion beyond that of classical Th2 driven immunity , and highlight the importance of IL-17 in intestinal contraction which may aid therapeutics to numerous diseases of the intestine .
Human intestinal helminths infect more than 1 billion of the world’s population , often affecting the most deprived communities [1] . These parasites are one of the most prevalent Neglected Tropical Diseases worldwide bringing huge morbidities to the host population; sub-Saharan Africa alone is estimated to lose 2 . 3 million disability-adjusted life-years annually [2] . Notwithstanding this hugely successful colonisation , we have evolved numerous Th2-driven mechanisms of parasite expulsion [3–8] , which must be tightly regulated to avoid potential immunopathology , such as uncontrolled fibrosis and barrier dysfunction , as seen in ulcerative colitis [9] . The small intestinal helminth Trichinella spiralis is the leading causative agent of trichinosis , which globally exhibits burdens of around 12 million [10] , equivalent to kinetoplastid-caused infections such as Leishmania sp . and Trypanosoma cruzi [11] . The life cycle consists of the release of larvae from nurse cells following pepsin digestion of contaminated meat in the stomach , prior to migration and swift development into adults in the small intestine . Male and female adults mate to produce new born larvae which migrate via the blood and lymph to the striated muscle where they form new nurse cells . Mouse models have demonstrated that infection produces a strong CD4+ T-cell [12 , 13] and type 2 cytokine [14–16] driven transient inflammation culminating in worm expulsion around day 15 post-infection ( p . i . ) in C57BL/6 mice . IL-9 driven mastocytosis [17] is key in T . spiralis expulsion [18–20] , driving the degradation of epithelial tight junctions via the release of mast cell proteases during degranulation [21 , 22] . The resulting increase in luminal fluid , works in combination with Th2 driven alterations of enhanced intestinal propulsive activity . IL-13 and IL-4 , signalling via signal transducer and activator of transcription factor 6 ( STAT6 ) [23] on smooth muscle cells [24] , allow jejunal muscle hypercontractility [23–25] . Despite the potential for immunopathology in terms of intestinal barrier weakening and exposure to luminal commensals , in combination these pathways produce the “weep and sweep’ mechanism [26] , to drive out the enteric stage of infection with only short-lived pathology . In comparison to other helminths , T . spiralis infection produces a robust Th2 response with evident pathology in terms of weight loss prior to intestinal worm expulsion [27] , while the following encapsulation of new born larvae within the striated muscle is associated with a general malaise . Previous work has demonstrated the importance of the pluripotent cytokine TGFβ in the chronic muscular phase of the parasite life cycle [28] , but the role of this complex cytokine during the intestinal phase remains unclear . Given the fundamental importance of TGFβ in regulating many aspects of T-cell biology [29] we chose to investigate the mechanistic function of TGFβ signalling in regulating the potential pathological immune response during T . spiralis enteric infection . Here , we demonstrate that mice infected with T . spiralis , display enhanced TGFβ signalling in intestinal CD4+ T-cells which drives Th17 induction , as opposed to an increased regulatory T-cell ( Treg ) response . We find that the expression of integrin αvβ8 on dendritic cells ( DCs ) , previously shown to be key in activating TGFβ and maintaining Tregs during intestinal homeostasis [30 , 31] , is essential for the induction of TGFβ signalling in CD4+ T-cells and the generation of Th17 cells during infection . Importantly , mice lacking integrin αvβ8 on DCs ( Itgb8 ( Cd11c-cre ) ) have a delayed ability to expel the intestinal stage of the infection , despite an equivalent Th2 response to wild-type controls . Utilising the DEREG system for Treg ablation [32] demonstrates an essential requirement of Tregs for parasite expulsion , yet the adoptive transfer of Tregs into Itgb8 ( Cd11c-cre ) mice suggests that the reduced Treg level seen is not responsible for the delayed parasite expulsion in this model . Instead , we show that the Th17 response promotes intestinal contractility and the “sweep” mechanism of parasite expulsion . Our results therefore provide novel insights into the role of TGFβ during intestinal helminth infection , contributing greater understanding to mechanisms of helminth expulsion and potentially enteric diseases encompassing muscle hypercontractility .
Expulsion of the small intestinal helminth T . spiralis is associated with a strong and acute T-helper 2 ( Th2 ) CD4+ T-cell response , around one week p . i . in mice ( [12–16] and S1A Fig ) . Mice develop a biphasic morbidity in parallel to the enteritis and myositis of infection [27] , indicating a need to regulate this strong inflammatory response . We investigated the mechanistic role of the pluripotent cytokine TGFβ , which regulates many aspects of innate and adaptive immunity including T-cells [29] , during the potential pathological immune response during T . spiralis enteric infection . Wild-type C57BL/6 mice were infected with 300 T . spiralis larvae and followed throughout the time course of infection . We analysed parasite-specific cytokine production from mesenteric lymph node ( mLN ) cell preparations and saw a significant increase in TGFβ secretion in parallel to enhanced Th2 responses ( IL-13 , IL-9 and IL-4 production ) at day 6 p . i . ( Fig 1A and S1A Fig ) . Interestingly , in contrast to the reduction in IL-4 , IL-9 and IL-13 cytokine release later in infection ( S1A Fig ) , we saw a stronger , secondary peak of TGFβ at day 12 p . i . ( Fig 1A ) . As TGFβ is produced as a latent cytokine requiring activation , we examined phosphorylation of Smad 2/3 ( p-Smad2/3 ) , which is the initial signalling event triggered by engagement of active TGFβ with its receptor . We saw significantly increased p-Smad2/3 levels in CD4+ T cells at day 13 p . i . in the small intestinal lamina propria ( SILP ) intestinal niche of the parasite ( Fig 1B and 1C ) , indicating enhanced activation of TGFβ . TGFβ signalling in CD4+ T-cells can result in the induction of Th17 [33–35] , Th9 [36 , 37] or peripheral Treg subsets [38] , depending on co-stimulatory signals and the surrounding cytokine milieu . Although we did not see any significant increase in IL-9 secretion at day 12 p . i . ( S1A Fig ) , nor increase in the percentage of IL-9 expressing mLN CD4+ T-cells ( S1B Fig ) or Foxp3 expression in small intestinal CD4+ T-cells around this time-point ( S1C and S1D Fig ) , we did see a significant increase in IL-17 secretion at day 12 p . i . in parallel to the secondary peak of TGFβ production ( Fig 1D ) . This increase in IL-17 production was also concomitant with a significant increase in IL-6 ( S1A Fig ) , which can synergise with TGFβ to drive Th17 cell induction [39] . Indeed , on performing intracellular flow cytometry we identified CD4+ cells as the source of the IL-17 produced during this infection ( Fig 1E ) , with additional gating showing significant increases in IL-17 seen within the CD4+CD3+ T-cell gated population during infection ( Fig 1F ) . These data indicate that TGFβ signalling in CD4+ T-cells is induced during the enteric stage of T . spiralis infection and is associated with Th17 cell induction subsequent to the classical Th2 response . We next sought to determine the mechanisms responsible for enhanced TGFβ signalling during T . spiralis infection . The requirement for the activation of latent TGFβ prior to function [40] led us to investigate the potential for integrin αvβ8 , a key activator of latent TGFβ in the intestine expressed by dendritic cells ( DCs ) [30 , 31 , 41] , to be responsible for the enhanced signalling seen in CD4+ T-cells . To this end , we analysed T-cell responses following infection with 300 T . spiralis larvae in mice lacking integrin αvβ8 on DCs ( Itgb8 ( CD11c-Cre ) mice [30] ) and wild type littermate controls . We found that the increase in TGFβ signalling observed in CD4+ T-cells during T . spiralis infection was significantly reduced in Itgb8 ( CD11c-Cre ) mice , with pSmad2/3 levels remaining similar to those observed in uninfected mice ( Fig 2A ) . Interestingly , this lack of TGFβ signalling in CD4+ T-cells did not affect the classical Th2 , Th9 nor Th1 immune cytokine responses during the time-course of infection , with no significant difference observed in parasite specific IL-13 , 4 , 9 ( Fig 2B ) and IFNγ ( S2A Fig ) production from mLN antigen restimulation . This was also reflected in the similar IgG response seen at day 18 post-infection ( S2B Fig ) , which is a key indicator of Th1/2 balance , and IL-9 expression in mLN CD4+ T-cells at day 13 post-infection ( S2C Fig ) . However , IL-17 production was significantly reduced at day 13 p . i . , in both mLN restimulations ( Fig 2B ) as well as from small intestinal lamina propria CD4+ T-cells ( Fig 2C ) , which were also observed to produce similar IL-13 levels ( Fig 2C ) . Indeed , beyond the previously reported initial baseline differences in intestinal Th17 cells in Itgb8 ( CD11c-Cre ) mice ( [30] and ( Fig 3D ) ) , total small intestinal lamina propria IL-17+ CD4+ T-cell numbers failed to significantly increase following infection at day 13 p . i . in Itgb8 ( CD11c-Cre ) mice as compared to wild-types ( Fig 2D ) . Interestingly , we also observed a significant reduction in small intestinal lamina propria Foxp3+ regulatory T-cells at rest in the Itgb8 ( CD11c-Cre ) mice , with neither wild-type or Itgb8 ( CD11c-Cre ) mice Treg numbers altering during enteric T . spiralis infection ( Fig 2E ) . Thus , during enteric T . spiralis infection , enhanced TGFβ activation by integrin αvβ8 on DCs is important in triggering infection-induced TGFβ signalling pathways in CD4+ T-cells , driving Th17 cells , and maintaining Treg numbers during homeostasis . Strikingly , and despite the maintained Th2 and Th9 response in Itgb8 ( CD11c-Cre ) mice , we observed a significant delay in worm expulsion and exacerbated weight loss ( Fig 2F and 2G ) following infection , as compared to wild-type mice . This delay was not associated with differences in other proposed mechanisms involved in helminth expulsion , with no significant difference in crypt/villus architecture ( S2D Fig ) , goblet cell hyperplasia [42] ( S2E Fig ) , mastocytosis [18–20] and associated MMCP-1 production [21 , 22] ( S2F and S2G Fig ) or RELMβ expression [43] ( S2H Fig ) between wild-type and Itgb8 ( CD11c-Cre ) mice . Collectively these data indicate that despite the maintenance of a Th2 response in Itgb8 ( CD11c-Cre ) mice , TGFβ activation by integrin αvβ8 on DCs is essential for triggering TGFβ signalling pathways in CD4+ T-cells and promoting parasite expulsion . We next focussed on uncovering the mechanisms responsible for the delayed expulsion of the small intestinal helminth T . spiralis from mice lacking the TGFβ activating integrin αvβ8 on DCs . Given the stark baseline reduction in small intestinal Foxp3+ Tregs in Itgb8 ( CD11c-Cre ) mice ( Fig 2E ) , we utilised the DEREG mouse model , which allows specific ablation of Foxp3+ Tregs by injection of diphtheria toxin [32] , to directly test the functional role of Foxp3+ Tregs during infection . DEREG mice treated with diphtheria toxin had successful complete depletion of Foxp3-GFP+ cells during the time course of the experiment , although we did see grow back of non-GFP Foxp3+ cells ( S3A Fig ) , which have previously been demonstrated to possess no inhibitory function [44] . We found that worm burdens in DEREG mice recapitulated the delayed expulsion seen in Itgb8 ( CD11c-Cre ) mice , with significantly increased worm burdens observed at day 7 and 15 p . i . ( Fig 3A ) . Furthermore , as in Itgb8 ( CD11c-Cre ) mice , a heightened weight loss was apparent , but this took on differing kinetics , with mice presenting with sustained significant weight loss from day 4 p . i . in DEREG mice versus day 13 p . i . in Itgb8 ( CD11c-Cre ) mice ( Fig 3B versus Fig 2G ) . Moreover , this weight loss in infected DEREG mice did not recede , despite attempts to rehydrate the animals with saline , resulting in mice reaching the threshold for humane end-point and the cessation of the experiments at day 15 p . i . ( Fig 3B ) . To try and decipher reasons behind this extreme morbidity , we examined parasite-specific cytokine responses following mLN antigen restimulation . In stark contrast to Itgb8 ( CD11c-Cre ) mice , we observed significant increases in IL-4 production at day 7 p . i . ; while IL-13 and IFNγ increased at day 15 p . i . ( Fig 3C ) . Interestingly no differences were seen in parasite–specific IgG antibody nor MMCP-1 production , as compared to untreated control mice , indicating no overall imbalance in the Th1/Th2 paradigm ( S3B and S3C Fig ) . Recent publications have discovered an essential role for Foxp3+ Tregs in eliminating the small intestinal helminth Heligmosoides polygyrus , with Treg depletion associated with delayed worm expulsion following an uncontrolled “cytokine storm” [45] . We therefore looked at other pro-inflammatory cytokines and we did indeed see a significant increase in IL-6 at day 15 p . i . ( Fig 3C ) . Importantly , we did not see the reduction in IL-17 later in infection in DEREG mice , as seen in Itgb8 ( CD11c-Cre ) mice ( Fig 2B vs . Fig 3C ) . Despite the clear evidence demonstrating a complete lack of Tregs could mediate worm expulsion and weight loss during T . spiralis infection , we next asked if the adoptive transfer of Tregs to Itgb8 ( CD11c-Cre ) mice was sufficient to rescue worm expulsion kinetics . Despite the successful restoration of small intestinal lamina propria Foxp3+ cells ( S3D and S3E Fig ) resulting in augmented percentage weight ( Fig 3D ) , we saw no alteration in IL-13 or IL-17 production in Treg treated Itgb8 ( CD11c-Cre ) mice ( Fig 3E and 3F ) , culminating in similar delayed expulsion as in untreated Itgb8 ( CD11c-Cre ) mice ( Fig 3G ) . Collectively , these data suggest Foxp3+ Tregs are an important cell type in the context of T . spiralis infection and are required for efficient expulsion of small intestinal helminths via inhibiting runaway inflammation , as well as modulating weight loss pathology . However , given the increased Th1 and Th2 cytokines but maintenance of IL-17 production in the DEREG system and the failure of Treg adoptive transfer to rescue Itgb8 ( CD11c-Cre ) delayed worm expulsion , this mechanism seems not to be solely responsible for the phenotype displayed in T . spiralis infected Itgb8 ( CD11c-Cre ) mice . Given that the adoptive transfer of Tregs into Itgb8 ( CD11c-Cre ) mice restored weight loss kinetics but not worm expulsion , coupled with the strong Th2 response and accompanying effector mechanisms seen in infected Itgb8 ( CD11c-Cre ) mice , we next examined a role for the altered Th17 cell population during this infection . We hypothesised that IL-17 may influence muscle hypercontractility rather than mastocytosis induced luminal fluid increases , hence the “sweep” but not the “weep” aspect during expulsion of the enteric phase of T . spiralis . To investigate the individual importance of IL-17 in T . spiralis infection , we blocked IL-17 from day 7 p . i . in C57BL/6 mice via antibody depletion . Although we saw no significant difference in weight or worm burdens when IL-17 was depleted from day 7 p . i . ( Fig 4A and 4B ) , we did see a significant reduction in in vivo transit time in the small intestine , as measured by the transit of orally gavaged carmine dye ( Fig 4C and 4D ) . Importantly , the depletion of IL-17 did not impinge on the CD4+ mLN T-cell production of IL-13 ( or IFNγ ) ( S4A and S4B Fig ) , suggesting that alterations in transit time were possibly due to the absence of IL-17 , rather than a follow-on effect of reduced Th2 cytokines known to induce small intestinal hypercontractility [23 , 24] . We next isolated jejunal smooth muscle and confirmed the expression of the IL-17ra via qPCR both at rest and following infection with T . spiralis ( Fig 4E ) . This suggested the potential for IL-17 to directly influence intestinal smooth muscle contraction . To investigate this hypothesis , we first incubated isolated jejunal strips of intestine from wild-type mice with or without rIL-17 prior to assessing longitudinal muscular tension ex vivo generated in response to stimulation with carbachol . Treatment with rIL-17 produced a significant increase in tension ( Fig 4F ) , indicating IL-17 could promote tension and therefore potentially drive parasite expulsion . We next asked what downstream pathways could be responsible for transposing the IL-17 signal , with COX-2 and STAT6 pathways previously being shown to drive TGFβ and IL-4/13 intestinal contraction respectively , following T . spiralis infection [24 , 46] . To this end , we repeated ex vivo contraction experiments with prior exposure to inhibitors for both pathways , but detected no alteration in the hypercontraction response to carbachol following rIL-17 incubation ( Fig 4G ) . Previous studies have demonstrated that Rho kinase signalling is emerging as an important mediator of intestinal smooth muscle contraction [47] , with IL-13 and TNFα driving smooth muscle contraction via the small GTPase , RhoA via STAT6 and NF-κβ signalling respectively [48] . We therefore targeted the RhoA downstream effector kinases via prior exposure to a ROCK pathway inhibitor , and observed an inhibition of the ability of IL-17 to produce significant hypercontraction in response to carbachol ( Fig 4G ) . Collectively , these data show that , although not solely sufficient for worm expulsion or altered weight loss , IL-17 has direct effects on small intestinal hypercontractility , acting via the ROCK signalling pathway , and could potentially be responsible for the delayed expulsion seen in T . spiralis infected Itgb8 ( CD11c-Cre ) mice . Given the role of IL-17 in driving small intestinal contraction , we tested whether the reduced levels of parasite specific IL-17 production seen in Itgb8 ( CD11c-Cre ) mice were responsible for delayed worm expulsion via a reduced small intestinal hypercontractility . To this end , we examined if we could rescue delayed expulsion in these mice via treatment with recombinant IL-17 . Treatment with rIL-17 from day 9 p . i . completely restored the weight loss kinetics ( Fig 5A ) to levels seen in wild-type mice . This rescue of weight loss following rIL-17 treatment was not associated with any changes in parasite-specific IL-4 , IL-13 or IFNγ cytokine production ( Fig 5B ) , nor in parasite specific IgG responses ( S5A Fig ) . Next , we examined isolated longitudinal muscle tension between jejunal samples from wild-type and Itgb8 ( CD11c-Cre ) mice . Although there was no differences in tension either at baseline nor following carbachol treatment in naïve mice ( S5B Fig and Fig 5C ) , following infection Itgb8 ( CD11c-Cre ) mice failed to significantly increase jejunal tension in response to stimulation with carbachol at day 13 p . i . , as seen in in wild-type infected mice ( Fig 5C and [23–25] ) . Moreover , the treatment of infected Itgb8 ( CD11c-Cre ) mice with rIL-17 rescued this muscular tension to wild-type levels ex vivo ( Fig 5C ) . Next , we examined in vivo contraction in the small intestine and despite no alteration at base line ( Fig 5E and S5C Fig ) , we saw significantly delayed transit time following infection in Itgb8 ( CD11c-Cre ) mice , which was again rescued via the addition of rIL-17 , but could not be restored by the adoptive transfer of Tregs ( Fig 5D and 5E ) . Strikingly , in parallel to this recued small intestinal contraction , treatment with rIL-17 from day 9 p . i . completely restored the worm burden kinetics in infected Itgb8 ( CD11c-Cre ) mice ( Fig 5F ) to levels seen in wild-type mice . In sum , these data indicate that TGFβ activation by integrin αvβ8 on DCs is essential for triggering TGFβ signalling pathways in CD4+ T-cells allowing the maintenance of Tregs and induction of Th17 cells during T . spiralis infection . Tregs play a key role in mediating weight loss and aiding helminth expulsion via inhibiting runaway inflammation , while Th17 produced IL-17 contributes to enhanced muscular “sweep” tension promoting parasite expulsion .
We have evolved immune driven mechanisms to allow the expulsion of intestinal helminths , with the “weep and sweep” supplied by increased intestinal epithelial permeability and muscle contraction [21–25] essential during T . spiralis infection . In most cases these expulsion mechanisms rely on Th2 cytokines resulting in minimal host damage indicating an essential role for regulation to avoid immunopathology; however the pathways and mechanisms involved remain unclear . Our data now indicate an essential role for TGFβ , activated via DC expressed integrin αvβ8 , in parasite expulsion via the maintenance of Tregs and induction of Th17 cells , as opposed to simply immuno-regulation . Using the small intestinal dwelling helminth T . spiralis , we observed increased TGFβ signalling in CD4+ T-cells and production of Th17 cells late in infection . Mechanistically , we find that enhanced TGFβ signalling in T-cells occurs via expression of the TGFβ-activating integrin αvβ8 on DCs and that DC-specific lack of this integrin results in increased weight loss and delayed worm expulsion , despite the occurrence of the “classical” Th2 response . The total ablation of Tregs , in the DEREG model , demonstrates a role for this cell in aiding helminth expulsion via inhibiting runaway inflammation , while their adoptive transfer into Itgb8 ( CD11c-Cre ) mice indicates a key role in mediating infection induced weight loss . Moreover , Itgb8 ( CD11c-Cre ) mice lack intestinal hypercontractility that can be rescued via treatment with recombinant IL-17 , fully restoring both weight loss and worm expulsion kinetics . We have therefore identified a novel , non-Th2 based , mechanistic pathway that could potentially be targeted to treat helminth infection and contractile diseases of the intestine . Previously , TGFβ signalling within T-cells has been shown to play an important role in downregulating Th2 responses via downregulation of the key transcription factor GATA-3 [49 , 50] . Indeed , we have previously shown that enhanced TGFβ signalling in T-cells during chronic Th1-induced Trichuris muris infection also occurs via expression of the TGFβ-activating integrin αvβ8 on DCs . Moreover the lack of this integrin on DCs completely protects mice from T . muris infection due to an enhanced protective Th2 response in this model of large intestinal infection [51] . However , here , we did not see any alteration in parasite-specific Th2 responses associated with delayed parasite expulsion , nor any increase in IFNγ production in T . spiralis infected Itgb8 ( CD11c-Cre ) mice . These data may represent tissue-specific effects of TGFβ activation in the small and large intestine , or more likely that it is mechanistically difficult to surpass the robust Th2 driven cytokine response seen during a normal T . spiralis infection . Instead we saw a lack of IL-17 production at day 13p . i . in mice lacking the TGFβ-activating integrin αvβ8 on DCs , accompanying an unaltered Th1/Th2 balance . ILC3s are known as important producers of IL-17 at mucosal barriers [52]; however , it appeared that the IL-17+ population was found within the CD3/CD4+ T-cell pool , therefore likely bona-fide Th17 cells . Increased TGFβ release is seen in human DCs following treatment with T . spiralis antigen [53] , although these DCs go on to favour a Th2 rather than a Th17 response , indicating that other cellular populations or subsets are producing cytokines which favour Th17 induction during in vivo infection . Along with TGFβ , numerous cytokines are involved in Th17 induction , including IL-6 , IL-21 , IL-1β and IL-23 ( reviewed in [39] ) . The production of IL-6 specifically at day 13p . i . is likely to be driving the Th17 induction [54] and possibly explains why we saw minimal IL-17 production corresponding with the initial peak of TGFβ at day 6 p . i . The source of IL-6 remains elusive , but Th17 induction via DC produced TGFβ relies on IL-6 production from a CD301b DC population during intranasal infection [55] , indicating a possible DC source . Overall , it will be interesting to define what cytokines and from which cells are involved in inducing the Th17 seen during T . spiralis infection . Furthermore , it is interesting to postulate the antigen specificity in the system . The data displayed are based on parasite-specific cytokine responses as well as PMA/ionomycin re-stimulation and , given helminths directly influence the intestinal microbiome [56 , 57] , it remains to be seen if Th17 responses to bacterial antigens would influence the outcome to T . spiralis infection . Our initial hypothesis to explain the delayed parasite expulsion was based on the previous finding that TGFβ-activating integrin αvβ8 is key in Treg development , as mice lacking the integrin on DCs have reduced Foxp3+ Tregs within the colonic lamina propria [30] . We therefore predicted that a possible reduction in Tregs in the small intestine of Itgb8 ( CD11c-Cre ) mice could be playing a role in the delayed expulsion seen during T . spiralis infection . Indeed , recent publications have demonstrated a requirement for Tregs for efficient helminth expulsion in the small intestinal H . polygyrus model [45] . Of note previous findings have demonstrated that H . polygyrus produces a TGFβ mimic which acts as an immunomodulatory agent aiding chronicity [58] , while our results suggest host TGFβ promotes expulsion of T . spiralis , as in our hands T . spiralis antigens have no TGFβ like properties [59] . This disparity could possibly be explained by the differing tissue localisation of the helminths during establishment , sub-mucosal versus epithelial niches or the local cytokine milieu , as H . polygyrus infection suppresses IL17 production [60] . However , the demonstration of reduced Tregs within the small intestinal lamina propria of Itgb8 ( CD11c-Cre ) mice , coupled with the delayed expulsion and increased weight loss in Treg depleted DEREG mice was initially indicative that reduced Treg numbers were solely responsible for the phenotype seen in Itgb8 ( CD11c-Cre ) mice . However , the extreme morbidity and mixed cytokine production observed , with no difference in IL-17 production , supported the previous hypothesise of “immunological chaos” in these mice . These results , coupled with the failure to rescue intestinal hypercontractility and worm expulsion kinetics when Itgb8 ( CD11c-Cre ) had been successfully adoptively transferred with Tregs , pointed towards additional mechanisms involved in T . spiralis delayed expulsion in Itgb8 ( CD11c-Cre ) mice . Adoptive transfer of Tregs was sufficient to return weight loss to wild-type levels , which has previously been shown to be mediated by the peptide hormone cholecystokinin [27] . It will therefore be of interest to examine any potential for Tregs to interact with production of cholecystokinin from enteroendocrine cells , given the recent interest in the immunoendocrine axis [61] . We have recently identified activated Tregs as expressing the TGFβ-activating integrin αvβ8 [62] which in the presence of IL-6 allows Tregs to induce Th17 cells in a GARP-dependent process [63] . It was therefore possible that the reduced small intestinal Treg numbers seen in Itgb8 ( CD11c-Cre ) mice were also responsible for the reduction in Th17 induction during T . spiralis infection . However , given that Treg depleted DEREG mice still mounted similar IL-17 responses as infected controls and the adoptive transfer of Tregs into Itgb8 ( CD11c-Cre ) mice failed to rescue Th17 numbers , the delayed parasite expulsion and reduced Th17 induction appears independent of Treg activation of TGFβ , and directly dependent on DCs . We began to examine several other mechanisms of helminth expulsion , and saw no changes in goblet cell kinetics or mastocytosis . Mucosal mast cells are also under the control of TGFβ , with the cytokine controlling mast cell expression of the gut homing integrin alphaE and MMCP-1 [64] , essential for the weep aspect of T . spiralis expulsion20 , 21 . It is therefore surprising that both mastocytosis and release of MMCP-1 appeared normal in Itgb8 ( CD11c-Cre ) mice . This may reflect alternative cell-specific mechanisms for the activation of TGFβ , with the active cytokine signalling within the local cellular environment , such as the T cell synapse via DC expressed αvβ8 . This hypothesised high level of control is perhaps unsurprising given the multiple pathways that TGFβ drives . Indeed , previous studies have demonstrated that epithelial expression of the TGFβ –activating integrin αvβ6 is essential for mast cell hyperplasia and MMCP-1 release during small intestinal helminth infection [65] . Moreover , epithelial cell specific αvβ6 null mice demonstrated abnormal mastocytosis and MMCP-1 expression [66] linked with reduced expression of the intestinal homing integrin alphaE [67] . Collectively , this supports the context specific integrin activation of TGFβ , allowing distinct and tight control of this pleiotropic cytokine . Finally , after we observed rIL-17 treatment was able to rescue weight loss and expulsion kinetics in T . spiralis infected Itgb8 ( CD11c-Cre ) mice , we investigated the possibility for IL-17 driving parasite expulsion . Indeed , late acting Th17 cells would prove beneficial in aspects of immunity and repair to helminth infection , with IL-17 driving Paneth cell antimicrobial peptide production [68] and IgA secretion [69] . This may be another important role of Th17 induction during T . spiralis infection , as microbial dysbiosis is a hallmark of intestinal helminth infection [57] and the microbiota also plays important roles in Th17 cell induction [39] . Although the data presented here was gained from co-housed littermate controls , it is interesting to speculate on how the microbiome may alter intestinal contraction via the induction of Th17 cells . Alternatively , IL-17 can have direct effects on nematode behaviour [70] and epithelial permeability; TGFβ activation by αvβ8 integrin has been shown to be important for increased alveolar permeability in acute respiratory distress syndrome [71] . Although we saw no changes at the microscopic level in infected Itgb8 ( CD11c-Cre ) mice , including goblet cells and RELMβ expression , Th17 production of IL-22 is related to goblet cell hyperplasia and enhanced worm expulsion [72] . Taking these potential mechanisms into account , and given the minimal effect of extra-intestinal larvae on muscle function at this timepoint [73] , we examined the possibility of alterations in jejunal contractility as a possible role for the delayed expulsion , concentrating on a possible role for IL-17 as an expulsion mechanism . Gut contraction during T . spiralis infection has previously been shown to be driven by Th2 cytokines and TGFβ , acting via STAT6 and COX-2 respectively [24 , 46] . Although we saw no changes in Th2 responses in our model , the reduced gut levels of active TGFβ seen in infected Itgb8 ( CD11c-Cre ) mice , could be involved directly in the reduced contraction seen . However , we observed a significant effect of rIL-17 on baseline gut contraction , reinforcing data from other investigators [74] , that was independent of COX-2 , as well as a complete rescue during infection by the addition of rIL-17 , but not Tregs; making it unlikely that TGFβ was directly responsible for contractility differences . Previous studies have demonstrated that Rho kinase signalling is emerging as an important mediator of intestinal smooth muscle contraction [47] , and may play a role during pathophysiology [75] . Moreover , there is precedent within the mucosal barrier of the lung , for αvβ8 dependent Th17 induction driving smooth muscle contraction via NF-κβ and the ROCK2 signalling cascade , with Itgb8 ( CD11c-Cre ) mice protected from airway hyper-responsiveness in response to house dust mite and ovalbumin sensitization and challenge [76] . Indeed , inhibiting the ROCK pathway , rather than STAT6 , prevented hypercontractility of small intestinal muscle in response to IL-17 indicating a potential similar mechanism ex vivo . However , it remains likely that Th2 cytokines and IL-17 may interact during the intestinal hypercontractility response to T . spiralis infection in vivo , with IL-17 previously shown to enhance IL-13 driven STAT6 intracellular responses in mouse and human lung epithelial cells [77] . Collectively , these data support a novel role for IL-17 in driving the intestinal contraction and augmenting the expulsion of T . spiralis . The inhibition of IL-17 during T . spiralis infection in wild-type mice further supports a key role for this cytokine in infection induced hypercontractility , but it must be noted that worm expulsion was unaltered when compared to vehicle treated animals . These data , when coupled with the complete rescue of weight , contractility and worm expulsion seen in IL-17 treated Itgb8 ( CD11c-Cre ) mice , suggests an additional facet , possibly reduced intestinal Tregs , that further promotes the key role of IL-17 within the Itgb8 ( CD11c-Cre ) model . An important question remains as to what regulates the strong Th2 response seen during T . spiralis infection . Although we did see some increased morbidity in terms of weight loss during the infection of Itgb8 ( CD11c-Cre ) mice , our adoptive transfer experiments suggest this is most likely due to the decreased Treg population and possibly the increased worm burden phenotype seen . As discussed earlier , activation of TGFβ via other mechanisms in a cell specific context may be responsible , or it may be a combination of several factors; as seen by the dual roles of IL-10 and TGFβ seen in T . spiralis nurse cell immunopathology [28] . Indeed IL-10 has previously been shown to be essential in avoiding fatal immunopathology in response to the microbiota during another epithelial dwelling helminth , Trichuris muris [78] . Tregs are likely to play a role , and are often associated with helminth infection , but we are reliant on more subtle approaches to remove distinct Treg subsets , as our results confirm global depletion as being detrimental to mouse survival by failing to regulate the majority of inflammatory pathways [45] . In summary , we have highlighted an important cellular and molecular pathway by which the DC expressed TGFβ-activating integrin αvβ8 , maintains intestinal Tregs and drives the induction of Th17 cells late during infection with the small intestinal helminth T . spiralis . Tregs are essential for mediating infection induced weight loss , while the resulting Th17 produced IL-17 mediates the contraction of jejunal muscle via ROCK signalling aiding the “weep and sweep” mechanism of helminth expulsion . Thus , we have identified the molecular mechanism maintaining Tregs and driving Th17 induction and helminth expulsion , beyond the classical Th2 responses . Additionally , whether the Th17 pathway can be harnessed therapeutically in other parasitic diseases or pathologies encompassing muscle hypercontractility should be a focus of further studies .
C57BL/6 mice were purchased from Harlan Laboratories . Mice lacking integrin αvβ8 on DCs via expression of a conditional floxed allele of β8 integrin in combination with CD11c-Cre ( Itgb8 ( CD11c-Cre ) mice ) [30] and DEREG mice [32] , all on a C57BL/6 background , have been previously described and were bred in house . For Itgb8 ( CD11c-Cre ) mice transgene negative littermate controls were used in all experiments . For DEREG mice transgene positive littermates were treated with PBS for controls . All experiments were on male , age-matched mice maintained in specific pathogen-free conditions at the University of Manchester and used at 6 to 12 weeks of age . All animal experiments were performed under the regulations of the Home Office Scientific Procedures Act ( 1986 ) , specifically under the project licence PPL 40/3633 . The project licence was approved by both the Home Office and the local ethics committee of the University of Manchester . Animal euthanasia occurred using approved schedule 1 methods . The maintenance , infection and recovery of T . spiralis were carried out as previously described [79] . Mice were orally infected with 300 larvae and individually weighed on a daily basis . Worm burdens were assessed by counting the number of worms present in the small intestine as described previously [79] . Foxp3+ Tregs were depleted in DEREG mice as described [32] , via i . p . injection of 200 ng diphtheria toxin ( Merck ) every 2 days from 2 days prior to infection . IL-17 was blocked via i . p . injection of 100μgs of anti-IL-17α ( 17F3 ) or IgG1 isotype control ( MOPC-21 ) ( BioXCell ) from day 7 p . i . and every 3 days following . For Treg treatment , cells were isolated via Treg isolation kit ( Miltenyi ) according to manufacturer’s instructions . Cells were assessed as >95% Foxp3+ and mice were adoptively transferred with 1x106 Tregs prior to infection . For IL-17 treatment , 2ug of recombinant IL-17 ( Peprotech ) was injected i . p . every 3 days from day 9 post-infection . In both gain of function treatments control animals received PBS vehicle injections at identical time points . Spleens and mesenteric lymph nodes ( mLNs ) were removed from mice and disaggregated through a 100 μm sieve . Small intestines were excised and lamina propria lymphocytes ( SILP ) were prepared essentially as described [80] with slight modification in the tissue digestion step ( digestion medium used was RPMI with 10% Foetal calf serum , 0 . 1% w/v collagenase type I and Dispase II ( both Invitrogen ) , and tissue was digested for 30 min at 37°C ) . Cell suspensions were blocked with anti-FcγR antibody ( clone 24G2; eBioscience ) before labelling with antibodies specific for CD3 ( eBio500A2 ) , CD4 ( clone GK1 . 5; eBioscience ) , Foxp3 ( clone FJK-16s; eBioscience ) , IL-13 ( clone eBiol13A; eBioscience ) , IFNγ ( clone XMG1 . 2; eBioscience ) , IL-17 ( eBio17B7; eBioscience ) , IL-9 ( RM9A4e; Biolegend ) or p-Smad 2/3 ( Santa Cruz ) . For intracellular cytokine analysis cells were incubated for 12 hours with 1x Cell stimulation cocktail ( plus protein inhibitors ) ( ebioscience ) . Cells were then stained with antibodies using the eBioscience Foxp3 permibilization kit according to the manufacturer's instructions . For pSmad2/3 staining , an Alexa Fluor 594-labelled donkey anti-goat secondary antibody was used ( Invitrogen ) . All samples were analysed on a FACS LSRII . mLN and SILP cells were prepared as described above before incubating with 50μg/ml T . spiralis antigen for 24 hours in media ( RPMI-1640 , 10% FCS , 100U/ml Pen/strp , 5%NEAA , L-glutamine and HEPES , 0 . 05 mM β-mercaptoethanol ( SIGMA ) ) . Cell-free supernatants were analysed for cytokine production via cytometric bead array ( BD ) or paired ELISA antibodies ( anti-IFNγ , clone XMG1 . 2 and R4-6A2; anti-IL-13 , clone eBio13A and eBio1316H; anti-IL-4 , clone 11B1and BVD6-2462 , anti-IL-17 clone eBio17CK15A5 and eBio17B7; ( eBioscience ) ) . For TGFβ analysis samples were acid-activated prior to detection on a mouse TGF-beta 1 DuoSet ELISA ( R and D Systems ) . Intestinal tissue was fixed in Carnoy’s solution and embedded in wax prior to mast or goblet cell staining via toludine blue or Schiff's reagent , respectively . Following antigen retrieval , RELMβ was labelled via primary antibody 1:400 ( Abcam-ab11429 ) followed by detection with an Elite ABC HRP Kit ( Vectastain ) according to manufacturer’s instructions . After mounting , positive cells were enumerated in 20 randomly selected villus crypt units ( VCU ) and results presented as mean number of positive cells/20 VCU ( ± S . D . ) . Lengths of villus/crypts were enumerated via image J . Serum was obtained from blood at the time of sacrifice via centrifugation at 15000×g . Parasite specific IgG1 and IgG2a assessed via 5 μg/ml T . spiralis antigen coated ELISA plates in 0 . 05 M carbonate/bicarbonate buffer , pH 9 . 6 . IgG1 and IgG2a were detected using biotinylated rat-anti mouse antibodies ( Pharmingen , UK and Serotec , UK respectively ) diluted in PBS-Tween and visulaised using streptavidin peroxidase and ABTS substrate prior to being read 405nm on a VersaMax microplate reader ( Molecular devices , UK ) . Mouse mast cell protease-1 assessed via ELISA according to manufacturer’s instructions ( Moredun ) . Ex vivo intestinal contraction was measured as previously described [81] . Briefly , 3cm isolated jejunal strips were placed in oxygenated ( 95%O2-5%CO2 ) Krebs solution and surgical silk was used to hang the tissue longitudinally in an isolated tissue bath ( Radnoti ) . Tissues were equilibrated for 30mins at 37°C under tension ( 1g ) , prior to baseline and carbachol ( 10-6M ) response readouts being measured . The maximum force generated by the tissue was assessed ( AD Instruments and Labchart Reader 8 ) and expressed in milligrams after normalising for cross sectional area [81] . In some cases , jejunal tissue was incubated in 10ng/ml rIL-17 for 6 hours in medium ( Leibovitz’s L-15 , 10% FCS , 100 U/ml Pen/strep , 50mg/ml gentamicin , 5% NEAA , L-glutamine and HEPES , 0 . 05 mM β-mercaptoethanol ) , following 2 hour treatment with 10μM celecoxib ( COX-2 inhibitor ) , 100nM AS1517499 ( STAT6 inhibitor ) or 10uM Y-27632 ( ROCK inhibitor ) ( Sigma ) prior to measuring longitudinal muscle tension generated in response to carbachol ( 10-6M ) . In vivo intestinal contraction was assessed via a 12 hour fast prior to gavage of 200μl of 6% carmine red dye ( Sigma ) in 0 . 5% methylcellulose 400c . p . ( Sigma ) before measuring distance of dye front , confirmed via tissue blotting , and gut length precisely 20mins later . Total RNA was purified from small intestinal isolated jejunal muscle strips using Trizol reagent according to the manufacturer’s instructions ( ThermoFischer ) . RNA was reverse transcribed using oligo ( dT ) primers and complementary DNA for specific genes detected using a SYBR Green qPCR Kit ( Roche ) . Gene expression was normalized to HPRT levels . IL-17ra Forward-5’ CAAGTTTCACTGGTGCTGCC; IL-17ra Reverse-5’ TAGTCTGCAACTGGCTTGGG; HPRT Forward-5’ GCGTCGTGATTAGCGATGATGAAC; HRPT Reverse-5’ GAGCAAGTCTTTCAGTCCTGTCCA . Results are expressed as mean ± S . D . . Where statistics are quoted , two experimental groups were compared via the Student’s t test for non-parametric data . Three or more groups were compared with ANOVA , with Dunnett’s or Bonferroni’s post-test as indicated . A p value of <0 . 05 was considered statistically significant . * , P<0 . 05; ** , P<0 . 01; or *** , P<0 . 005 for indicated comparisons , error bars represent SD of means .
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Infection with intestinal parasitic worms is a major global health problem . We have therefore evolved means to drive the expulsion of these worms ( known as helminths ) , based on protective ( type 2 ) immune responses . However , if these immune responses are not regulated they can result in more harm than good . One protein that can be key in controlling immune responses is transforming growth factor beta ( TGFβ ) . Using a model helminth which infects mice , we found that TGFβ was indeed signalling to the immune cells which can initiate the type 2 response , but rather than increasing the regulation of these T-cells it was driving a different inflammatory immune response ( termed Th17 ) . Interestingly , this Th17 response was important in expelling the parasite , as mice lacking the ability to activate the TGFβ protein , lacked Th17 responses and the ability to contract intestinal muscles and flush out the parasite . Our findings therefore provide new insights into how helminths are expelled and identify potential molecular targets for the prevention of helminth infection which affects billions of the world’s population in deprived communities .
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2019
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TGFβ-activation by dendritic cells drives Th17 induction and intestinal contractility and augments the expulsion of the parasite Trichinella spiralis in mice
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DNA repair mechanisms are crucial for maintenance of the genome in all organisms , including parasites where successful infection is dependent both on genomic stability and sequence variation . MSH2 is an early acting , central component of the Mismatch Repair ( MMR ) pathway , which is responsible for the recognition and correction of base mismatches that occur during DNA replication and recombination . In addition , recent evidence suggests that MSH2 might also play an important , but poorly understood , role in responding to oxidative damage in both African and American trypanosomes . To investigate the involvement of MMR in the oxidative stress response , null mutants of MSH2 were generated in Trypanosoma brucei procyclic forms and in Trypanosoma cruzi epimastigote forms . Unexpectedly , the MSH2 null mutants showed increased resistance to H2O2 exposure when compared with wild type cells , a phenotype distinct from the previously observed increased sensitivity of T . brucei bloodstream forms MSH2 mutants . Complementation studies indicated that the increased oxidative resistance of procyclic T . brucei was due to adaptation to MSH2 loss . In both parasites , loss of MSH2 was shown to result in increased tolerance to alkylation by MNNG and increased accumulation of 8-oxo-guanine in the nuclear and mitochondrial genomes , indicating impaired MMR . In T . cruzi , loss of MSH2 also increases the parasite capacity to survive within host macrophages . Taken together , these results indicate MSH2 displays conserved , dual roles in MMR and in the response to oxidative stress . Loss of the latter function results in life cycle dependent differences in phenotypic outcomes in T . brucei MSH2 mutants , most likely because of the greater burden of oxidative stress in the insect stage of the parasite .
Two members of the trypanosomatidae family , Trypanosoma cruzi and Trypanosoma brucei , are important human pathogens , since they cause , respectively , Chagas disease , or American trypanosomiasis , and African Sleeping Sickness , or Human African trypanosomiasis . Together , T . cruzi and T . brucei infections affect almost 20 million people [1 , 2] . The life cycles of both these parasites involve two hosts: an invertebrate vector and a mammalian host . In the digestive tract of the insect vector T . cruzi multiplies as epimastigotes and differentiates into metacyclic trypomastigotes , which are expelled with the vector’s faeces . After a blood meal , trypomastigotes injected in the host bloodstream can invade different cell types , where they replicate as intracellular amastigotes that , after a number of replication cycles in the host cell cytoplasm , differentiate into trypomastigotes and lyse the host cell membrane . Despite being similar in general strategy , the life cycle of T . brucei is different to that of T . cruzi in several key details . Notably , T . brucei does not display any intracellular replicative stages . In the mammal , T . brucei is exclusively extracellular , replicating in the bloodstream and tissue fluids as bloodstream form ( BSF ) cells , which can be taken up by the tsetse fly vector during a bloodmeal . In the insect vector BSF cells differentiate into replicative procyclic forms ( PCF ) , which then undergo several further differentiation events associated with migration to the fly salivary glands , where non-replicative metacyclic trypomastigotes are formed and can be passed into a new mammalian host through the proboscis when the infected fly is feeding [3] . Irrespective of the detailed differences in the life cycles , differentiation between the mammal-infective and vector-infective forms of both T . cruzi and T . brucei is accompanied by dramatic metabolic changes and morphological alterations [4] . The ability to multiply and survive inside a host or vector is crucial for the maintenance of a parasite infection and transmission , allowing continuation of the life cycle . As for any cell , unicellular parasites are exposed to potentially deleterious events during cell division . The by-products of cellular metabolism , allied to routine errors during DNA replication or recombination processes , represent endogenous sources of potential DNA damage and genome change . In addition , all organisms are subjected to exogenous genotoxic agents from the environment or , in the case of parasites , derived from host . In the mammalian host , T . cruzi invades non-phagocytic cells or can be internalized by macrophages by a phagocytosis-like process [5] . Inside macrophages T . cruzi triggers the activation of NADPH oxidase , which generates large amounts of reactive oxygen species ( ROS ) such as O2⠁- . Moreover , pro-inflammatory cytokines triggered by T . cruzi infection also stimulate infected macrophages to produce high amounts of nitric oxide ( ⠁NO ) through the induction of inducible nitric oxide synthase ( iNOS ) , which can react with O2⠁- producing peroxynitrite ( ONOO- ) , a powerful oxidant and cytotoxic molecule [6 , 7] . Similarly , the insect life forms of both parasites must also deal with the invertebrate oxidative stress response generated against the parasite . Upon challenge with T . brucei the tsetse fly activates iNOS , generating ⠁NO , and increases the levels of ROS such as hydrogen peroxide ( H2O2 ) [8 , 9] . To deal with all of these potentially genome damaging agents , trypanosomes , like any other organism , possess multiple DNA repair pathways [10 , 11] , though little work has detailed to what extent these pathways are needed in different parasite life cycle stages . One such DNA repair pathway is Mismatch Repair ( MMR ) , which acts to detect and correct mispaired bases that escape the proofreading activity of DNA polymerases during replication or occur during recombination between non-identical DNA molecules . In eukaryotic cells , even small distortions in DNA caused by single-base mismatches or insertion/ deletion loops ( IDLs ) of 1–3 bases are recognised by the “sliding clamp” heterodimer formed by MSH2 and MSH6 proteins , which moves along DNA searching for errors [12] . Larger IDLs are recognised by a distinct heterodimer , composed of MSH2 and MSH3 . Eukaryotes encode several further MSH proteins , all of which are homologous to bacterial MutS proteins , though many have adopted non-MMR roles [13] . Following mismatch recognition , an ATP-dependent conformation change in MSH2-6 or MSH2-3 promotes interaction with heterodimeric homologues of bacterial MutL proteins , bringing these factors to the site of the lesion . The excision step is catalyzed by an endonuclease activity within the MutL-related heterodimer formed between MLH1-PMS1 [14] , and that activity is activated by PCNA ( a component of replication machinery ) [15] [16] . A defect in or directed inactivation of the MMR pathway leads to a 100–1000 fold increase in spontaneous mutation rate in all organisms examined , including Escherichia coli [17] , Saccharomyces cerevisiae [18] , Caenorhabditis elegans [19 , 20] , and T . brucei [21] . In human cells and murine models MMR deficiency is correlated with predisposition to cancer [22 , 23] . MMR suppresses mutations by increasing DNA replication fidelity through preventing base substitutions or repeat sequence instability , events that can also occur during homologous recombination [24] . In addition to repair of non-identical DNA sequences , MMR has also been demonstrated to be involved in the response to DNA damage induced by genotoxic agents , among them the alkylator N-methyl-N’-nitro-N-nitrosoguanidine ( MNNG ) , the anti-cancer drug cisplatin and H2O2 [25] . Methylation of DNA by MNNG gives rise to O6-methylguanine ( O6-MeG ) , opposite which thymine can be misincorporated during replication , forming a base mismatch recognised by MMR . Defective MMR is associated with increased tolerance to MMNG [26] , due to loss of what has been termed a futile cycle of repair , where MMR fails to remove O6-MeG and instead re-inserts either cytosine or thymine opposite the lesion . In some organisms , active MMR at MNNG damage leads to persistent DNA breaks and increased cell death [27] . H2O2 generates reactive oxygen species ( ROS ) with high capacity to damage DNA [28] . The most common DNA lesion resulting from ROS is 7 , 8-dihydro-8-oxoguanine ( 8-oxoG ) [29] . MMR has the ability to prevent oxidative mutagenesis in E . coli by removing 8-oxoG or adenine misincorporated paired with 8-oxoG [30] . In S . cerevisiae it was demonstrated that the MSH2-MSH6 heterodimer has a direct role in removing adenine in 8-oxoG:A mispaired bases [31] . More recently , Zlatanou et al . proposed a non-MMR role for MSH2-MSH6 in human fibroblasts in response to oxidative damage . The model suggests that in some circumstances DNA oxidative damage by MSH2-MSH6 does not recruit other MMR proteins , but instead repair is mediated through the action of monoubiquinated-PCNA ( mUb-PCNA ) and Polη [32] . With the availability of the complete genome sequences of T . brucei and T . cruzi the full repertoire of the parasite’s putative DNA MMR machinery was revealed to comprise homologues of MSH2 , MSH3 , MSH6 ( originally named MSH8 ) [21] , MLH1 and PMS1 [10 , 33 , 34] . However , functional characterization studies to date have been limited to a single life cycle stage in each parasite and have only tested the roles of MSH2 in T . brucei and T . cruzi , and MLH1 in T . brucei . Null mutants of T . brucei msh2 ( Tbmsh2-/- ) or mlh1 ( Tbmlh1-/- ) in BSF cells show several phenotypes characteristic of MMR-deficient cell lines: increased tolerance to MNNG , increased rates of sequence change in a number of microsatellite repeat loci , and elevated rates of homologous recombination-based integration of transformed DNA molecules carrying base mismatches relative to genomic target loci [21 , 35 , 36] . In addition , evidence that TbMSH2 and TcMSH2 play a role in in the oxidative stress response has been found in studies showing that Tbmsh2-/- BSF cells and Tcmsh2+/- epimastigotes are more susceptible to H2O2 treatment than wild type parasites [21 , 37] . The role played by MSH2 in tackling oxidative damage appears not to involve a complete MMR reaction , since BSF Tbmlh1-/- mutants do not display equivalent increased H2O2 sensitivity to Tbmsh2-/- mutants [38] . Moreover , heterologous expression of T . cruzi MSH2 in T . brucei msh2-/- mutants shows that the American trypanosome MSH2 protein can functionally replace the endogenous MSH2 protein in the oxidative stress response , but cannot work with the T . brucei MMR machinery to successfully execute MMR [38] . Although only single allele knock-outs of msh2 have been described in T . cruzi epimastigotes , the T . cruzi msh2+/- mutants display increased sensitivity to H2O2 treatment [37] , consistent with the null mutants in T . brucei BSF cells [38] . However , despite evidence in both T . brucei and T . cruzi that H2O2-induced damage predominantly affects the kinetoplast genome when MSH2 is lost or impaired [37] , the exact role of MSH2 remains elusive . Here , we have sought to clarify the role of MSH2 in the oxidative stress response of T . brucei and T . cruzi , and to ask to what extent this putative MMR-related function is conserved or diverged in the two parasites . We describe the generation of msh2 null mutants in T . brucei PCF cells , which differ from BSF cells in the increased use of mitochondrial metabolism [39] , with the consequence that there is greater endogenous reactive oxygen species . In addition , we describe , for the first time , the generation of msh2 null mutants in T . cruzi epimastigote cells , which also rely on aerobic metabolism [40] . In both cell types , msh2 null mutants are viable and are impaired in MMR . Unexpectedly , both mutants do not display increased sensitivity to H2O2 treatment , but instead , increased resistance , which we suggest to be due to parasite adaptation to the loss of a crucial molecule . Thus , we propose that MSH2 provides one of several interconnected mechanisms that are common to T . brucei and T . cruzi and allow both parasites to cope with oxidative stress .
T . brucei cultures of the Lister 427 strain were maintained as both bloodstream ( BSF ) and procyclic ( PCF ) forms . BSF parasites were maintained at 37°C , 5% CO2 in HMI-9 ( GIBCO ) medium supplemented with 20% fetal bovine serum ( GIBCO ) . Cell passages were performed every 48 hours , with population density maintained between 1 x 105 and 2 x 106 cells . mL-1 . PCF cells were maintained at 27°C in SDM-79 ( GIBCO ) medium supplemented with 10% fetal bovine serum ( GIBCO ) . Weekly passages were performed , but cell density was never lower than than 5 x 105 cells . mL-1 . Epimastigote forms of the CL Brener clone of T . cruzi were maintained in logarithmic growth phase at 28°C in liver infusion tryptose ( LIT ) medium supplemented with 10% fetal bovine serum ( GIBCO ) and penicillin ( 10 , 000 U . mL-1 ) /Streptomycin ( 10 , 000 μg . mL-1 ) ( GIBCO ) as described by [41] . Metacyclic trypomastigotes , obtained after metacyclogenesis of epimastigotes cultures maintained in LIT medium for 15 to 20 days , were used to infect Vero cells cultured in DMEM medium ( GIBCO ) supplemented with 5% fetal bovine serum ( GIBCO ) . Transfection of PCF parasites were carried out at a density of 5 x106 cells . mL-1 resuspended in 0 . 5 mL of ice-cold Zimmerman medium ( 132 mM NaCl , 8 mM KCl , 8 mM Na2HPO4 , 1 . 5 mM KH2PO4 , 0 . 5 mM MgAc2 , and 0 . 06 mM CaAc2 , pH 7 . 5 ) and 10 μg of DNA . The mixture was subjected to two rounds of electroporation with a Bio-Rad Gene Pulser II ( 1 . 5 kV current and 25 μF capacitance ) . The cells were then transferred into SDM79 medium and incubated at 27°C overnight . To select for antibiotic-resistant transfectants , parasites were diluted 1:100 and 1:10 in 96 well plates containing conditioned medium and the appropriate antibiotic and incubated for 10–14 days . Transfection of BSF cells were carried out using AMAXA Nucleofactor ( Amaxa Biosystems ) with 4 x 107 cells resuspended in 100 μL of nucleofector solution ( optimised for human T-cells ) and mixed with 5–10 μg of DNA . After following the nucleofection protocol according to manufacturer instructions , the cells were serially diluted 1:10 , 1:100 and 1:1000 in HMI-9 medium without antibiotic and incubated 6–12 hrs for recovery , after which 1 mL of HMI-9 medium containing antibiotic was added to each well . To select for MSH2 or MLH1 single allele mutants , PCF cells were selected with either 10 μg . mL-1 blasticidin or 1 μg . mL-1 puromycin; both drugs , at the same concentrations , were used to select for deletion of the second allele in the single allele mutants . To select for PCF msh2-/- cells in which MSH2 was re-expressed , transformants were grown in the presence of 2 . 5 μg . mL-1 phleomycin . Transfection of T . cruzi epimastigotes was carried out with 107 cells . mL-1 collected during exponential growth phase and 100 μg of plasmid constructions as previously described [42] . Twenty-four hours after transfecting hygromycin resistant cell lines , 100 μg . mL-1 of selective antibiotic ( G-418 Sulfate ) was added to transfected cultures . Weekly passages were performed with increasing concentration of the selective drug ( up to 200 μg . mL-1 ) . After 30–40 days , a double-resistant population was selected and cloned cell lines were obtained by plating epimastigotes on semisolid blood agarose plates with 200 μg . mL-1 of G-418 Sulfate and Hygromycin B , after an additional 30 days of incubation at 28°C . Knockout constructs to delete msh2 ( TritrypDB Tb927 . 10 . 11020 ) or mlh1 ( TritrypDB Tb927 . 8 . 6840 ) in T . brucei PCF cells have been described before [21] and were generated by PCR-amplifying the 5’ and 3’ UTRs corresponding to each gene from TREU 927 genomic DNA and cloning into pBluescript II KS and separated by antibiotic resistance gene ( BSD and/or PUR ) , flanked by 230 bp of β-α tubulin and 330 bp of α-β tubulin processing signals . The constructs were linearized by digestion with XhoI and NotI restriction enzymes before transfecting into T . brucei PCF . Epimastigote cultures of T . cruzi with one of the msh2 alleles disrupted by a Hygromycin resistance gene was generated as described by [37] . The deletion of the second allele was performed using a DNA construct containing the Neomycin phosphotransferase gene ( Neo ) flanked by intergenic sequences of the HX1 and GAPDH regions that were PCR-amplified from the pROCK-GFP vector [42] and cloned into pGEM T-easy vector ( Promega ) . DNA sequence corresponding to ~500 bp of the 5’ and 3’ end of TcMSH2 ( TritrypDB TcCLB . 507711 . 320 ) coding region was inserted upstream and downstream of HX1 and GAPDH , respectively , in the pTopo_HX1_Neo_GAPDH and the plasmid linearized using the XbaI and SmaI restriction enzyme digestions before transfection . T . brucei msh2-/- BSF and PCF were transfected with an MSH2 re-expression construct , which has been described before [21] and where the msh2 ORF integrates and replaces either the BSD or PUR resistance cassette in the mutated msh2-/- locus . This construct was generated using a 4 . 5 kb region containing the MSH2 gene flanked by MSH2 5’UTR and 3’UTR . The 4 . 5 kb fragment was cloned into pBluescript SK II , followed by a cloned phleomycin resistant cassette downstream of the 3’ UTR of the MSH2 gene . The construct was digested with HindIII prior to transfection . To generate RNAi constructs for MSH2 , a 513bp region of the gene was PCR-amplified from wild type Lister 427 genomic DNA and cloned into the vector pZJM [43] where they are flanked by opposing T7 promoters and Tet operator sequences . The MSH2 RNAi plasmid was linearized with NotI and used to transform T . brucei PCF strain 427 pLew29-pLew13 developed by Wirtz et al [44] , constitutively co-expressing T7 RNA polymerase and Tet repressor . Clones were selected with 2 . 5 μg . ml-1 phleomycin . Total RNA was isolated from T . brucei PCF form and T . cruzi epimastigote forms using the RNeasy kit ( Qiagen ) . For cDNA generation RNA samples were treated , on column , with RNAse-free DNAse ( Qiagen ) as per the manufacturer’s instructions . cDNA was synthesized using High Capacity RNA-cDNA master mix ( Applied Biosystems ) . cDNA from wild type ( WT ) cells , Tbmsh2+/- blasticidin ( BSD ) or puromycin ( PUR ) resistant clones , Tbmsh2-/- , Tbmlh1+/- BSD or PUR resistant clones and Tbmlh1-/- were used in reverse transcriptase ( RT ) PCR with specific primers for the TbMSH2 or TbMLH1 genes . As a positive control , primers to specifically PCR-amplify TbRAD51 were used . For northern blot analyses , 20 μg of total RNA of T . cruzi WT , Tcmsh2+/- and three different clones of Tcmsh2-/- were separated in a 1 . 2% agarose/MOPS/formaldehyde gel . The RNA was then transferred to hybond-N+membrane ( GE Healthcare ) and hybridized with a TcMSH2 specific PCR fragment previously labelled with [α-32P]-dCTP using the Amersham Ready-to-Go DNA Labelling Beads ( GE Healthcare ) . The hybridization was carried out as previously described by [45]; briefly , hybridisation was in 50% formamide buffer overnight at 42°C , after which the blot was washed twice with 2× SSC/ 0 . 1% SDS at 65°C for 20 min . The membrane was then exposed to a phosphor screen of the STORM 820 phosphor image ( GE Healthcare ) and analysed by ImageQuant TL software ( GE Healthcare ) . To quantify levels of mRNA by RT-PCR after RNAi induction , primers specific for msh2 and mlh1 genes were used . As a endogenous control primers for GPI8 gene ( TritrypDB Tb427 . 10 . 13860 ) were used . SYBR Green PCR Master Mix ( Applied Biosystems ) was used for PCR in 96 well plates . Reactions were run on an ABI Prism 7000 thermocycler and mRNA levels quantified from amplification according to the manufacturer’s instructions; T . brucei PCF MMR mutants were tested for genetic instability by PCR amplification of the region containing the JS-2 microsatellite from parasites grown in the absence or presence of 20 μM H2O2 for 48 hours . The JS-2 microsatellite has been mapped to Chromosome IV and is composed of GT-dinucleotide repeats [46] . Genomic DNA was extracted from 10 independent clonal populations derived from PCF wild type and knockout mutants and PCR-amplified with JS2 microsatellite complementary primers . PCR products were resolved for 50 minutes at 100 V by electrophoresis in a 3% low melting agarose gel . Mid-log phase PCF T . brucei cultures were inoculated in SDM-79 ( GIBCO ) at density of 5 x 105 cells . mL-1 in the absence or presence of 2 . 5 μM or 5 μM N-methyl-N’-nitro-N-nitrosoguanidine ( MNNG , Tokyo chemical industry Ltd ) . After 72 hours survival was determined using a haematocytometer . T . cruzi epimastigote form cells in the exponential growth phase were counted and diluted to 1x 107 cells . mL-1 in LIT medium in the absence or presence of 5 μM MNNG ( Tokyo chemical industry Ltd ) . After 72 hours cell densities were determined by counting live cells with a haematocytometer using Erythrosin B exclusion . Mid-log phase T . brucei PCF cells were diluted to 5 x 105 cells . mL-1 in SDM-79 ( GIBCO ) and then incubated with 10 μM or 20 μM H2O2 ( VWR ) at 27°C for 48–72 hours . BSF cells were diluted to 1 x 106 cells . mL-1 in HMI-9 medium ( GIBCO ) and incubated with 100 μM or 200 μM H2O2 ( VWR ) at 37°C , 5% CO2 for 48 hours . After growth , cell density was measured using a haematocytometer . T . cruzi epimastigote form in exponential growth phase were diluted to 1x 107 parasites . mL-1 in PBS 1x and incubated with 75 μM H2O2 ( Sigma-Aldrich ) for 20 minutes at 28°C . After this , the cells were centrifuged , washed once with PBS and allowed to recover in LIT medium for 48 hours before cell densities were determined by counting live cells with a haematocytometer using Erythrosin B exclusion . Two clones of PCF RNAi cell line targeting MSH2 were grown to log phase and diluted to a starting density of 5 x 105 cells . mL-1 . Each culture was then split and grown in the absence of tetracycline or after the addition of tetracycline to 2 μg . mL-1 . Cell density was determined every 24 hours up to 72 hours and then the cultures were diluted to their starting density . After adding again tetracycline to induce siRNA expression , parasite numbers were further determined every 24 hours for a further 72 hours , before diluting again the cultures back to starting densities . Trypomastigotes released in the supernatants of infected Vero cells were counted with a haemocytometer and an equivalent cell number for each culture was used to infect Vero cells or intraperitoneal macrophages ( harvested from BALB/c mice ) that had been allowed to adhere to glass cover slips in a 24 well plate . Trypomastigotes were incubated with the cell monolayers for 4 hours , after which non-internalized trypomastigotes were washed away with PBS 1x . The infected cells were incubated for an additional 48 hours at 37°C . The number of intracellular amastigotes was determined by staining cell nuclei with DAPI ( 1000 μg . mL-1 ) and visualised through fluorescence microscopy ( Olympus ) . The average number of amastigotes was determined from analysing 1000 host cells , in different fields of the microscopy slide . In vitro infection of BALB/c mice macrophages were carried out in strict accordance with the Brazilian laws regarding animal use ( Law # 11 . 794 , December 8 , 2008 ) , following a protocol approved by the Committee on the Ethics of Animal Experiments of UFMG ( CETEA-UFMG ) under the number 132/2014 . 8-oxoG measurement was performed based on the principle of binding affinity of FITC-conjugated avidin to 8-oxoG [47] and an adapted protocol [48] , which has been previously used to quantify oxidative DNA lesions in different T . cruzi strains and mutants for different DNA repair proteins [37 , 49 , 50] . Briefly , 20 μL aliquots of cell suspensions were distributed on a glass slide coated with poly-lysine ( Sigma-Aldrich ) and left to adhere for 5–10 min , after which cells were fixed with ice-cold methanol for 20 min at -20°C . The methanol-fixed cells were then washed with room temperature PBS 1x , cells permeabilized with 0 . 1% Triton X-100 for 3 min and incubated with RNase A ( 100 μg . mL-1 ) for 1 hour at 37°C . After another wash with PBS 1x , cells were treated with proteinase K ( 10 μg . mL-1 ) for 7 min at room temperature , followed by treatment with HCl ( 4N ) for 7 min at room temperature and overnight blocking with 10% fetal bovine serum . FITC-avidin was diluted 1:200 in blocking buffer and incubated with the cells for 1 hour at room temperature . After extensive washing with PBS , cell nucleus and kDNA were stained with DAPI . Slides were mounted with prolong gold anti-fade solution ( Molecular Probes/Life Technologies ) , visualized under a fluorescence microscope and images of at least 10 different fields were captured . After manually delimiting the nucleus and the kDNA of each parasite , as visualized by DAPI staining , FITC- fluorescence intensity restricted to these sites were determined with ImageJ software and plotted as the average fluorescence ( arbitrary units ) of 100 random cells . T . brucei BSF , PCF and T . cruzi epimastigote cells were transfected with constructs to tag MSH2 C-terminally in the endogenous locus . Primers were generated against a C-terminal region of msh2 ORF , but excluding the stop codon . The region was selected to have a unique restriction enzyme recognition site within the ORF fragment that could be used to linearize the DNA . This fragment was cloned into the plasmid pNAT12myc [51] allowing in frame fusion of the ORF with 12 repeats of the c-MYC epitope . Similarly , the C-terminal region of Tcmsh2 ORF was cloned in pCR 2 . 1 Topo vector ( Life Technologies ) in frame with the 12 repeats of the c-MYC epitope derived from the T . brucei pNAT12myc plasmid . As a selective mark , neomycin resistance gene derived from the pROCK_Neo plasmid [42] was also cloned in the same pCR 2 . 1 Topo vector . The constructs were linearized with BmgBI ( for T . brucei ) or SalI ( for T . cruzi ) restriction enzymes and used to transfect heterozygous msh2 knockout mutants of T . brucei , and wild type T . cruzi epimastigotes; transfected T . brucei or T . cruzi were selected with 10 μg . mL-1 blasticidin or 200 μg . mL-1 G418 Sulfate , respectively . T . brucei BSF and PCF expressing MSH2 fused to 12x c-MYC epitopes were fixed in chilled methanol for 1 hour or overnight . Fixed slides were then blocked with 2% fetal calf serum ( FCS ) , incubated with mouse anti-c-MYC antiserum ( 1:5000 ) ( Millipore ) for 1 hour , followed by incubation with Alexafluor 594 conjugated anti-mouse IgG secondary antiserum ( Molecular Probes/ Life Technologies ) in the dark . Slides were mounted with vectashield containing 4’ , 6-diamidino-2-phenylindole ( DAPI; Vector labs ) and visualized on a Zeiss Axioplan microscope . Images were captured using Hamamatsu ORCA-ER digital camera and Openlab software . T . cruzi epimastigote and amastigote cells expressing MSH2 fused to 12x c-MYC epitopes were fixed with 4% paraformaldehyde for 5 minutes , permeabilized with 0 . 1% Triton X-100 for 10 min , blocked with 1% BSA , 0 . 2% Tween 20 for 1 hour at room temperature and incubated with 1:500 anti-c-MYC antiserum conjugated to Alexa 488 ( Milipore ) for 1 hour . After washing with PBS , nuclei were stained with 1 μg . mL-1 of DAPI ( Molecular Probes/ Life Technologies ) for 5 min and cover slides mounted with prolong gold anti-fade solution ( Molecular Probes/ Life Technologies ) . Images were captured on an Olympus BX60 microscope using Q-color 5 digital camera and Qcapture Pro 6 . 0 software . Statistical analyses in this work were performed using GraphPad Prism version 5 . 00 ( GraphPad Software , San Diego California USA ) . Data are presented as mean plus standard deviation , and all experiments were repeated at least three times . Results were analysed for significant differences using ANOVA followed by Bonferroni post-test . Statistical tests used are described at each figure legend . The level of significance was set at P < 0 . 05 .
The genomes of T . brucei and T . cruzi each contain a single-copy gene encoding MSH2 [33 , 34] . To generate T . brucei PCF msh2 null ( -/- ) mutants , we relied upon the same constructs used previously to make BSF cells in which both msh2 alleles were deleted [21] ( S1 Fig ) . In parallel , we also generated T . brucei PCF mlh1-/- mutants , again using pre-existing constructs . For both genes , the constructs replace the entire ORF ( 2856 bp and 2664 bp for MSH2 and MLH1 , respectively ) after homologous integration . Cells with a single allele deleted ( heterozygous mutants; +/- ) were first selected using either a construct encoding resistance to blasticidin ( BSD ) or puromycin ( PUR ) and confirmed by PCR ( S2 Fig ) . The +/- cells were then transformed with the reciprocal construct to attempt to make-/- mutants lacking both alleles; in both cases , and for reasons that are unclear , this was only successful when transforming the PUR deletion constructs into the cells that had integrated BSD and , furthermore , required a number of transformation attempts using varying antibiotic selection concentrations . Correct integration of the constructs and loss of both TbMSH2 or TbMLH1 alleles in the-/- mutants were confirmed by PCR ( S2 Fig ) . Deletion of both alleles in the PCF-/- mutants was further verified by RT-PCR amplification of RNA extracted from drug resistant parasites: as shown in Fig 1A , PCR products from the ORFs were detected in +/- cells as well as in wild type ( WT ) parasites , but not in the-/- mutants . To generate T . cruzi epimastigote msh2-/- mutants , we started with clones in which one MSH2 allele was deleted ( +/- cells ) [37] and replaced by the ORF for the hygromycin phosphotransferase ( HYG ) gene . It should be noted that in the msh2 heterozygous mutants ( +/- ) the HYG mRNA is generated by the predicted 5’ and 3’ processing signals flanking the MSH2 gene . In order to mutate the remaining allele , we found it was necessary to use a gene disruption construct ( S1 Fig ) in which a neomycin phosphotransferase gene ORF ( NEO ) was flanked upstream by processing signals derived from the T . cruzi intergenic region of the TcP2β gene [52] , and downstream by the intergenic region derived from the gapdh gene [42] . To allow integration into the remaining MSH2 allele , homologous targeting was based on TcMSH2 ORF sequence , and not on the 5’ and 3’ UTRs , as used before to generate the msh2+/- mutants . Finally , in order to successfully select for-/- cells , in which the first allele was deleted and the second disrupted , transformed parasites had to be selected initially with a low drug concentration ( 100 μg . mL-1 ) that was gradually increased to 150 μg . mL-1 and 200 μg . mL-1 during a period of 4 weeks . PCR amplification of DNA extracted from the Tcmsh2+/- cells , and from three cloned putative Tcmsh2-/- cell lines showed the expected integration of the different MSH2 targeting constructs in the T . cruzi genome ( S1 Fig ) . Northern blots using a probe specific for the TcMSH2 ORF and for the 24Sα rRNA as a loading control showed 52% less TcMSH2 mRNA in the +/- cells relative to WT , and no detectable MSH2 mRNA in the Tcmsh2-/- clones ( Fig 1B ) , confirming the gene disruption . The apparent reduction in TcMSH2 mRNA levels in the +/- cells is consistent with the observation of altered phenotypes in these cells relative to WT ( see below; and [37] ) . Similar to T . brucei msh2 mutants , no changes in population doubling times were detected when comparing growth of WT cells to the T . cruzi mutants with one or both msh2 alleles deleted ( S3 Fig ) . To ask if the mutations described above result in detectable loss of MMR , we measured the sensitivity of the parasites to MNNG [26] . T . brucei and T . cruzi mutants and WT cells were grown for 72 hours with increasing concentrations of MMNG . Survival of the cells was determined by measuring the cell density of the WT or mutant cells after MNNG treatment relative to untreated cells . In T . brucei , all cells showed increasing growth impairment as MNNG was increased from 2 . 5 to 5 μM . However , similar to what has been described in BSF cells [21] , and consistent with the proposed futile cycle of alkylation repair in MMR-proficient cells [26 , 27] , deletion of one allele of Tbmsh2 or Tbmlh1 in the PCF+/- mutants caused increased tolerance to MNNG , and this tolerance increased yet further when both alleles were deleted in the-/- mutants ( Fig 2A ) . Deletion of TbMSH2 or TbMLH1 in PCF cells also resulted in the-/- parasites displaying increased microsatellite instability , as was observed in T . brucei BSF mutants , indicating decreased replication fidelity ( S4 Fig ) . In T . cruzi increased tolerance to 5 μM MNNG was seen in the Tcmsh2+/- cells and was not detectably increased in the-/- mutants ( Fig 2B ) . Though this somewhat contrasts with the response of T . brucei MMR mutants to MNNG , these data nonetheless show that mutation of MMR genes in either parasite resulted in the expected enhanced survival in the presence of this alkylating drug . To ask how the loss of the MMR genes affects the response of T . brucei and T . cruzi cells to oxidative stress , we compared growth of the WT cells and mutants in the presence of H2O2 , again determining survival in the presence of the damaging agent relative to undamaged cells . In striking contrast to our previous observations in T . brucei , which showed that Tbmsh2-/- BSF cells are more susceptible to H2O2 [38] , PCF T . brucei msh2 mutants were more resistant to H2O2 than WT cells after 48 hrs growth at either 10 μM or 20 μM ( Fig 3A ) : improved survival was seen in both the msh2+/- and msh2-/- cells at this time point , and was also observed 24 and 72 hrs post-treatment ( S5 Fig ) . In contrast , though T . brucei mlh1+/- mutants displayed a modest increase in H2O2 resistance ( in particular upon treatment with 10 μM H2O2; Fig 3A ) , mlh1-/- mutants displayed no detectable difference from WT , indicating that the MMR response to H2O2 damage is predominantly mediated through MSH2 and not MLH1 . This separation in function between the two MMR factors is consistent with observations in T . brucei BSF cells , though with distinct patterns of H2O2 sensitivity [38] . Analysis of the T . cruzi epimastigote mutants revealed that loss of both msh2 alleles also resulted in increased resistance to H2O2 in these parasite , though loss of one msh2 allele resulted in increased sensitivity to 75 μM H2O2 , which is distinct from T . brucei msh2+/- mutants [38] and consistent with previous findings [37] ( Fig 3B ) . Taken together , the enhanced survival of PCF T . brucei msh2 null mutants to H2O2 exposure suggests a life cycle difference in the consequence of this mutation relative to BSF cells . Moreover , this unexpected phenotype is conserved in epimastigote T . cruzi msh2 null mutants . To investigate the role of MSH2 in protecting T . cruzi against oxidative stress generated by host cells , we compared the capabilities of T . cruzi WT and msh2-/- mutants to infect two different cell types: Vero cells and mouse macrophages . Equal numbers of trypomastigotes derived from Vero cells infected with WT and msh2-/- mutants were added to cultures of the two cell types and the numbers of intracellular amastigotes were determined 2 days later by staining parasite nuclei with DAPI . As shown in Fig 4A , no difference in the number of intracellular amastigotes was observed in Vero cells infected with WT or Tcmsh2-/- parasites . However , infections with each of the three Tcmsh2-/- clonal cell lines resulted in a 3-fold increase in the number of intracellular amastigotes relative to infection with WT cells in cultivated mouse macrophages ( Fig 4B ) . As macrophages generate ROS , through an infection-induced respiratory burst [6] , while Vero cells do not , these infection data appear consistent with the increased resistance of T . cruzi msh2-/- null mutants to H2O2 treatment ( see Fig 3B ) . The infection data also indicate that the increased capacity to survive exposure to oxidative stress is maintained after T . cruzi differentiates into other life cycle stages . The increased resistance to oxidative stress observed in T . brucei PCF cells and T . cruzi epimastigotes after MSH2 mutation could be a direct consequence of the loss of this MMR component , or could be due to indirect effects , such as a metabolic adaptation . To begin to address this , we determined the capacity of mutant cells to limit the accumulation of oxidized bases in their genome , which can arise from exposure to ROS generated by endogenous parasite metabolism or from the host . The primary DNA lesion generated by oxidative damage is 8-oxoG , which , if not removed by base-excision repair , can be recognized by MMR [26] . We therefore measured the levels of this oxidized base in the WT and msh2 mutant parasite genomes using avidin-conjugated FITC and measuring fluorescence [47] . As shown in Fig 5A and 5B , PCF T . brucei msh2+/- and msh2-/- mutants each displayed ~2 fold greater fluorescence in their nuclear DNA ( nDNA ) and kinetoplast DNA ( kDNA ) compared with WT cells . These fluorescence data indicate that the levels of 8oxoG were no greater in the T . brucei msh2-/- mutants than in the Tbmsh2+/- mutants , consistent with the observation that the two mutants display equivalent levels of resistance to H2O2 ( Fig 3 ) . In contrast , no difference was observed in the levels of fluorescence in the nDNA or kDNA of mlh1 mutants related to WT ( Fig 5B ) , a distinction from T . brucei msh2 mutants again consistent with the separation of MMR functions observed when examining levels of resistance to H2O2 . Increased levels of avidin-FITC fluorescence were also seen in the nDNA and kDNA of T . cruzi epimastigote msh2 mutants: 1 . 7 to 1 . 9 fold increase in fluorescence was seen in the nDNA and kDNA of both Tcmsh2+/- clones and both Tcmsh2-/- clones examined relative to WT ( Fig 5C ) . These data suggest that loss or reduction of MSH2 expression ( but not MLH1 ) in PCF T . brucei and in epimastigote T . cruzi results in the impairment of a pathway involved in the repair of DNA-directed oxidative damage , such as 8-oxoG . Thus , the increased resistance to H2O2 in the mutants is best explained by an indirect adaptation to cope with oxidative stress following MSH2 mutation . In order to test further if H2O2 resistance in msh2 mutants results from an adaptation process that occurred in insect life stages of T . brucei , we re-expressed MSH2 in both the BSF and PCF msh2-/- cells , using a previously described construct and conditions [21] . Integration of the MSH2 re-expression construct was confirmed by PCR ( S6 Fig ) , and southern blot in BSF [21] . Both BSF and PCF msh2 mutants display increased tolerance to MNNG ( Fig 2A ) , and re-expression of MSH2 in BSF msh2-/- mutants reverts this tolerance to the levels of msh2+/- mutants [21 , 38] . As shown in Fig 6A , re-expressing MSH2 ( Tbmsh2-/-/+ ) in the PCF msh2-/- mutants also resulted in levels of MNNG survival similar to msh2+/- cells . In addition , and as seen in T . brucei BSF msh2-/-/+ cells [21] , PCF msh2-/-/+ cells no longer showed detectable microsatellite variation in clonal growth assays ( S7 Fig ) . Taken together , these assays indicate that MMR function can be restored in T . brucei msh2 null mutants in both life cycle stages after re-introduction of MSH2 into the genome . In contrast , MSH2 re-expression had a different outcome for H2O2 sensitivity in the two life cycle stages . When T . brucei PCF msh2-/-/+ cells were grown in the presence of 10 μM or 20 μM H2O2 for 48 or 72 hrs , there was no significant difference in survival relative to the msh2-/- mutants , and survival was significantly different from the msh2+/- mutants ( Fig 6B ) . However , in BSF T . brucei , the survival of the msh2-/-/+ cells ( in this case after 48 hrs growth in either 100 or 200 μM H2O2 ) was indistinguishable from the msh2+/- cells and significantly greater than the msh2-/- mutants ( Fig 6C ) . Thus , while re-expression of MSH2 in T . brucei msh2-/- null mutants was able to restore MMR function in both life cycle stages , the same re-expression was able to revert the increased sensitivity to H2O2 only in BSF msh2-/- mutants . In contrast , the increased tolerance to H2O2 observed in PCF after loss of MSH2 could not be reverted by re-expressing this gene in this life cycle form of T . brucei . This lack of MSH2 complementation is most simply explained by changes in expression or function of another factor ( s ) that allowed PCF MSH2 mutants to cope specifically with oxidative stress , though we cannot rule out the possibility of this specific phenotypic difference between BSF and PCF cells arising due to differing levels of MSH2 in the two life cycle stages and in the msh2-/-/+ re-expressers . As suggested by RNAi data ( S8 Fig ) , the adaptation process that may have occurred during the cloning period needed to generate the msh2-/- mutants requires several generations . When MSH2 expression is abruptly inhibited by tetracycline induction of siRNA in T . brucei PCF cells , a discernible slowing of growth is observed as a consequence of the reduced msh2 mRNA expression . In this study , and in previous work [37] , we have shown that deletion of msh2 results in increased levels of 8-oxoG in both the nDNA and kDNA . Indeed , in BSF T . brucei the most pronounced cell cycle effect of MSH2 loss , which is exacerbated by H2O2 treatment , is the accumulation of cells with reduced amounts of kDNA ( evaluated by DAPI staining ) [37] . Because of these findings , and coupled with lack of a detectable kinetoplastid homologue of MSH1 ( a MutS-like factor involved in mitochondrial genome repair , including oxidative damage repair ) [53 , 54] , we hypothesized that MSH2 could provide a repair function for the trypanosomes’ mitochondrial ( kDNA ) genome . To test this hypothesis , we expressed T . brucei and T . cruzi MSH2 as C-terminal fusions with a 12X c-MYC epitope . For T . brucei , MSH2-myc was expressed from the endogenous locus in both BSF and PCF cells in which the other MSH2 allele was deleted; by evaluating MNNG sensitivity , we showed that the epitope tag did not affect the function of MSH2 in BSF cells ( S9 Fig ) . As shown Fig 7A and 7B , immunolocalization of MSH2:myc with anti-c-MYC antiserum in T . brucei BSF and PCF cells revealed only a nuclear signal . The same nuclear localization was found in T . cruzi epimastigotes expressing MSH2:myc , as well as in amastigotes obtained after infection of Vero cells ( Fig 7C and 7D ) . No changes in subcellular localization of the tagged MSH2 protein were observed in T . cruzi epimastigotes expressing MSH2:myc after exposure to H2O2 ( Fig 7E ) or other genotoxic agents , such as MNNG and cisplatin .
In previous studies we have described the phenotypic effects of deleting both alleles of MSH2 or MLH1 in T . brucei BSF cells , and the effects of loss of a single allele of MSH2 in T . cruzi epimastigotes [21 , 37] . Here , we provide several new insights into the function of MMR in African and American trypanosomes . First , we show that genetic ablation of MSH2 or MLH1 is possible in T . brucei PCF cells , as is MSH2 ablation in T . cruzi epimastigotes . In all cases , loss of MSH2 results in detectable impairment in MMR , as demonstrated by the increased tolerance to the alkylator MNNG , a phenotype specifically seen in MMR mutants in other eukaryotes [55] and in T . brucei BSF cells [21] . Second , we reveal a striking life cycle dependent difference in the effect of MSH2 ablation in T . brucei: in PCF cells loss of MSH2 results in increased tolerance to H2O2 , whereas MSH2 loss results in increased sensitivity in BSF cells [38] . The same increased tolerance is also seen in T . cruzi epimastigote MSH2 mutants , where it impacts on the capacity of the parasite to grow in ROS-producing host macrophages . Importantly , altered H2O2 resistance was not observed when T . brucei BSF or PCF cells lacking MLH1 were examined . Finally , we provide evidence that the increased resistance to H2O2 in T . brucei after loss of MSH2 is due to a life cycle dependent adaptation in a facet of the cell that is distinct from MSH2 , since re-expression of the protein restores MMR activity in PCF cells but does not alter the response to H2O2 . In contrast , re-expression of MSH2 in T . brucei BSF msh2-/- mutants reverts both MMR impairment and H2O2 sensitivity . Despite the complexity of phenotypes observed after MMR mutation , the findings indicate a common function of MSH2 in both trypanosomes: in addition to its role as a key component of MMR , MSH2 is also directly involved in the response to oxidative stress . Since loss of MLH1 did not result in increased resistance to H2O2 in PCF T . brucei , our new data confirms previous indications from BSF T . brucei [38] that although MSH2 acts in the parasite’s response to oxidative stress , such a role is unlikely to involve execution of MMR on oxidative lesions through MLH1-directed functions . Indeed , this is supported by the observation that PCF T . brucei MSH2 mutants , but not MLH1 mutants , display increased levels of 8-oxoG , a known form of oxidized base damage [56] , in their nuclear and mitochondrial genomes . The same accumulation of 8-oxoG is also seen in T . cruzi msh2-/- and msh2+/- mutants [37] , indicating that such a role for MSH2 is conserved in the two trypanosomes species . Most likely , a separation of function between MSH2 and MLH1 in this role will also be found in T . cruzi , though this has not to date been tested . The nature of MSH2’s role in responding the oxidative damage remains unclear , including whether or not it is limited to acting upon or repairing 8-oxoG . One possibility is that MSH2 acts in conjunction with MSH6 to repair 8-oxoG in DNA , a known activity of this heterodimer in other eukaryotes that can act independently of downstream MMR components [32] . However , we also observe accumulation of 8-oxoG in the kDNA of T . brucei and T . cruzi MSH2 mutants , consistent with previous descriptions of kDNA loss in T . brucei BSF msh2-/- mutants [37] , and it is not clear that MSH2-6 could direct such a repair role in the mitochondrion . A broader role for MSH2 in the oxidative stress response might therefore need to be considered , perhaps related to findings in other eukaryotes that MSH2-6 can act to signal the presence of various forms of DNA damage , for instance through ATR [57–59] . It remains puzzling , however , that much of the signaling and wider activities attributed to MSH2-6 in other eukaryotes appear to reside in the extended N-terminal domain of MSH6 [59] , which is notably truncated in trypanosomatid MSH6 orthologues [21] . Nonetheless , such a role for MSH2 perhaps most readily explains the adaptation we propose in T . brucei PCF , but not in BSF cells after loss of MSH2 . PCF T . brucei have active mitochondrial metabolism , unlike BSF , and therefore greater levels of endogenous ROS , meaning that loss of MSH2 may be more detrimental in this life cycle stage [39] . T . cruzi epimastigotes also have an aerobic metabolism relying on mitochondrial respiration [60] , and it is thus tempting to speculate that the same adaptation most likely occurred during the generation of msh2 null mutants in T . cruzi epimastigotes; though we have no direct evidence for such adaptation , the selection of cells lacking both alleles was notably problematic and necessitated an altered targeting transfection approach for removing the second allele . To date , our analysis of the consequences of T . brucei MMR mutation have only been conducted in vitro , meaning it remains possible that the life cycle differences , and in particular the proposed PCF adaptation to MSH2 loss , are due to culture conditions rather than environmental and metabolic changes as the parasite cycles between host and vector . However , we provide direct evidence that the increased capacity to survive oxidative stress observed in T . cruzi msh2 -/- mutants may reflect challenges faced by this parasite during its life cycle . Although no difference in infectivity was observed between T . cruzi WT cells and msh2-/- mutants in Vero cells , macrophages infected with T . cruzi msh2-/- mutants contained almost 3-fold more intracellular amastigotes than macrophages infected with WT parasites . Due to their phagocytic nature , macrophages naturally produce ROS through the activation of NADPH oxidase during phagocytosis or by stimulation with a wide range of infective agents [61] . Although ROS are expected to be involved in pathogen elimination , increasing evidence suggests that ROS production actually could enhance T . cruzi infection in macrophages . For instance , it was recently proposed that oxidative stress mobilizes cellular iron and fuels T . cruzi infection [62 , 63] . A role for ROS as a signalling molecule has also been highlighted in studies with Leishmania , where low ROS concentrations regulate proliferation and differentiation by modulating the activity of cellular targets by oxidation [64] . It seems reasonable to assume that MSH2 is part of the arsenal of functions that trypanosomatid parasites are equipped with to withstand and detect oxidative stress during their natural life cycles , and the absence of MSH2 can have wider effects than simply loss of MMR , as reflected in the adaptation we suggest in PCF T . brucei . What is the nature of the adaptation following MSH2 mutation ? Answering this question is complicated by the multiple potential pathways that might be affected . One possibility is that loss of MSH2 necessitates the up-regulation of an alternative repair pathway , such as base excision repair ( BER ) . BER may be an attractive option because it is known to respond to oxidative stress and , indeed , a DNA glycosylase termed OGG1 is found in many organisms [65–67] , including T . cruzi [68] , that acts on 8-oxoG . However , increased BER activity seems incompatible with the increased levels of 8 oxoG we detect in T . brucei and T . cruzi MSH2 mutants . These data indicate that increased oxidative damage to nucleic acids occurs in the mutants and therefore suggests that the cells might adapt by limiting their exposure to oxidative stress in other ways . Trypanosomes have a complex set of enzymes involved in the oxidative stress response . One such pathway distinct from the mammalian host is based on trypanothione metabolism [69] . A paradox in our study is that we can only find evidence for a nuclear localization of MSH2 , even after exposure to H2O2 . Most oxidative damage is likely to occur in the trypanosome mitochondrion , as this is the major source of ROS . However , if MSH2 is limited to the nucleus , then how does loss of MSH2 result in ( as noted above ) increased levels of 8 oxoG in the kDNA ? Moreover , if even some of the adaptation we see after loss of MSH2 affects trypanothione metabolism , then how is the loss of a nuclear protein communicated to these enzymes , which are thought to be mitochondrial or cytoplasmic [70–74] ? One possibility is that C-terminal tagging impairs mitochondrial localization or MSH2 function . In BSF cells , we can rule this out because MSH2-myc was shown to be functional in the response to MNNG treatment ( S9 Fig ) . However , the same analysis has not been conducted in PCF T . brucei , where perhaps mitochondrial localization is more important or pronounced . An alternative explanation is that trypanosome MSH2 , perhaps in conjunction with MSH6 , does indeed provide a role in signaling damage , similar to the activities detailed in other eukaryotes . Whether such signaling is limited to oxidative damage is unknown , but the signal provided by MSH2 may be communicated , in ways still to be determined , beyond the nucleus . Hence , if MSH2 is ablated , this element of the signaling cascade is lost . In the insect stages of at least T . brucei this loss is more deleterious than in the mammal , necessitating the selection for metabolic adaptation to deal with an altered oxidative stress response , with the consequence that the mutant becomes more resistant to ROS . The same hypothesis applies to T . cruzi since similar phenotypic changes were also seen in T . cruzi epimastigote MSH2 null mutants . Clearly , further studies will be needed to understand how the parasites adapt to MSH2 mutation and it may be that metabolomic or proteomic approaches are the best strategies to take , in particular if no compensatory genetic changes follow MSH2 mutation . Nonetheless , this work reveals surprising complexity in the outcome of mutation to a core DNA repair pathway , suggesting interconnections with other cellular pathways . In addition , this study potentially reveals life cycle-dependent differences in MMR function . Loss of BRCA2 has also been shown to have different effects on genome stability in T . brucei BSF and PCF cells [75] , but the extent to which the wide range of DNA repair pathways in trypanosomatids can vary in their activity or use through the life cycle remains little explored .
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Trypanosoma brucei and Trypanosoma cruzi are protozoa parasites that cause sleeping sickness and Chagas disease , respectively , two neglected tropical diseases endemic in sub-Saharan Africa and Latin America . The high genetic diversity found in the T . cruzi population and the highly diverse repertoire of surface glycoprotein genes found in T . brucei are crucial factors that ensure a successful infection in their hosts . Besides responding to host immune responses , these parasites must deal with various sources of oxidative stress that can cause DNA damage . Thus , by determining the right balance between genomic stability and genetic variation , DNA repair pathways have a big impact in the ability of these parasites to maintain infection . This study is focused on the role of a DNA mismatch repair ( MMR ) protein named MSH2 in protecting these parasites’ DNA against oxidative assault . Using knock-out mutants , we showed that , besides acting in the MMR pathway as a key protein that recognizes and repairs base mismatches , insertions or deletions that can occur after DNA replication , MSH2 has an additional role in the oxidative stress response . Importantly , this extra role of MSH2 seems to be independent of other MMR components and dependent on the parasite developmental stage .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Distinct Phenotypes Caused by Mutation of MSH2 in Trypanosome Insect and Mammalian Life Cycle Forms Are Associated with Parasite Adaptation to Oxidative Stress
|
Comparison of protein structures is important for revealing the evolutionary relationship among proteins , predicting protein functions and predicting protein structures . Many methods have been developed in the past to align two or multiple protein structures . Despite the importance of this problem , rigorous mathematical or statistical frameworks have seldom been pursued for general protein structure comparison . One notable issue in this field is that with many different distances used to measure the similarity between protein structures , none of them are proper distances when protein structures of different sequences are compared . Statistical approaches based on those non-proper distances or similarity scores as random variables are thus not mathematically rigorous . In this work , we develop a mathematical framework for protein structure comparison by treating protein structures as three-dimensional curves . Using an elastic Riemannian metric on spaces of curves , geodesic distance , a proper distance on spaces of curves , can be computed for any two protein structures . In this framework , protein structures can be treated as random variables on the shape manifold , and means and covariance can be computed for populations of protein structures . Furthermore , these moments can be used to build Gaussian-type probability distributions of protein structures for use in hypothesis testing . The covariance of a population of protein structures can reveal the population-specific variations and be helpful in improving structure classification . With curves representing protein structures , the matching is performed using elastic shape analysis of curves , which can effectively model conformational changes and insertions/deletions . We show that our method performs comparably with commonly used methods in protein structure classification on a large manually annotated data set .
Comparison of protein structures ( or structure alignment ) is an important tool for understanding the evolutionary relationships between proteins , predicting protein structures and predicting protein functions [1] , [2] . In annotating functions of new proteins , such as those solved in structural genomics projects , sequence alignment methods may not be sufficient to identify functionally related proteins when the sequence identities between the query protein and its related proteins are low ( i . e . lower than 20% ) [3] . Comparing their structures provides an effective means of annotating protein functions based on the structural similarity of proteins since homologous proteins are more conserved in their structures than sequences [4] . To organize proteins by the similarity of their backbone structures , databases , such as SCOP [5] , [6] , CATH [7] , [8] and FSSP [9] were built for all proteins of known structures in the protein data bank ( PDB ) [10] by manual annotation [5] , [6] , automatic classification [9] or combination of the two [7] , [8] . As the structure information is increasing at an accelerated speed , human annotations have become more time and resource consuming . Automatic structure alignment methods developed in the past [11]–[36] can be largely divided into several categories according to the specific similarity metrics ( distances ) they aim to optimize to achieve the best alignment . The particular metric used reflects the emphasis of the method on what constitutes a good alignment between two structures . When using the same similarity measures , methods differ by how they achieve the optimal solution through various search algorithms . Several studies have been performed to comprehensively compare different structure alignment methods [37]–[39] . The conclusions from these studies are that there is still room for improvement in structure alignment and there is no common standard for assessing the quality of alignment . Different criteria tend to rank methods differently and for a particular purpose one method may work better than the others . But , in general , no one method works better than others for all purposes . Despite extensive studies in the past , structure alignment , especially flexible structural alignment ( i . e . one of the structures has undergone some conformational changes ) , continues to be a very challenging problem [37]–[39] . Another problem in structure alignment is to assess the statistical significance of the similarity between two protein structures . This problem is partly due to the lack of a proper metric for measuring the distance between two protein structures [40] . The root-mean-square-deviation ( RMSD ) of aligned parts between two structures has been commonly used to measure the similarity between pairs of protein structures after they are superposed . However , RMSD is not a proper distance when different sets of atoms are used to align different pairs of structures . Other similarity scores have also been used to derive statistical methods for evaluating significance of similarities . They suffer from the same drawback of RMSD as not being proper distances . In addition , a problem with many of the current metrics is that the best alignment between two structures , corresponding to the minimum value of the alignment metric used , cannot be obtained easily . Heuristic methods are often used to search the alignment space to find the best alignment , producing approximate minimum distances with possible biases . A previous study aiming to develop a statistical framework for structure alignment [41] inferred the probability distribution of similarities of unrelated proteins by performing large scale alignment of protein structures . The resulting pair-wise alignment scores are then fitted to an extreme value distribution . It has also been pointed out that in these frameworks , the commonly used metric RMSD does not lead to as reliable a measure of structural significance compared to some “less proper” distances such as the alignment scores [41] . This raised some concerns over these statistical frameworks . In this study , we develop a mathematical framework for protein structure comparison using a formal distance , a geodesic distance based on a particular Riemannian metric . Geodesic distances in elastic shape analysis have been used widely in shape analysis in computer vision [42]–[45] . An advantage of this approach is that the dynamic-programming algorithm can efficiently compute the optimal alignment between two protein structures . In this framework , we consider protein backbones as continuous three-dimensional curves . The alignment of two protein structures then becomes alignment of the two curves derived from the two backbone structures . Curves can bend and stretch readily during alignment so that the flexibility of and variations among protein structures can be adequately accounted for . Our goal is to develop a comprehensive framework for statistical analysis of protein structures . This framework can: ( 1 ) Generate optimal matching of protein backbone structures using shape information , where a formal distance , geodesic distance , is computed as a measure of the dissimilarity between shapes of any two protein structures . The optimal matching of two structures , computed by dynamic programming algorithm , gives the minimum distance among all possible matchings of two structures . ( 2 ) Compute statistical averages of a collection of structures using geodesics and geodesic distances . Such tools can be further advanced to define statistical models for capturing variations in protein conformations and for classifying future discoveries into pre-determined classes . That is , one can generate mean and covariance associated with a set of protein structures and characterize the central behavior of a population . ( 3 ) Generate optimal deformation of one backbone into another using geodesic path in the shape space . This work is an extension of a recent framework for comparing shapes of curves in Euclidean spaces , called the elastic shape analysis [42] , [43] , [46] . The rest of this paper is organized as follows . We first describe the mathematical framework that is behind our approach to protein structure comparison . We then use some examples to illustrate this method in pair-wise structure alignment and in computing mean and covariance of a group of protein structures . We further demonstrate the performance of our method using a large-scale classification of proteins in SCOP database and compare our performance with some commonly-used methods . Finally , we conclude the paper with discussions .
We treat the backbone structure of a protein as a parameterized curve in R3 . Given any two such parameterized curves , we desire a framework that can quantify the differences in shapes of these two curves . Since the comparisons involve shapes of proteins , the resulting quantifications should not depend on the rigid motions and parameterizations of these curves . We will use a Riemannian framework for this task and the basic idea in this approach is the following . We represent each parameterized curve by a special function called the square root velocity function ( SRVF ) and restrict to the manifold of such functions under the desired constraints . In order to compare shapes of curves , we have to remove all the shape-preserving transformations from this representation . This is done using an algebraic technique – we form a quotient space of the original manifold with respect to these shape-preserving transformation groups . In the resulting quotient space , called the shape space of elastic curves , one can perform statistical analysis of curves as if they are random variables . One can compare , match , and deform one curve into another , or compute averages and covariances of curve populations , and perform hypothesis testing and classification of curves according to their shapes . The mathematical details are provided next .
In this section , we present the performance of our method on a large scale protein structure classification using structures from SCOP database and compare our results with CE [12] and Matt [25] . We selected a subset of non-homologous proteins from SCOP database with pair-wise sequence identity smaller than 40% from the four largest classes ( with at least 5 members ) at top level of SCOP hierarchy ( all alpha , all beta , alpha/beta and alpha+beta ) . Classes at the bottom level ( family level ) with less than 20 members are ignored . This gave us a set of 1579 proteins in total . We calculated the pair-wise geodesic distances among these protein structures and clustered them into different classes . Hierarchical clustering is done using the cluster function in Matlab and average linkage is used to calculate distances among clusters . When number of clusters , n , is provided , the hierarchical clustering results can be easily divided into n classes . For CE and Matt , we used ( 1−score/score_max ) as the distance , where score is either z-score provided by CE or a matching score provided by Matt , and score_max is the maximum z-score ( for CE ) or maximum matching score ( for Matt ) among all pairwise scores . Using the scores directly gave worse performances . We then used random index ( RI ) as a criterion to evaluate the accuracy of our classification . RI measures the percentage of correct decisions by looking at all pair-wise decisions , which is the ratio ( ( TP+TN ) / ( TP+TN+FP+FN ) ) , where TP is true positive for a pair of proteins , which are in the same class in SCOP and classified into the same class , and TN ( True Negative ) , FP ( False Positive ) , FN ( False Negative ) are defined similarly . In Table 1 , we compare the performance of our method with CE and Matt . To show how the methods perform for different types of proteins classified at the top level , we also show the results for these classes . We can see from Table 1 that our method , without using any secondary structure information , is comparable with CE and Matt overall . It is interesting that these methods have quite different performances for some protein classes . An example that illustrates the strength of our method is protein pair 1ycc and 1gu2 , which have a small geodesic distance ( 0 . 84 ) and are correctly classified into the same family by our method . For these two proteins , CE gives a small z-score ( 2 . 6 ) and classifies them into different classes . DaliLite and Mammoth give z-scores of 3 . 2 and 1 . 6 , respectively ( small scores imply large distances ) . Matt , a method for flexible protein alignment , gives a p-value of 0 . 03 showing the two proteins have statistically significant similarities . The rigid alignment of the two proteins by Mammoth is shown in the left panel of Fig 6 and matching of the two proteins by ESA is shown in the right of Fig 6 . One can see that a rigid alignment aligns the two proteins rather poorly . On the other hand , flexible alignment methods like Matt and ours can match them quite well . Finally we compared the running time of our method with several other methods . Table 2 shows the comparison of running time of CE , Matt , MUSTANG and ESA on three pairs of proteins with around 100 , 200 and 300 residues , respectively . All the programs were run using the same computer .
In summary , we have developed a mathematical framework for protein structure comparison based on elastic shape analysis , a method originally developed in the field of computer vision and image analysis . Under this framework , protein structures are compared as three dimensional elastic curves and can be treated as random variables for statistical analysis . Mean and covariance of a group of protein structures can be computed . Probability distributions can be built for a population of protein structures and hypothesis testing can be conducted for a protein structure against a known protein family/class . Although protein structures have been studies for many years and many computational methods have been developed for protein structure comparison , as far as we know , this is the first rigorous mathematical framework that can address the above computations . It is worth mentioning that although we consider protein structures as three dimensional curves in this study and ignore the sequence and local structure features ( such as secondary structures ) , the framework can readily incorporate amino acid sequence or secondary structure information . Such additional information can be very helpful to achieve better alignment . For example , secondary structure information has been used by many structure alignment methods since secondary structure type is the major feature used in manual structure classification . To incorporate such auxiliary information we can construct continuous auxiliary functions along the curves , derived from the additional information . The matching and deformations can then be performed using the higher dimensional composite curves that are formed by concatenating the geometric and the auxiliary coordinates . The distances obtained are still proper distances on the higher dimensional space . In this matching , one needs to adjust the relative magnitude ( weight ) of the geometric and auxiliary coordinates , which can be problem dependent . With secondary structure type as auxiliary function , we can force protein fragments with the same secondary structure type to match with each other by giving a larger weight on the auxiliary secondary structure information , which may further improve the accuracy of structure classification . When using sequence as auxiliary information , one can perform alignment on both structure and sequence space by using an amino acid substitution matrix ( for instance , BLOSUM62 matrix ) as the distance measure for amino acid residues along the chains . One can also force all corresponding residues to match with each other when comparing two protein structures with the same sequence . The geodesic path ( deformation from one structure to another ) generated using such constraint may then have a more natural physical interpretation . In this study we focused mainly on pairwise protein structure comparison and studying the basic properties of a population of structures such as means and covariances . The framework can also be applied to study multiple structure comparison ( multiple structure alignment ) and provide an alignment of multiple structures if it is desirable . To do so , we can calculate the mean structure of the multiple structures and align each structure to the mean structure . The mathematical framework also provides principled ways to deal with more complex situations . For example , in the troublesome case that there is one or more structures that are very different from the rest of the structures to be aligned , outliers can be detected based on the mean and covariance structure of the population . In constructing a probability distribution from a group of structures , we chose the tangent space of our shape space and assumed Gaussian distribution on this space . The shape spaces ( ours and most other formally defined shape spaces ) are highly nonlinear manifolds and it is difficult to build distributions on them directly . On the other hand , it is a very common practice to impose probability distributions on the tangent space since they are linear ( vector ) spaces . The mapping between a tangent space and the manifold can be made a bijection by putting some appropriate constraints on the tangent space . As for the choice of Gaussian distribution , we have not validated it on the tangent spaces of our shape space . Our goal in this study is to demonstrate the computation of the second moment for observed shapes and to suggest the simplest probability model that captures the first two moments , i . e . a multivariate normal . One can easily extend this framework to include mixtures of Gaussian models [52] or even generalized Gaussian models and we expect them to better match the observed variability of the protein structures . These extensions can be explored in future studies . Since we represent protein structures as curves , our method mainly deals with the type of structure comparison where sequence order of amino acid residues is relevant to the distances of structures ( sequential structure alignment ) . In general , our method is not good at detecting related proteins whose differences are caused by changes such as domain swapping , or domain insertion/deletion . However , the method can be readily modified to compare circular permuted proteins [33] by linking the C-terminal and N-terminal ends of a protein ( for example , using a straight line ) and cutting the protein in the middle , preferably at residues linking domains or secondary structure fragments . To deal with domain insertion/deletion/swapping , we can use the algorithm in [33] , where this problem is formulated as a mixed-integer programming problem , to select near optimal combination of fragments before calculating geodesic distances . If domain swapping or deletion/insertion can be detected or predicted ( i . e . using sequence based methods ) , cuts and reconnections can also be done at corresponding positions to allow for even more flexible structure comparisons .
|
Protein structure comparison is important for understanding the evolutionary relationships among proteins , predicting protein functions , and predicting protein structures . Despite its importance , there have been no rigorous mathematical or statistical frameworks for protein structure comparison . One notable issue in this field is that with many different similarity measures used in comparing protein structures , none of them are proper distances when protein structures of different sequences are compared . In this study , we develop a mathematical framework for protein structure comparison by treating protein structures as three dimensional curves . A formal distance , geodesic distance , can be computed for any two protein structures . In this framework , population-specific variations within protein families can be characterized through building probability distributions for structures of protein families . The mean and covariance computed from groups of protein structures can also help to improve the classifications of protein structures . With curves representing protein structures , the matching is performed using elastic shape analysis of curves , which can effectively model conformational changes and insertions/deletions .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"computational",
"biology/macromolecular",
"structure",
"analysis"
] |
2011
|
A Mathematical Framework for Protein Structure Comparison
|
The worldwide production of maize ( Zea mays L . ) is frequently impacted by water scarcity and as a result , increased drought tolerance is a priority target in maize breeding programs . While DREB transcription factors have been demonstrated to play a central role in desiccation tolerance , whether or not natural sequence variations in these genes are associated with the phenotypic variability of this trait is largely unknown . In the present study , eighteen ZmDREB genes present in the maize B73 genome were cloned and systematically analyzed to determine their phylogenetic relationship , synteny with rice , maize and sorghum genomes; pattern of drought-responsive gene expression , and protein transactivation activity . Importantly , the association between the nucleic acid variation of each ZmDREB gene with drought tolerance was evaluated using a diverse population of maize consisting of 368 varieties from tropical and temperate regions . A significant association between the genetic variation of ZmDREB2 . 7 and drought tolerance at seedling stage was identified . Further analysis found that the DNA polymorphisms in the promoter region of ZmDREB2 . 7 , but not the protein coding region itself , was associated with different levels of drought tolerance among maize varieties , likely due to distinct patterns of gene expression in response to drought stress . In vitro , protein-DNA binding assay demonstrated that ZmDREB2 . 7 protein could specifically interact with the target DNA sequences . The transgenic Arabidopsis overexpressing ZmDREB2 . 7 displayed enhanced tolerance to drought stress . Moreover , a favorable allele of ZmDREB2 . 7 , identified in the drought-tolerant maize varieties , was effective in imparting plant tolerance to drought stress . Based upon these findings , we conclude that natural variation in the promoter of ZmDREB2 . 7 contributes to maize drought tolerance , and that the gene and its favorable allele may be an important genetic resource for the genetic improvement of drought tolerance in maize .
Maize is one of the most planted crops world-wide and has tremendous value for providing food , forage , pharmaceuticals , and other industrial products . Its productivity is frequently hampered by water scarcity and so improved drought tolerance is an important goal in many breeding programs . Considerable research has been conducted to better understand the genetic and molecular basis for drought tolerance in plants with the idea that this research will provide information that will greatly increase the efficiency of traditional breeding programs to select for drought tolerance through the use of molecular markers . Alternatively , this research can be used to identify specific genes that can be used to improve drought tolerance using transformation technologies . Abiotic stress research in Arabidopsis has revealed two major ABA-dependent and ABA-independent signaling pathways , that control stress-inducible gene expression . DREBs/CBFs ( Dehydration Responsive Element Binding proteins/C-repeat Binding Factors , hereafter referred as DREBs ) are thought to be the major transcription factors ( TFs ) that control stress-inducible gene expression in the ABA-independent pathway [1] . DREB TFs , belonging to the APETALA2/Ethylene-Responsive Factor ( AP2/ERF ) superfamily of TFs , are able to bind a Dehydration Responsive Element ( DRE , core motif: A/GCCGAC , also known as a C-repeat and low-temperature-responsive element [2]–[4] , in the promoter region of many drought and/or cold stress-inducible genes . They were first identified using a yeast one-hybrid system to screening for the trans-factors of the DRE element identified in a set of drought and cold-inducible gene promoters [5] , [6] . There are two groups of DREB genes in the Arabidopsis genome ( DREB1s and DREB2s ) that are composed of six and eight members , respectively [7] . Ectopic or selective expression of DREB1A/CBF3 can significantly enhance plant tolerance to multiple abiotic stresses , including drought , freezing and high salinity [6] , [8] . Over-production of a constitutive active form of DREB2A ( DREB2A-CA ) protein conferred significant both drought and heat tolerance in transgenic plants [9] , [10] . Thus , distinct from DREB1 , post-translational modification of the DREB2A protein was demonstrated to finely modulate its abundance and activity [11] . In plants , the DREB gene family consists of multiple genes . Although they are primarily involved in the regulation of water-stress-related gene expression , other functions have been noted for specific DREB genes . For example , DREB1D/CBF4 plays a role in plant drought stress tolerance which is in contrast to the homologous DREB1A/CBF3 gene that functions in cold response [12] . DREB1C/CBF2 has been characterized as a negative , but not a positive , regulator of plant cold stress response by tightly controlling DREB1A/CBF3 and DREB1B/CBF1 expression [13] . DREB2C has been reported to play a role in heat rather than drought tolerance [14] . The functional divergence of different DREB genes has proven to be an attractive and challenging topic of research . Studies in other species , such as rice , tomato , soybean , wheat , barley and maize , suggest that DREB genes play a central role in plant stress response [15] , [16] . In maize , two DREB genes ( ZmDREB1A and ZmDREB2A ) belonging to the DREB1 and DREB2 subgroups , respectively , were cloned and demonstrated to be upregulated in response to plant water stress [17] , [18] . It was found that , distinct from Arabidopsis DREB2A , ZmDREB2A gene expression in response to abiotic stress was regulated via an alternative splicing mechanism and that the expressed protein could directly activate downstream gene expression [18] . Similar findings in rice , wheat and barley , indicate the presence of a mechanism that finely modulates the activity of stress-inducible TF genes and suggest that the molecular mechanism is different in monocot and dicot plants [19]–[21] . Other homologous DREB genes in maize have not been identified and characterized . Although DREB genes play an important role in plant response to water stress , several important questions remain and require further research . For instance: is the natural variation in DREB genes directly associated with levels of drought tolerance in a plant; which DREB gene is the most important for the genetic improvement of drought tolerance; can a favorable allele or alleles of a key DREB gene be identified in order to facilitate molecular breeding programs which aim to select for drought tolerance ? Answering these questions will not only facilitate the genetic improvement of drought tolerance but will also increase our knowledge of the biological function of this gene family . With the completion of the sequencing of the maize B73 genome , it is now possible to identify all maize DREB genes and systematically evaluate their contribution to drought tolerance . Association studies , based on genetic disequilibrium linkage ( LD ) , provide a novel approach for dissecting complex trait loci in plants [22]–[25] . Moreover , maize is thought to be an ideal plant species due to its high level of genetic diversity and quick LD decay , which was estimated to be within several kilobases ( kbs ) among maize landraces [26] . This feature makes the resolution of genome-wide association studies ( GWAS ) more precise at the gene level than that in self-pollinated plant species , provided that high-density and genome-wide DNA markers are available [27] , [28] . Candidate gene association analysis is made possible with high-throughput technology which enables the discovery and detection of DNA polymorphisms ( e . g . Single Nucleotide Polymorphism , SNP ) and ensures that markers are within or closely-linked to genes contributing to complex traits [27] . Therefore , this strategy has been widely used in human and animal systems and successfully applied to detect allelic diversity of genes controlling alpha-tocopherol and β-carotene content , aluminum tolerance , kernel size , and fatty acid content in maize and/or rice , given that proper statistic models were employed [29]–[36] . Additionally , after genome-scale resequencing large numbers of varieties with different genetic backgrounds , GWAS accelerates the genetic dissection of complex traits in crops [37]–[39] . In the present research , eighteen maize ZmDREB1 and ZmDREB2 genes were cloned and analyzed to determine their phylogenetic relationship , chromosomal synteny with rice and sorghum , pattern of gene expression in response to drought stress , and their protein transactivation activity . Importantly , the association between the genetic variation of each ZmDREB gene with drought tolerance was evaluated using a diverse population of maize consisting of 368 varieties from tropical and temperate regions . A strong association between ZmDREB2 . 7 gene sequence variance and the degree of drought tolerance at seedling stage was detected . Differences in the promoter region of ZmDREB2 . 7 , but not the protein coding region itself , was associated with distinct patterns of gene induction in response to drought stress in the different maize varieties . Moreover , a favorable allele of the ZmDREB2 . 7 gene was identified in drought-tolerant varieties .
In order to identify all genes encoding ZmDREBs in maize , multiple searches were first performed for all maize genes encoding AP2/ERF TFs using various plant TF databases . The corresponding sequences were then downloaded from the 5b . 60 version of the maize genome sequence database ( http://www . maizegdb . org/ ) . Additionally , DREB orthologous genes from Arabidopsis , rice and sorghum were also identified and downloaded . All of the resultant sequences were then pooled and redundancies were eliminated . Every sequence was manually examined to determine the number and exact location of the AP2/ERF DNA domains . In total , 210 proteins containing AP2/ERF domain ( s ) were identified in the maize B73 genome ( Table S1 ) . Based upon the phylogenetic classification of this superfamily in Arabidopsis [7] , 44 of the maize proteins , containing multiple AP2/ERF domains or lacking a conserved WLG motif within the domain , were classified in the APETALA2 subfamily , which is most likely involved in floral organ development . Three of the proteins , containing both AP2 and B3 domains , were classified in the RAV subfamily . Of the remaining 163 proteins , possessing only one AP2 domain , 65 members were classified in the DREB ( A ) subfamily and 98 members were placed in the ERF ( B ) subfamily ( Table S2 ) . The canonical DREB proteins belong to the A-1 ( DREB1 ) and A-2 ( DREB2 ) subgroups within the DREB subfamily . Ten maize genes belonging to each of these subgroups were identified . Due to our interest in these DREB genes , we attempted to clone them from the B73 inbred line of maize . As a result , 18 genes were successfully cloned , and a sequence analysis of the cloned genes showed that they were 100% identical to the annotated gene sequences . All the genes are intronless except that ZmDREB2 . 2 and ZmDREB2 . 1/2A [18] contain one and two introns , respectively . Two of the 20 identified genes , GRMZM2G323172 and GRMZM2G348307 , containing multiple introns , failed to be obtained from the maize cDNA libraries prepared from various normal growing or stressed tissues collected at different developmental stages . A phylogenetic tree of the ZmDREB proteins and their orthologs from rice , sorghum and Arabidopsis was constructed ( Figure 1; Table S3 ) . The previously cloned genes encoding ZmDREB1A and 2A proteins [17] , [18] were renamed as ZmDREB1 . 1 and 2 . 1 , respectively . The DREB1 group consists of 36 proteins , ten each from maize , sorghum and rice , and six from Arabidopsis . Interestingly , the proteins derived from monocots clustered separately from those of dicots . Some proteins from three of the monocot plants examined displayed pairwise correspondences with high bootstrap support , suggesting that these genes are phylogenetically conserved across these species . Furthermore , proteins from maize and sorghum shared a closer phylogenetic relationship than those from maize and rice , which is consistent with the concept that sorghum is a closer relative of maize than rice . The DREB2 group consists of 30 genes , 10 , 5 , 6 and 9 from maize , sorghum , rice and Arabidopsis , respectively . The ABI4 orthologs identified in these four species were found in the DREB2 group and formed a clade . Compared to the DREB1 group , proteins in the DREB2 group are more phylogenetically divergent , with the exception of the ABI4-type proteins that are conserved across all four of the examined species . ZmDREB2 . 4 , 2 . 5 , 2 . 6 and ZmDREB2 . 7 and 2 . 8 most likely represent duplicated genes in maize since only one ortholog of each of these genes could be found in the rice and sorghum genomes . The two genes that failed to be cloned clustered together and orthologs could not be identified in the other species . Based upon these results , it is possible that they are pseudogenes that may have originated as a result of genome duplication in maize and subsequently became dysfunctional over the course of evolution . In summary , ten ZmDREB1 and eight ZmDREB2 genes , including ZmDREB2 . 3/ZmABI4 , were cloned from the B73 inbred line of maize . Since comparative genomic study of gene synteny is indicative of homologous gene function exploration , the colinearity of this gene group within rice , sorghum , and maize genome was explored . Gene colinearity data were collected from the Plant Genome Duplication Database ( PGDD , http://chibba . agtec . uga . edu/duplication , Table S4 ) using ZmDREB genes as anchors . Each genomic syntenic block was defined as the chromosomal segment consisting of multiple homologous genes across species [40] . Genes located on chromosomal segments containing ZmDREB genes shared good synteny with those in rice and sorghum , especially for ZmDREB1 . 7 , 1 . 8 , 1 . 9 , 1 . 10 , 2 . 2 and ZmDREB2 . 3/ZmABI4 ( Figure 2 ) . This indicates that not only the individual genes but these entire chromosomal segments are evolutionally conserved . Two segments on chromosomes 8 and 9 of rice , containing OsDREB1B and 1H , share synteny with two segments in maize on chromosomes 2 and 7 , carrying ZmDREB1 . 1/1A and 1 . 2 , respectively . Interestingly , their orthologs in sorghum are tandem duplicated on a single chromosomal segment . One rice chromosomal block containing OsDREB2C shared synteny with two segments on chromosomes 1 and 4 of maize with its orthologous genes , ZmDREB2 . 7 and 2 . 8 , on each of them . However , only one syntenic block can be found in the sorghum genome ( Figure 2 ) . Another fragment on chromosome 3 of rice containing OsDREB2E is also duplicated on chromosomes 1 and 9 of maize , probably serving as the origin of ZmDREB2 . 4 and 2 . 5 . Additionally , ZmDREB2 . 5 has a tandem duplicated gene , ZmDREB2 . 6 . Although the syntenic segment in sorghum can be identified , SbDREB orthologs could not be found . Based on the collective data , it appears that most of the DREB1 genes existed prior to the divergence of the rice , sorghum and maize genomes , due to the genetic synteny across species; however , some ZmDREB2 genes may have originated from the allotetraploid origin of the maize genome and tandem duplication . In order to better understand the function of each of the ZmDREB genes , their expression profiles were investigated in 15 different tissues of maize plants growing under non-limiting growth conditions . Using transcriptomic data from maize B73 [41] , an expression heatmap was constructed for 17 ZmDREBs plus ZmDREB2 . 3/ZmABI4 in different tissues from 15 developmental stages ( Figure 3A ) . Results indicated that the expression patterns of different ZmDREB genes varied greatly . Transcripts of ZmDREB1 . 6 , 1 . 10 , 2 . 1 , 2 . 2 , and 2 . 4 were constitutively expressed in the various tissues . ZmDREB1 . 6 and 2 . 1 showed a relatively high level of expression compared to the other ZmDREB examined . This result is consistent with a previous report that ZmDREB2 . 1/2A gene activity is regulated by stress-induced alternative splicing and that non-functional transcripts are abundant under non-stress conditions [18] . Evidently , the transcripts of ZmDREB2 . 3/ZmABI4 were highly present in germinating seeds and embryos . Additionally , all ZmDREB1-type genes were found to be relatively highly expressed in roots , and other ZmDREB2 genes exhibited a constitutively low level of expression in different tissues in the B73 variety grown under non-limiting conditions . Next , the expression of all the ZmDREB genes was experimentally examined in leaves and roots of 3-week-old drought-stressed maize seedlings by quantitative real-time PCR analyses . As illustrated in Figure 3B , in the genotype of B73 , a dramatic upregulation of all ZmDREB1 genes was observed in response to dehydration , especially in the roots . The greatest dehydration-inducible gene response was observed in ZmDREB1 . 7 , whose expression was upregulated more than 400-fold in roots , and 300-fold in leaves , relative to expression under normal growing conditions . The induction response of ZmDREB2 genes was lower than that of ZmDREB1 genes . Among the ZmDREB2 genes , only ZmDREB2 . 8 exhibited the highest dehydration-inducible response with about an 80-fold increase in root expression , however , it was not greatly dehydration-inducible in leaves . A clear induction of ZmDREB2 . 3/ZmABI4 gene was observed in dehydrated leaves , even though this gene was shown to be mainly expressed in embryos and during germination under non-stressful growth conditions . The expression of ZmDREB2 . 7 was only slightly upregulated in response to dehydration , exhibiting about a 1 . 4-fold and 2 . 0-fold increase in transcript abundance in drought-stressed leaves and roots , respectively . In contrast to the other ZmDREB genes , expression levels of ZmDREB2 . 2 and ZmDREB2 . 4 decreased in leaves in response to dehydration . Collectively , the data indicate that different ZmDREB genes exhibit variable levels of expression in different tissues and developmental stages of maize , as well as in response to dehydrative stress . These data suggests that ZmDREB genes play diverse roles in maize development and stress response . DREB proteins function as transactivators that regulate the transcription of downstream target genes in response to abiotic stress . The transactivation activity of each ZmDREB protein was characterized using a yeast activation assay . All eighteen genes were subcloned into a yeast expression vector in a fusion of GAL4-DNA binding domain and transformed into yeast reporter cells which harbor a reporter gene , HIS3 , driven by the GAL4 upstream activating sequence . The level of transactivation activity was measured by the ability of the transformed yeast cells grow on a stringent selective medium containing 0–50 mM 3-aminotriazole ( 3-AT ) , which is a competitive inhibitor of HIS3 protein . Results indicated that the ZmDREB proteins can be classified into three groups based upon their levels of transactivation activity ( Figure 4A ) . Three ZmDREB1 ( 1 . 1/1A , 1 . 7 , 1 . 6 ) and four ZmDREB2 ( 2 . 1/2A , 2 . 4 , 2 . 7 , 2 . 8 ) proteins exhibited the highest level of transactivation activity . Five ZmDREB1 ( 1 . 3 , 1 . 4 , 1 . 5 , 1 . 9 , 1 . 10 ) , ZmDREB2 . 5 , and ZmDREB2 . 3/ZmABI4 proteins exhibit moderate levels of transactivation activity as determined by their ability to grow well on the selective medium amended with 10 mM 3-AT . Lastly , four ZmDREB1 ( 1 . 2 , 1 . 8 , 2 . 2 , and 2 . 6 ) proteins exhibited minimal transactivation activity as the yeast cells transformed by these plasmids could only grow on a medium without 3-AT . In order to gain insight into the differences in transactivation activity exhibited by the ZmDREB proteins , the sequence similarity between all of the proteins was examined ( Figure 4B ) . In addition to the conserved AP2/ERF DNA-binding domain , all of the ZmDREB1s proteins commonly shared a number of conserved motifs , such as motifs 3 , 4 , 6 , 7 and 8 . The sequences of ZmDREB2 proteins , however , were more diversified in relative comparison to ZmDREB1 proteins . ZmDREB2 . 1/2A contained motif 3 which was present only in DREB1 proteins but absent in the other ZmDREB2 proteins . ZmDREB2 . 7 and 2 . 8 , which displayed high transactivation activity , shared a similar motif structure . Motif 13 , found in these two proteins , was also present in ZmDREB1 . 7 but not in any other proteins . Although the motif composition of ZmDREB2 . 4 , 2 . 5 and 2 . 6 were highly conserved , the protein transactivation activity of ZmDREB2 . 6 was much lower than ZmDREB2 . 4 and 2 . 5 . Therefore , other unconserved regions or some key amino acid residues of these proteins may be responsible for the observed differences in protein activity . ZmDREB2 . 3/ZmABI4 and ZmDREB2 . 2 share little similarity to the other ZmDREB proteins . These results demonstrated that transactivation activity and motif organization among the different ZmDREB proteins were remarkably distinctive . Taken together with the diverse patterns of gene expression exhibited by these genes , it suggested that ZmDREB genes in maize may have very diversified functions . Previous research reported that ZmDREB1 . 1/1A and 2 . 1/2A are transcription factors that play an important role in the regulation of maize drought-stress response [17] , [18] . In order to further investigate whether the natural variation in any of the genes encoding ZmDREB1 and 2 TFs was associated with the diversity in drought tolerance of maize varieties , an association analysis was conducted for each of the ZmDREB genes . Recently , 525 , 105 high-quality maize SNP markers ( minor allele frequency ( MAF ) ≥0 . 05 ) were identified from transcriptomic sequencing of a maize natural diversity panel consisting of 368 inbred lines from tropical and temperate regions [39] , [42] . These markers were then utilized to characterize the presence of genetic polymorphisms in each of these 18 ZmDREB genes . Among the ZmDREB genes , 14 were found to be polymorphic with 17 SNPs on average identified in each gene . The polymorphic information was currently absent for four genes , due to above 60% missing rate in the genotyping data . ZmDREB2 . 1/2A was found to be the most polymorphic , with 42 SNPs in this natural diversity panel . The drought stress tolerance of each variety was also investigated . The survival rate of seedlings under severe drought conditions was scored . Statistically , the inbred lines from tropical regions exhibited higher survival rates in comparison to those from temperate regions or B73 derivatives ( Figure S1; Table S5 ) . These data supported the hypothesis that varieties existing within the area of origination may possess better and wider resistance than those in cultivated regions . Three kinds of statistical models were applied to identify significant genotypic and phenotypic associations . Specifically , a general linear model ( GLM ) , principle component analysis ( PCA ) , and a mixed linear model ( MLM ) were used in the associations . PCA was applied to correct for spurious associations caused by population structure . MLM incorporated both PCA and a Kinship matrix ( to correct for the effect of cryptic relatedness ) and was considered to be effective for controlling false positives in the association analysis [42]–[45] . The analysis detected significant associations in the genetic variation in ZmDREB2 . 7 and ZmDREB2 . 3/ABI4 under different models . However , ZmDREB2 . 7 was the gene that was the most significantly associated ( −logP = 3 . 07 ) with drought tolerance in this natural variation panel ( Table 1 , Figure S2 ) . In order to fully identify the DNA polymorphism present in the ZmDREB2 . 7 gene , it was re-sequenced in 105 maize inbred lines that were randomly selected from the variation panel . A 2 . 1 kb genomic fragment was sequenced spanning the ZmDREB2 . 7 coding region and both the 5′- , and 3′-untranslated region ( UTR ) . In total , 102 SNPs and 22 insertions or deletions ( InDels ) were discovered including the SNPs previously identified and reported in the RNA-seq data of 368 maize varieties ( MAF≥0 . 05; [39] ) . The association of each polymorphism with drought tolerance was analyzed again using the MLM model and the pairwise linkage disequilibrium ( LD ) of these polymorphisms was calculated ( Figure 5 ) . Results indicated that five newly-identified polymorphisms ( SNP-503 , -260 , -150 and InDel-185 , -154 ) , located upstream from the ATG site , were significantly associated with phenotypic variation , and were in complete LD among these materials . Additionally , three significant , nonsynonymous SNPs ( SNP142 , 436 , 661 ) and a 3-bp InDel141 polymorphisms were found in the coding region . A significant synonymous variation of SNP408 , located in AP2/ERF DNA-binding domain , was also detected , and it was in a strong LD with InDel141 . Two of the nonsynonymous SNPs ( SNP142 and SNP661 ) were in strong LD with the five polymorphisms in the 5′-UTR ( Figure 5A ) . In order to determine whether or not the differences in gene expression or protein activity contribute to drought tolerance , mRNA levels of ZmDREB2 . 7 under favorable , moderate and severe drought conditions were quantified in 73 randomly selected maize inbred lines . It was found that under moderate/early drought stress ( RLWC = 70% ) , ZmDREB2 . 7 gene expression level was positively correlated with increased survivability . However , no significant correlation was observed under either well-watered or severe/late drought conditions ( Figure 5B ) . This observation indicated that an early induction of ZmDREB2 . 7 gene expression in response to drought stress , rather than a basic or slow response , was important for survival of maize plants under drought stress . On the other hand , the protein transactivation assay indicated that changes in amino acids due to the four nonsynonymous mutations in the coding region did not significantly affect protein activity ( Figure S3 ) . In summary the differences in the regulation of ZmDREB2 . 7 expression , but not transactivation activity of the protein , probably contributed to the natural variation in drought tolerance . Therefore , the polymorphism in the 5′-UTR of ZmDREB2 . 7 may be the important functional variation conferring drought tolerance on maize seedlings . To determine whether or not ZmDREB2 . 7 is a typical DREB-type transcription factor and is able to improve plant drought stress tolerance , the protein was purified and tested for its ability to bind to the DRE sequence in vitro . As illustrated in Figure 6A , ZmDREB2 . 7-GST fusion protein could bind both typical DRE sequences , ACCGAC and GCCGAC , with a similar affinity , and the binding signal was specifically inhibited by un-labeled DNA sequences in competitive assays . When compared with ZmDREB2 . 1/2A protein , ZmDREB2 . 7 was found to possess a similar target DNA binding ability . The GCC sequence is the target DNA sequence of the ERF subgroup of TFs within the AP2/ERF superfamily and this sequence is enriched in the promoters of ethylene-responsive or biotic-stress-responsive genes [46] . TINY , one of Arabidospsis AP2/ERF TFs , can bind both DRE and GCC cis-elements equally , thus enabling crosstalk in plant biotic and abiotic stress responses [47] . When the GCC sequence was used in the binding assay , both ZmDREB2 . 1/2A and ZmDREB2 . 7 proteins displayed a very faint binding signal , indicating a low level of binding affinity . Additionally , the band intensity was only slightly weakened in the competitive assay . This indicates that the GCC sequence was not the specific DNA target site of either ZmDREB2 . 1/2A or ZmDREB2 . 7 ( Figure 6A ) . Since overexpression of the Arabidopsis DREB2A gene did not result in a remarkable drought tolerant phenotype in transgenics , which is most likely a result of the instability of the ectopic expressed protein in plant cells [9] , [11] , we were interested to determine whether ectopic expression of the ZmDREB2 . 7 gene was capable of improving stress tolerance . Transgenic Arabidopsis plants overexpressing the ZmDREB2 . 7 gene were created and drought tolerance was observed to be significantly enhanced in all three independent transgenic lines . The survival rate of the vector-transformed control plants was 35% , while the survival of the ZmDREB2 . 7 overexpressing lines ranged from 82–97% ( Figure 6B ) . A dwarf or delayed-flowering phenotype was not observed in most of the ZmDREB2 . 7-OE lines , however , ZmDREB2 . 7-OE9 plants exhibited a slight reduction in the size of rosette leaves , which had the highest level of transgene expression ( Figure 6B ) . Unlike Arabidopsis DREB2A , these data support the hypothesis that post-translational regulation might not be important for ZmDREB2 . 7 . Protein sequence analysis indicated that ZmDREB2 . 7 did not contain the amino acid sequence homologous to the negative regulation domain ( NRD ) present in Arabidopsis DREB2A . Taken together , these data clearly demonstrate that ZmDREB2 . 7 can specifically bind DRE sequences and overexpression of this gene can confer drought stress tolerance on transgenic Arabidopsis . In order to compare the genetic effect of different ZmDREB2 . 7 alleles on drought tolerance in maize , four drought-tolerant , inbred lines ( CIMBL70 , 91 , 92 and CML118 were selected and crossed with a drought-sensitive variety ( Shen5003 ) resulting in four segregating F2 populations . All four drought-tolerant lines have the same ZmDREB2 . 7 allelic sequence in the 5′-UTR at five significant loci , while Shen5003 has the opposite allele at all five loci . Thus , the ZmDREB2 . 7 allele in the tolerant inbred lines was considered to be the favorable/tolerant allele and the allele in Shen5003 was inferior/sensitive . The DNA polymorphisms of the five varieties at the significant loci are shown in Figure 7A . Additionally , a 20-bp InDel , located 21-bp upstream of the start codon , was found in the four drought-tolerant inbred lines . Although this polymorphism was not as significantly associated with drought tolerance in the 105 varieties as was the five loci located in the 5′-UTR , a pair of primers , surrounding the 20-bp InDel , was designed to distinguish the presence of the favorable ZmDREB2 . 7 allele by PCR , due to their close physical linkage ( Figure 7A ) . A comparison of the level of drought tolerance in the five parental materials is shown in Figures 7B . When drought stress was applied to the plants , about 33 . 3% Shen5003 plants survived , while survival rate of the CIMBL70 , 91 , 92 and CML118 was 100% , 88 . 1% , 65 . 5% and 100% , respectively ( Figure 7C ) . Expression of ZmDREB2 . 7 was significantly induced in the four tolerant genotypes in response to a moderate drought stress ( RLWC = 70% ) whereas , it was not significantly upregulated at all in the sensitive genotype ( Figure 7D ) . More than 400 individual F2 plants in each of the four F2 segregating populations were genotyped for the presence of the favorable/tolerant allele of ZmDREB2 . 7 by PCRs . As expected , a Mendelian inheritance pattern was observed for the ZmDREB2 . 7 favorable/tolerant allele in each of the four segregating populations . The segregation rate of homozygous tolerant , heterozygous tolerant/sensitive , and homozygous sensitive plants was approximately 1∶2∶1 ( Figure S4; Table S6 ) . The survival rates of plants carrying the three different assortments of ZmDREB2 . 7 alleles were then compared after being subjected to a drought stress . As shown in Figure 7E , plants that were homozygous for the favorable/tolerant allele of ZmDREB2 . 7 were more tolerant to drought stress than plants that were homozygous for the inferior/sensitive allele . Plants that were heterozygous for the favorable and inferior alleles exhibited a level of drought tolerance that was intermediate between the plants that were homozygous favorable or homozygous inferior . Co-segregation of the ZmDREB2 . 7 tolerant allele with improved drought tolerance suggested the linkage of this locus with the trait in segregation populations . In maize , linkage analyses using bi-parental crosses also reported QTLs ( quantitative trait loci ) for drought tolerance within the chromosomal region ( Chr . 1 , bin 1 . 07 ) where the ZmDREB2 . 7 gene located [48]–[50] . Collectively , these data further support the premise that natural variation in ZmDREB2 . 7 contributes to enhanced drought tolerance in different maize varieties . Importantly , the tolerant/favorable allele of ZmDREB2 . 7 represents a promising genetic resource for the development of drought-tolerant maize cultivars using traditional breeding approaches or genetic engineering .
Although a number of reports have indicated the important role played by DREB-type transcription factors in the regulation of plant response and adaptation to multiple abiotic stresses , including drought stress , little is known about the diverse functions of individual DREB genes and whether or not quantitative differences in the DREB response pathway may contribute to the natural variation in plant response to drought stress observed between and within a species . Answering this question can have a great practical benefit for the development of stress-tolerant crops . In the present study , we were able to utilize recent advances in maize genomic research and high-throughput sequencing technology , to systematically identify DREB-type genes in the maize B73 genome and determine if polymorphisms in the sequence of DREB-type genes were associated with drought tolerance . While much of the previous research has studied the function of an individual gene in a single genotype , the present study provides comprehensive information regarding DREB-type TF gene function in maize drought tolerance through the association analysis . Moreover , biochemical and transgenic studies further supported the natural variation in ZmDREB2 . 7 gene contributed to maize drought tolerance at seedling stage . In the present study , ten DREB1-type genes were identified in the maize B73 genome . This gene number is conserved among rice , maize and sorghum although it is different from the number present in Arabidopsis ( Figure 1 ) . Phylogenetic analysis showed that monocot DREB1 proteins cluster independently from those in Arabidopsis suggesting a potential functional diversity between dicot and monocot plants . In Arabidopsis , DREB1 proteins are the major TFs involved in plant cold stress response . Transcriptomic and metabolomic studies in plants overexpressing DREB1A genes indicated that genes for starch degrading enzymes and sugar alcohol synthases , as well as the resultant metabolites , were upregulated just as they are in plants exposed to low temperature . These data suggest that a re-allocation of energy and/or an osmotic adjustment is involved in stress adaptation [51] . Similar molecular mechanisms and physiological responses , induced and regulated by DREB1 genes , appears to occur in monocots [17] , [52] , [53] . The reason why monocot plants possess an increased number of DREB1 genes , compared to Arabidopsis , is unknown . We found that the majority of ZmDREB1 genes were expressed at high levels in roots under normal growing conditions ( Figure 3A ) . Whether they play a role in maize root development will require further investigation . The presence and organization of specific conserved motifs in the ZmDREB1 proteins exhibited a high degree of similarity amongst the various members while transactivation activity differed from low to high levels indicating that other residues outside of the conserved motifs may play an important role in transactivation activity ( Figure 4 ) . In relative comparison with DREB1s , DREB2 proteins are more phylogenetically diversified in the four species examined . Although ten ZmDREB2s genes were predicted based on a BLAST of the B73 maize genome , only eight genes could be cloned . An analysis of gene structure indicated that the two genes were probably pseudogenes , especially since no transcripts were ever identified . The two putative , pseudogenes may have originated and subsequently become dysfunctional during evolution of the maize genome ( Figure 1 ) . Only two clades in the DREB2 subgroup , each containing a single ZmDREB2 member ( either ZmDREB2 . 3/ZmABI4 or ZmDREB2A/2 . 1 ) , were evolutionarily conserved across the four species analyzed ( corn , rice , sorghum , and Arabidopsis ) ( Figure 1 ) . In Arabidopsis , ABI4 encodes a TF involved in ABA signaling , seed maturation and lateral root formation [54]–[56] . Rice homologs of this gene were also classified in the DREB2 subgroup based on protein sequence similarity [19] , thus ZmDREB2 . 3/ZmABI4 was also closely examined in our study . Similar to the expression pattern of this gene in Arabidopsis , ZmDREB2 . 3/ZmABI4 was found to be highly expressed in germinating seeds and embryos ( Figure 3A ) . Notably , the expression of this gene was clearly inducible in both leaves and roots under drought stress , indicating a possible role for this gene in the stress response ( Figure 3B ) . Supporting this premise is the fact that in the association analysis , the genetic variation of ZmDREB2 . 3/ZmABI4 was found to linked to the phenotypic variation in drought tolerance , although its association was less significant than ZmDREB2 . 7 ( Table 1 ) . In all likelihood , genetic polymorphisms in both ZmDREB2 . 7 and ZmDREB2 . 3/ZmABI4 contribute variations in maize drought tolerance . Additional copies of ZmDREB2 . 4 , 2 . 5 and 2 . 6 and ZmDREB2 . 7and 2 . 8 were only found in maize , enlarging the number of DREB2-type genes in this species ( Figure 1 ) . The chromosomal segments containing these genes were also found to be duplicated , supporting the concept that the maize genome may have arisen from an ancestral allotetraploid , half of which shares a common ancestor with sorghum , which in turn probably represents a lineage split in rice [57] , [58] . The biological significance of DREB2 gene duplications in the maize genome remains to be determined . Previous efforts have been made to explore the association of DREB1s or DREB2s with plant stress tolerance in a number of plants , including Arabidopsis , common bean , and foxtail millet [59]–[61] . In these studies , a few homologous DREB genes were investigated in a small number of varieties and predictive conclusions were proposed . Recent advances in maize genomics , and the availability of genetically diverse collections composed of hundreds of varieties enabled us to systematically undertake an association analysis in maize . We evaluated the drought stress tolerance of seedlings to a severe water stress for each genotype of a maize population consisting of 368 varieties from tropical and temperate regions . The size and genetic diversity of this population makes it ideal for use in a complex trait association studies [39] , [42] . RNA-seq data from this population identified 525 , 105 high quality SNPs , present in more than 25 , 000 maize genes [39] . This enabled us to study the association of 14 ZmDREB genes with drought stress tolerance . After controlling for population structure and cryptic relatedness , both of which may cause spurious associations , genetic polymorphism in ZmDREB2 . 7 , among all of the 14 ZmDREB genes analyzed , was identified to be the most significantly associated with phenotypic variation in drought tolerance ( P<0 . 001 , Table 1 ) using the MLM model . When population structure was controlled by the use of a Q matrix ( calculated by STRUCTURE ) , similar results were obtained . Further sequencing and association analyses identified five DNA polymorphisms in the 5′-UTR of ZmDREB2 . 7 that were associated to drought tolerance variation ( Figure 5A ) . In the B73 genotype of maize , ZmDREB2 . 7 expression was detected at a low level in various tissues and was slightly induced in leaves and roots by drought stress . However , the ZmDREB2 . 7 protein possessed a high level of transactivation activity compared with other ZmDREB proteins ( Figure 3 and 4 ) . In support of the association study , it was found that the expression level of ZmDREB2 . 7 , but not the activity of the protein , was correlated with drought tolerance among different maize varieties ( Figure 5B ) . Moreover , ZmDREB2 . 7 protein-DNA binding analysis in vitro and analysis of the effect of ZmDREB2 . 7 overexpression in transgenic Arabidopsis demonstrated that ZmDREB2 . 7 can function as a typical DREB-type TF and improve drought tolerance ( Figure 6 ) . The majority of ZmDREB1s , as well as some ZmDREB2s such as the previously identified ZmDREB1 . 1/1A and ZmDREB2 . 1/2A , are highly induced in leaves and/or roots in response to drought stress in the B73 in bred line . However , genetic polymorphisms in these genes were not as significantly associated with drought stress as those of ZmDREB2 . 7 . We suggest that some genes may be essential to stress response in all the maize varieties and that significant genetic variation in those genes would either result in a lethal phenotypic defects or an undetectable effect , the latter being due to functional compensation by other redundant genes . Therefore , we could not detect a significant association of these genes . In spite of a large degree of variation in the survival rates among the 368 varieties after being subjected to drought stress , basic stress responses ( e . g . stress-related gene induction , stomatal closure ) could still be observed even in the most sensitive genotypes , indicating that the central or basic response was still conserved in this variation panel . Gene transfer technology could be used to modulate the expression of a highly stress-inducible gene and thus improve tolerance to stress . This approach was evidenced by the creation of ZmDREB1 . 1/1A and ZmDREB2 . 1/2A overexpressors , however , their expressions or activity require optimization to avoid negative effects on plant growth and yield [17] , [18] . Additionally , four ZmDREB genes in our current dataset were not polymorphic . Therefore , their association with phenotypic variation in drought stress could not be estimated . Whether or not polymorphisms in these genes are important for drought tolerance remains undetermined . The fact that genetic variation in the five loci upstream the start codon of ZmDREB2 . 7 could only explain 6 . 68% of the variation in drought tolerance among the maize population is consistent with the notion that drought tolerance is a complex trait underlined by a number of contributing genes ( Table S7 ) . In the future , a whole genome scale GWAS for maize drought tolerance at the seedling stage will be further investigated . It is anticipated that this complex analysis will provide an overview of the genetic contribution to this trait . DREB2A protein was reported to prefer ACCGAC to GCCGAC as a target binding site , although both sequences represent a typical DRE cis-element [9] . We found that ZmDREB2 . 7 protein can equally bind both DRE target sequences in vitro , indicating that differences in DNA-binding-preference may exist between DREB2A and ZmDREB2 . 7 proteins . ZmDREB2 . 7 did not interact with the GCCGCC sequence in a specific manner , suggesting that this protein is mainly involved in drought stress rather than ethylene or biotic stress response ( Figure 6A ) . Together with its high level transactivation activity , it is suggested that , in response to drought stress , ZmDREB2 . 7 protein can bind and activate the promoter of downstream stress-responsive genes . Although the DNA binding preference of ZmDREB2 . 1/2A and ZmDREB2 . 7 is generally similar , at a low protein concentration ZmDREB2 . 1/2A showed a higher affinity for the DRE sequences than ZmDREB2 . 7 ( Figure 6A ) . Transgenic plants overexpressing ZmDREB2 . 7 exhibited improved plant drought stress tolerance which strongly supports the contention that regulation of gene expression was an important function for this gene . Previous reports indicated that transgenic plants constitutively overexpressing DREB2A-CA or ZmDREB2 . 1/2A gene exhibited a dwarf phenotype in addition to enhanced drought tolerance [9] , [18] . In the present study , significant growth retardation was not observed in most of the ZmDREB2 . 7 transgenic plants , except a mild phenotype of ZmDREB2 . 7-OE9 plants , which had the highest level of transgene expression ( Figure 6B ) . Probably , different DREB genes may differentially affect plant growth and development in Arabidopsis due to their different binding affinity to target DNA sequences . The function of DREB TFs is to bind DRE sequences present in the promoter region of many stress-inducible genes and transactivate gene expression , the gene products of which may protect plants from stress impairment [1] . Thus , an early and quick response to an environmental stress signal is important for the proper function of a TF gene . This can be accomplished either by a rapid induction of gene expression in response to an environmental stimulus or by quick modulation of transactivation activity of the protein coded by the TF . In our study , genetic polymorphisms in the 5′-UTR of ZmDREB2 . 7 were associated with variation in maize drought tolerance . Furthermore , differences in ZmDREB2 . 7 gene expression in response to a moderate drought stress , but not severe drought or normal growth conditions , were correlated with plant survival among different maize varieties ( Figure 5 ) . It suggested induction of ZmDREB2 . 7 expression in early drought stress was important for plant survival in stress , which coincided with its function as a TF to activate downstream stress-responsive gene expression . The quicker induction of ZmDREB2 . 7 expression in the tolerant genotype of CIMBL70 , 91 , 92 and CML118 than in the sensitive genotype of Shen5003 was consistently observed ( Figure 7D ) . We further analyzed the ZmDREB2 . 7 gene expression data in approximately seventy maize inbred lines based on tolerant or sensitive genotypes of ZmDREB2 . 7 , under well-watered , early and late drought stress conditions . The results demonstrated that , on average , the materials carrying the tolerant allele of ZmDREB2 . 7 had a significantly higher expression level than those carrying the sensitive allele in response to early drought stress ( Figure S5 ) . Moreover , we found that among the 105 randomly selected varieties , the subpopulation consisting of tropical inbred lines had the highest frequency of the favorable allele of ZmDREB2 . 7 , which is consistent with the observed higher level of drought tolerance of this subpopulation than the others ( Figure S6 ) . We searched the database of Plant Cis-acting Regulatory DNA Elements ( http://www . dna . affrc . go . jp/PLACE/signalscan . html ) to identify putative cis-elements in the obtained 570-bp sequences upstream from the start codon amongst the 105 genotypes . Among the most significant 5 loci and the 20-bp InDel polymorphism , only InDel-154 brings about an additional W-box in the promoter of Shen5003 , which is possibly a WRKY TF recognition site . At the present time it is not known whether this difference results in alteration of gene expression in response to drought stress . Four nonsynonymous polymorphisms in the ZmDREB2 . 7 coding region ( outside of the DNA-binding domain ) were detected to be significantly associated with drought tolerance ( Figure 5A ) but the proteins encoded by the different haplotypes displayed similar levels of transactivation activity ( Figure S3 ) , indicating that they were probably not causal variations that affected the function of the coded protein . In the present research we found that: ( 1 ) three SNPs and two InDels , upstream of the start cordon of ZmDREB2 . 7 were significantly associated with phenotypic variation in drought tolerance ( Figure 5A ) ; ( 2 ) nonsynonymous mutations in the protein coding region did not greatly affect transactivation activity of the coded protein ( Figure S3 ) ; ( 3 ) consistent with the TF function of ZmDREB2 . 7 , a rapid induction of ZmDREB2 . 7 gene expression in response to a moderate drought stress was important in conferring plant drought-stress tolerance ( Figure 5B ) ; ( 4 ) overexpressing ZmDREB2 . 7 can improve drought stress tolerance in transgenic plants ( Figure 6B ) ; ( 5 ) the favorable allele of ZmDREB2 . 7 could effectively enhance plant drought tolerance in four distinct genetic backgrounds compared to the inferior allele ( Figure 7E ) . We conclude that naturally occurring polymorphisms in ZmDREB2 . 7 contribute to drought stress tolerance of maize seedlings and that the polymorphisms in the gene promoter region were the functional variations responsible for the observed variations in gene expression and plant drought tolerance . The identified beneficial allele may be of more practical use rather than as a transgene since gene expression may have been optimized during evolution and/or natural selection in planta . Increasing gene function through ectopic gene expression usually results in pleiotropic effects , such as growth and/or developmental defects , which is especially true for overexpession of the regulatory gene . ZmDREB2 . 7 and its favorable allele may be a valuable genetic resource for improving maize drought tolerance either as a genetic marker in marker assisted breeding or in transgenic approaches .
Full-length amino acid sequences of 66 DREB1s and DREB2s identified in maize , rice , Arabidopsis and sorghum were aligned using the Clustal X 1 . 83 program with default pairwise and multiple alignment parameters . The phylogenetic tree was constructed based on this alignment result using the neighbor joining ( NJ ) method in MEGA version 5 ( http://www . megasoftware . net/ ) with the following parameters: Poisson correction , pairwise deletion , uniform rates and bootstrap ( 1000 replicates ) . The ZmDREB proteins were named sequentially according to their placement in the phylogenetic tree . Maize seeds were surface-sterilized in 1‰ ( v/v ) Topsin-M ( Rotam Crop Sciences Ltd . ) for 10 min , then washed in deionized water and germinated on wet filter paper at 28°C for 3 days . The germinated seeds were either transplanted to enriched soil ( turf to vermiculite in a ratio of 1∶1 ) or placed in a nutrient solution ( 0 . 75 mM K2SO4 , 0 . 1 mM KCl , 0 . 25 mM KH2PO4 , 0 . 65 mM MgSO4 , 0 . 1 mM EDTA-Fe , 2 mM Ca ( NO3 ) 2 , 1 . 0 µM MnSO4 , 1 . 0 µM ZnSO4 , 0 . 1 µM CuSO4 , 0 . 005 µM ( NH4 ) 6Mo7O24 for hydroponic cultivation [62] . Drought treatment was applied to the soil-grown plants at the 3-leaf seedling stage by withholding water . Leaf samples for gene expression analyses were collected when relative leaf water content ( RLWC ) decreased to 98% , 70% , 60% and 58% , which reflected different levels of drought stress . For root samples , the hydroponic cultured seedlings at a corresponding developmental stage were placed on a clean bench and subjected to dehydration ( 28°C , relative humidity of 40∼60% ) . Samples were exposed for 0 , 5 , 10 and 24 hours , the time point of which was determined by measuring the RLWC , corresponding to the drought-treated leaf samples , which were approximately 98% , 70% , 60% and 58% , respectively . Expression patterns of 18 ZmDREBs in different maize tissues were analyzed using the genome-wide gene expression atlas of the inbred B73 line of maize that was reported previously [41] . Expression data for the 15 tissues were combined from 60 growth stages . Normalized expression values of each gene in different tissues were averaged . The gene expression level was presented as a log value . The responsiveness of each ZmDREB gene to drought stress was analyzed by qRT-PCR and the expression of ZmUbi-2 ( UniProtKB/TrEMBL; ACC:Q42415 ) was used as an internal control . Total RNA was isolated using TRIZOL reagent ( Biotopped ) from no less than 3 seedlings . In order to eliminate genomic contamination , total RNA was treated with RNase-free DNAse ( Takara ) . The concentration of total RNA was determined using a Nanodrop1000 ( Thermo Scientific product , USA ) . In order to confirm RNA integrity and quantity , 5 µg of total RNA from each sample was run on a 0 . 8% agarose gel . Recombinant M-MLV reverse transcriptase and 1 µg of total RNA mixed with 1 µg Oligo ( dT ) 23 ( Promega ) were used to synthesize the cDNAs . Eighteen ZmDREB genes were individually cloned into the pBluescript II KS+ vector from the maize B73 inbred line . After sequence analysis , the ZmDREB genes were transferred to pGBKT7 for evaluation of transactivation activity in the AH109 yeast strain . The cell concentration of yeast transformants was adjusted to an OD600 of 0 . 1 , the yeast cells were then dropped on SD/-T , SD/-T-H , SD/-T-H-A and SD/-T-H-A plates containing various concentrations of 3-AT to compare their ability to grow . The plates were incubated at 30°C for 2–5 days before photographing . DNA fragments of ZmDREB2 . 7 and ZmDREB2 . 1/2A encoding the AP2/ERF DNA-binding domain were cloned into the EcoR I-Sma I sites of pGEX4T-1 vector and transformed into the E . coli strain of Rosseta pLys . The primers used for amplification of the fragments of ZmDREB2 . 7 and ZmDREB2 . 1/2A were 5′-TTGAATTCATGGATCGGGTGCCG-3′ and 5′-TCACTGCAGGTTTAGGCGAGC-3′ , 5′-GGGAATTCATGACGCTGGATCAG-3′ and 5′-TCAGGGGAAGTTAGTCCGTGC-3′ , respectively . The GST fusion proteins were extracted and purified using the GST-Sefinose resin as described in [6] . Gel mobility shift assays were performed according to the instructions provided with the LightShift Chemiluminescent EMSA Kit ( Thermo Scientific ) . The DRE and GCC-box sequences which were end-labeled with biotin were 5′biotin-TTGATACTA/GCCGACATGAGTTGATACTA/GCCGACATGAGT-3′ and 5′biotin-ACTCATGTCGGTAGTATCAACTCATGTCGGTAGTATCAA-3′ , respectively . A natural variation panel of maize consisting of 368 maize inbred lines [39] was planted in a cultivation pool ( 6×1 . 4×0 . 22 m , length×width×depth ) in which 5-ton of loam were uniformly mixed with 0 . 25-ton of chicken manure . Each pool was divided into 250 plots . Twelve plants were grown of each genotype in each plot . Watering was withheld when the seedlings had three true leaves . The time point for rehydration was determined by the characterization of drought resistance among all the genotypes , e . g . the wilting rate . Typically , this occurred seven days after the soil relative water content had decreased to nearly 0% . Watering was then resumed in order to recover the surviving plants . After rehydration for 6 days , the survival rate of each genotype was assessed . The drought phenotypic data were obtained from independent replicated experiments . Principle components of the association panel were calculated by EIGENSTRAT [63] using the high-quality 525 , 105 SNP data [39] with MAF≥0 . 05 . The first two dimensions were used in the principle components ( PCA ) to estimate the population structure , which could explain 11 . 01% of the phenotypic variation and was comparable to that calculated by STRUCTURE . The analysis was completed by the lm function in R program ( http://www . R-project . org ) . Single-maker association analysis was done first to filter markers that had no relationship with the trait ( p≥0 . 995 ) . After that , 1 , 822 SNP markers distributed on each chromosome were chosen to estimate the kinship coefficient ( K ) by SPAGeDi [64] . GLM method was applied to perform single-maker analysis . A mixed linear method [43] , [44] , taking account of both the kinship coefficients and the population structure ( PCA+K ) , was applied to identify the positive association of DNA polymorphisms with drought tolerance . The coding region of the ZmDREB2 . 7 cDNA of the maize B73 inbred line ( 1080 bp ) , digested with Sma I and Sal I ( Takara ) , was inserted into the pGreen0029-35S-Ω vector [11] . The constructed plasmid carrying the desired gene was transformed into Agrobacterium tumefaciens GV3101+pSoup . Arabidopsis thaliana ecotype Col-0 was transformed as described previously [6] . Using kanamycin-based selection , several independent T2 transgenic lines were obtained , and expression of ZmDREB2 . 7 transgene was confirmed in these lines by RT-PCR . Three independent overexpression lines ZmDREB2 . 7-OE9 , ZmDREB2 . 7-OE17 and ZmDREB2 . 7-OE19 were selected based on the level of transgene expression and subjected to further analyses . Seven-day-old plants were transferred into pots containing 100 g soil/pot . Thirty two-day-old plants growing under favorable water conditions were exposed to drought stress . Water was withheld from the plants for 14 days . Watering was then resumed to allow plants to recover . Six days later , the number of surviving plants was recorded . At least 30 plants of each line were compared with WT in each test and statistical data were obtained from three independent experiments . In order to amplify the full length ZmDREB2 . 7 gene , including 5′ and 3′-UTR sequence , in different maize inbred lines , three pairs of primers were synthesized using the B73 genome sequence as a reference ( MaizeGDB release 5b . 60 , http://www . maizegdb . org/ ) . All primers were designed using Primer Express 3 . 0 ( Table S7 ) . All of the obtained sequences were aligned using MEGA version 5 ( http://www . megasoftware . net/ ) . Nucleotide polymorphisms , including SNPs and InDels , were identified ( MAF≥0 . 05 ) . The significance of each DNA polymorphism associated with maize drought tolerance was calculated using the above-mentioned PCA+K model . Four segregating populations ( CIMBL70×Shen5003 , CIMBL91×Shen5003 , CIMBL92×Shen5003 , and CML118×Shen5003 ) were generated . Maize seedlings were grown in enriched soil ( turf to vermiculite in a ratio of 1∶1 ) in plastic boxes ( 0 . 70×0 . 50×0 . 18 m , length×width×depth ) . Each box contained 144 seedlings . Three independent replications were performed in a greenhouse using 16-h-light/8-h-dark , 28/22°C and a RH of 60% , to obtain the statistical data . A section of the cotyledons of 10-day-old plants were collected for ZmDREB2 . 7 genotyping . Subsequently , drought stress was applied to the plants by withholding water . When soil relative water content decreased from 40% to 0% and wilting and death of the seedlings were visible , plants were rewatered in order to identify the surviving plants . The survival rate of each genotype was recorded . Three replications were carried out for statistical analysis . All the PCR primers used in this research were listed in Table S8 .
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Water scarcity is one of the most severe threats to maize production worldwide . Although research has demonstrated that DREB-type transcription factors play important roles in plant water stress response , whether the specific genetic variants in DREB genes contribute to plant drought tolerance is largely unknown . Taking advantages of recent technical and methodological advance , we systematically analyzed all the functional DREB genes in maize and examined their associations with the natural variation in drought tolerance of 368 maize varieties collected from tropical and temperate regions . A significant association in the ZmDREB2 . 7 gene with drought tolerance was detected in that the DNA polymorphisms in the gene promoter region , but not those in the protein coding region , contributed to observed variations in maize drought tolerance , probably due to the distinct gene expression patterns in response to the stress . Overexpressing ZmDREB2 . 7 in Arabidopsis resulted in enhanced tolerance to drought stress . Moreover , a favorable ZmDREB2 . 7 allele , identified from drought-tolerant varieties , was effective in improving plant tolerance to drought stress when it was introduced into a drought-sensitive background . ZmDREB2 . 7 and its favorable allele represent a valuable genetic resource for enhancing maize drought tolerance by marker assisted breeding and transformation technology .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2013
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Genome-Wide Analysis of ZmDREB Genes and Their Association with Natural Variation in Drought Tolerance at Seedling Stage of Zea mays L
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Robust biological systems are expected to accumulate cryptic genetic variation that does not affect the system output in standard conditions yet may play an evolutionary role once phenotypically expressed under a strong perturbation . Genetic variation that is cryptic relative to a robust trait may accumulate neutrally as it does not change the phenotype , yet it could also evolve under selection if it affects traits related to fitness in addition to its cryptic effect . Cryptic variation affecting the vulval intercellular signaling network was previously uncovered among wild isolates of Caenorhabditis elegans . Using a quantitative genetic approach , we identify a non-synonymous polymorphism of the previously uncharacterized nath-10 gene that affects the vulval phenotype when the system is sensitized with different mutations , but not in wild-type strains . nath-10 is an essential protein acetyltransferase gene and the homolog of human NAT10 . The nath-10 polymorphism also presents non-cryptic effects on life history traits . The nath-10 allele carried by the N2 reference strain leads to a subtle increase in the egg laying rate and in the total number of sperm , a trait affecting the trade-off between fertility and minimal generation time in hermaphrodite individuals . We show that this allele appeared during early laboratory culture of N2 , which allowed us to test whether it may have evolved under selection in this novel environment . The derived allele indeed strongly outcompetes the ancestral allele in laboratory conditions . In conclusion , we identified the molecular nature of a cryptic genetic variation and characterized its evolutionary history . These results show that cryptic genetic variation does not necessarily accumulate neutrally at the whole-organism level , but may evolve through selection for pleiotropic effects that alter fitness . In addition , cultivation in the laboratory has led to adaptive evolution of the reference strain N2 to the laboratory environment , which may modify other phenotypes of interest .
Many developmental systems produce outputs that are insensitive to a wide range of environmental or genetic perturbations . In these robust systems , buffering may allow for the accumulation of “cryptic” genetic variation affecting the system without changing its end product [1]–[3] . Upon major environmental or genetic change , genetic variation that was previously cryptic may then become phenotypically expressed and play a role in the evolution of the system [2] , [3] . Cryptic variation thus refers to standing genetic variation that is epistatically masked and conditionally neutral: it is not expressed in most conditions , but it can be revealed based on genotype-by-genotype ( GxG ) interactions with loci involved in the development of the trait or through genotype-by-environment ( GxE ) interactions , as in the classical experiments by Waddington [4] , [5] . Beyond the interest for evolutionary biology , studying this kind of genetic variation is also important to understand the elevated incidence of complex human diseases in modern societies , a phenomenon that could result from the phenotypic expression of cryptic variation in response to the marked change of lifestyle that occurred in the last generations [6] . Two different hypotheses could explain the evolutionary origin of cryptic genetic variation . It may accumulate neutrally because it has little or no effect on traits evolving under selection . Alternatively , a mutation that presents a cryptic effect in a robust system could be under directional selection for its non-cryptic pleiotropic effect on another more sensitive trait . Molecular identification of factors involved in cryptic variation is required to understand the causes and consequences of such variation . Although the empirical study of cryptic genetic variation is limited by the difficulty in detecting it , it has been uncovered in several species after application of a perturbation , either genetic or environmental , to different wild genotypes [7]–[17] . However , in only few cases were the underlying polymorphisms precisely mapped [18] and candidate polymorphisms confirmed [19] . The objective of the present study was to characterize the molecular basis and the evolutionary origin of the cryptic variation previously uncovered in the vulval signaling network of the nematode Caenorhabditis elegans [10] . The vulva is the egg laying and copulatory organ of C . elegans hermaphrodites . It is formed during larval stages from a row of six competent cells in the ventral epidermis ( P3 . p to P8 . p ) . Only three of these cells ( P5 . p to P7 . p ) adopt vulval fates in wild-type animals . P6 . p adopts an inner 1° vulval fate , while P5 . p and P7 . p adopt a lateral 2° vulval fate . After fate specification , each precursor cell follows a specific division pattern during the L3 and L4 stages ( Figure 1A ) . Wild-type vulval cell fate patterning ( 3°3°2°1°2°3° ) relies on the spatio-temporal regulation of a signaling network including the EGF/Ras , Delta/Notch , and Wnt/βcat pathways ( Figure 1A ) [20] . During the L2 stage , the uterine anchor cell , which is located close to P6 . p , starts to emit an inductive LIN-3/EGF signal that can act as a morphogen: the high dose received by P6 . p leads to the 1° fate , whereas lower doses received by P5 . p and P7 . p contribute to their adoption of the 2° fate [21] . Ras/MAP kinase pathway activation in P6 . p also promotes the 2° fate in P5 . p and P7 . p through a lateral Delta/Notch pathway [20] . P3 . p , P4 . p , and P8 . p normally adopt a non-vulval fate , but are able to adopt a vulval fate if P5 . p , P6 . p , or P7 . p are missing . The Wnt/βcat pathway acts at several steps in the process , participating in cell competence , induction , and lineage polarity [22] . The vulval cell fate patterning system displays robustness to both environmental and genetic perturbations , which likely arises from properties of the signaling network creating a non-linear relationship between the activity of individual pathways and the resulting number of induced vulval cells [23] . The cell fate pattern of P4 . p to P8 . p is quasi-invariant in the Caenorhabditis genus and few variants were detected in C . elegans individuals raised in various environments , despite change in signaling pathway activity [24] . In addition , a recent computational model was able to reproduce the wild-type vulval cell fate pattern over a broad range of parameter values [25] . As expected in a system with a robust output , the underlying developmental mechanisms have evolved at the interspecific and intraspecific levels ( Figure 1C ) . Indeed , quantitative variation in a downstream fluorescent reporter of the EGF/Ras pathway was detected among C . elegans wild isolates despite no change in the resulting cell fates ( Figure 1D ) [10] . Furthermore , the type and frequency of vulval fate errors following a variety of environmental , genetic , or experimental perturbations differ among Caenorhabditis species and C . elegans wild isolates ( Figure 1E–F ) [10] , [24] , [26]–[28] . Due to the broad knowledge of the developmental network , the small number of cells involved and the ease of genetic studies in C . elegans , vulval cell fate patterning is an ideal model to investigate the evolutionary origin and consequences of cryptic variation . One of the genetic perturbations used to reveal cryptic variation among C . elegans wild isolates was the let-23 ( sy1 ) /egfr allele ( Figure 1B ) [10] . This EMS-induced mutation alters EGF receptor localization in vulval precursor cells and leads to a decrease in the mean number of cells adopting a vulval fate [29] , [30] , as well as an increase in the among-individual variation due to a shift of the system outside its buffered range . The expressivity of let-23 ( sy1 ) varies among wild genetic backgrounds of C . elegans , revealing cryptic variation among them [10] . Especially , let-23 ( sy1 ) expressivity , as quantified by the mean number of cells adopting a vulval fate ( vulval index ) , is much less pronounced in the AB1 wild background than in the N2 reference background in which this mutation was isolated ( Figure 1F ) [10] . In this case , the effect of the cryptic variation is thus revealed through an epistatic interaction between the laboratory allele at the let-23 locus and the wild genetic background . Here , we use a quantitative genetic approach to characterize the genetic architecture of variation in let-23 ( sy1 ) expressivity between these wild genetic backgrounds and identify underlying molecular polymorphisms . We find that a non-synonymous polymorphism in the nath-10 gene explains a major effect quantitative trait locus ( QTL ) . nath-10 is the human N-acetyltransferase 10 homolog and its function is largely unknown in C . elegans . We show that the nath-10 ( N2 ) allele likely appeared during early laboratory culture of the N2 strain and that in addition to its cryptic effect in the vulval system , this allele presents non-cryptic effects on life history traits such as progeny number , minimal generation time , or egg-production rate . Some of the effects of the nath-10 polymorphism are likely mediated through alterations in the timing of the sperm/oocyte switch in hermaphrodites . Finally , competition assays show a clear selective advantage of the N2 allele in laboratory conditions . We thus identify a pleiotropic polymorphism that shows a cryptic effect in the vulval system and a strong selective advantage in the laboratory environment due to its effect on life history traits . Therefore , because of pleiotropic effects , some cryptic genetic variation need not accumulate neutrally during the evolution of robust systems .
As previously observed [10] , the expressivity of vulval induction defects of a let-23 ( sy1 ) /egfr mutation was much higher in the JU605 strain ( N2 background ) than in the JU606 strain ( AB1 background ) ( Figure 1E , Table S3 ) . We express this phenotype as a vulval index , corresponding to the mean number of Pn . p cells induced to adopt a vulval fate in different individuals of a given strain . We repeatedly observed that the vulval index of the JU606 isogenic strain could significantly vary among cultures grown at 20°C and scored in parallel ( Figure S1 ) . Therefore , we searched for culture conditions in which the vulval phenotype of JU606 would be less variable . We found that the vulval index of JU606 was consistently increased at 25 . 5°C ( but not at 24°C ) compared to 20°C , whereas the vulval index of JU605 was not affected ( Figure 1F , Figure S1 ) . We therefore used this culture temperature to map the genetic variation involved in the phenotypic difference . In order to characterize the genetic architecture underlying the variation in vulval index between JU605 and JU606 , we constructed a set of 60 Recombinant Inbred Lines ( RILs ) from a cross between the two strains . The RILs were genotyped for 50 N2/AB1 SNP markers distributed along the genome ( Table S1 ) . The vulval index of all lines was scored twice at both 20°C and 25 . 5°C ( Figure 2A; Table S1 ) . Statistical analyses were performed to detect quantitative trait loci ( QTL ) , which are genomic regions significantly associated with phenotypic variation . Two QTLs were detected at 20°C ( Figure 2B ) , but their effect was not reproducible between the two replicates , probably due to the high vulval index variability at this temperature ( Figure S1 ) . By contrast , two QTLs were reproducibly found on chromosomes I and II at 25 . 5°C ( Figure 2C ) . The QTL on chromosome I was estimated to explain about 27% to 34% of the phenotypic variance , while the effect of the chromosome II QTL was only about 3 . 6% to 4 . 6% ( Multiple Interval Mapping , unpublished data ) . Another QTL was observed in one replicate on chromosome V at this temperature , but was not reproducible ( Figure 2C ) . AB1 alleles at these QTLs all led to higher vulval index than N2 alleles ( positive effect QTL ) . Finally , a QTL with strong negative effect was detected in one replicate at 20°C . This negative effect QTL could contribute to the transgressive phenotype of some RILs that presented a more extreme vulval induction index than either parental strain ( Table S1 ) . The npr-1 polymorphism [31] was a candidate to explain this putative QTL because it was previously identified in QTL analyses of various traits [32]–[36] . In support of this hypothesis , strains carrying the N2 allele of npr-1 in the N2 background presented a higher vulval index at 25 . 5°C than strains with the AB1 allele npr-1 ( g320 ) introgressed in the N2 background ( Figure S2 ) . This effect seemed sensitive to environmental conditions because it was not always observed in replicate experiments at 20°C or at 25 . 5°C ( unpublished data and Figures 2B–C , S2 ) . In order to characterize the genetic basis of the phenotypic plasticity to temperature , an additional QTL analysis was performed using as trait value for each RIL the difference in vulval induction index between 25 . 5°C and 20°C ( Figure 2D ) . The only QTL that was detected in this analysis corresponded to the major effect QTL detected on chromosome I at 25 . 5°C , which was absent in the 20°C analyses . This plastic effect corresponds to a genotype-by-environment interaction ( GxE ) since the effect of the QTL allele on vulval induction depends on temperature . Together , these results showed that the genetic architecture of the phenotypic variation observed between JU605 and JU606 was temperature-sensitive and involved more than one locus . No significant epistatic interactions were detected between single-effect QTLs ( multiple interval mapping , unpublished data ) . Since the QTL detected at 25 . 5°C on chromosome I was involved in a major fraction of the phenotypic variation , we next sought to identify the underlying causative molecular polymorphism ( s ) . Several lines were selected for a recombination event in the chromosome I QTL region after crosses of the RILs with highest vulval index to JU605 ( let-23 ( sy1 ) in N2 ) . After SNP genotyping and scoring of vulval index in these lines ( Table S2 ) , the QTL was restricted to a 183 kb region ( Figure 3A; Table S3 ) . The alignment of the N2 reference genome ( www . wormbase . org ) to the genome of the AB1 strain ( Illumina sequencing [L . Stein et al . , personal communication] followed by Sanger sequencing of non-covered regions ) revealed the presence of only three polymorphisms in the QTL region . Two of them lie in intergenic regions ( mfP14 and haw6786 ) and the third one ( haw6805 ) affects the coding sequence of a gene with unknown function , F55A12 . 8 , which was renamed nath-10 for its homology with the human NAT10 gene ( N-acetyltransferase 10 ) . We performed several experiments that test whether the nath-10 polymorphism explains the chromosome I QTL effect . First , RNAi inactivation of nath-10 in lines carrying either the nath-10 ( N2 ) or the nath-10 ( haw6805 ) allele decreased the vulval index ( Figure 3B ) . This suggested that nath-10 acts as a positive regulator of vulval induction and that nath-10 ( N2 ) is a hypomorphic allele compared to nath-10 ( haw6805 ) . In addition , the effect of nath-10 ( N2 ) on vulval induction was found to be recessive to that of nath-10 ( haw6805 ) ( Figure S3A ) . The vulval index still differed after nath-10 ( RNAi ) between the JU605 ( nath-10 ( N2 ) ) and the JU1624 ( nath-10 ( haw6805 ) ) strains ( Figure 3B ) , which may be explained by a partial inactivation of nath-10 by the RNAi treatment or by parental effects; alternatively , another polymorphism in the introgressed AB1 region of JU1624 could affect vulval induction . Heterozygous animals carrying the nath-10 ( N2 ) allele over the null mutation nath-10 ( tm2624 ) presented a decreased vulval index compared to JU605 ( Figure S3B ) . However , it is not clear whether this was due to the tm2624 deletion or to the translocation used to balance this embryonic lethal mutation ( Figure S3B ) . In order to confirm the role of nath-10 in vulval induction , we also overexpressed the gene using transgenesis . Overexpression of either nath-10 ( haw6805 ) or nath-10 ( N2 ) alleles increased the vulval index in the JU605 strain but not in the JU1620 ( nath-10 ( haw6805 ) ) strain ( Figure 3C ) . These results indicate that both alleles are functional , consistent with nath-10 ( N2 ) being a hypomorph and not a null allele . A possible explanation for the absence of effect of nath-10 overexpression in the JU1620 strain background may be that the endogenous nath-10 ( haw6805 ) activity is already saturating . Alternatively , nath-10 overexpression may have weak effects due to the low concentration of nath-10 genomic DNA used to avoid the lethality observed at higher concentrations . This may also explain why nath-10 ( haw6805 ) overexpression does not rescue vulval induction in JU605 to the level observed in JU1620 ( Figure 3C ) . A third experiment was performed to test whether the two other polymorphisms in the QTL region ( Table S2 ) could be ruled out . The nath-10 polymorphism was the only variation with N2 found to be shared by the LSJ1 and AB1 strains in the QTL region ( LSJ1 is a strain closely related to N2 , as described below ) [37] , [38] . The nath-10 ( haw6805 ) allele was thus introgressed into JU605 ( let-23 ( sy1 ) in N2 ) from the LSJ1 genetic background . Irrespective of their genetic background origin , strains homozygous for nath-10 ( haw6805 ) always presented a higher induction index than strains homozygous for nath-10 ( N2 ) at 25 . 5°C ( Figures 3D , S5B ) . Therefore , the QTL effect is very probably due to the nath-10 polymorphism and not to other polymorphisms in the QTL region . From the three experiments above , we conclude that nath-10 ( haw6805 ) is the causative chromosome I polymorphism that explains a large part of the difference in expressivity of the let-23 ( sy1 ) allele between the N2 and AB1 genetic backgrounds . The increase in vulval index conferred by the nath-10 ( haw6805 ) allele represented 53%±4% of the total difference observed between the JU605 and JU606 parental strains . The nath-10 polymorphism does not affect vulval cell fates in a wild-type context ( no defect observed in N2 and AB1 individuals grown at 25 . 5°C , n = 100 ) . We wondered whether its effect on let-23 ( sy1 ) expressivity was specific to the sensitizing mutation . To address this point , a gain-of-function mutation in Ras , let-60 ( n1046 ) /ras , was crossed in the N2 background with the introgressed segment mfIR16 bearing the nath-10 ( haw6805 ) allele from AB1 . let-60 ( n1046gf ) led to vulval fate hyperinduction ( more than 3 induced Pn . p cells ) , and the vulval index was higher in lines carrying the nath-10 ( haw6805 ) allele ( Figure 4 ) , as was the case for let-23 ( sy1 ) . Therefore , the effect of the nath-10 polymorphism can be uncovered with different sensitizing factors and is not specific to the mutation initially used to identify it . nath-10 encodes a polypeptide of 1 , 043 amino acids . Pairwise alignment of the NATH-10 protein sequence with its human homolog NAT10 indicates a 57 . 3% conservation at the amino-acid level ( Figure 5A ) . In human , the NAT10 protein regulates different cellular processes such as cytokinesis , mitotic chromosome decondensation , or telomerase expression and it can acetylate different substrates such as histones and α-tubulin [39]–[42] . In C . elegans , nath-10 was recently identified in a RNAi screen for abnormal expression of sex-specific gonadal markers [43] , but its function has not been further investigated . The recessive nath-10 ( tm2624 ) deletion , which results in a truncated protein of 394 amino-acids , leads to fully penetrant embryonic lethality . The N2 protein presents an isoleucine residue at position 746 instead of the methionine found in the AB1 protein or in the human alignment at the corresponding position ( Figure 5B ) . This non-synonymous polymorphism affects a conserved region , which corresponds to the acetyltransferase domain in the human counterpart ( Figure 5A ) . A protein with acetyltransferase activity could act at different levels of the vulval signaling network to regulate cell fate induction . For instance , mys-1 and hda-1 , which encode a MYST family histone acetyltransferase and a class I histone deacetylase , respectively , can both act as class B SynMuv genes to repress vulval induction [44]–[46] . Single mutations of SynMuv genes do not affect vulval fate patterning , whereas the combination of two mutations belonging to different SynMuv classes result in a Synthetic Multivulva phenotype . Remarkably , several SynMuv B null mutants respond to temperature in a similar way as nath-10 ( haw6805 ) animals: they present a different phenotype at 24°C compared to 25–26°C [47] , [48] . For these reasons , we tested whether the combination of the nath-10 ( haw6805 ) allele with a SynMuv mutation of either class led to excess vulval induction . The nath-10 ( haw6805 ) ; lin-15A ( n767 ) and nath-10 ( haw6805 ) ; lin-15B ( n744 ) lines did not present a Multivulva phenotype ( Table S4 ) , suggesting that nath-10 does not act as a SynMuv gene . To study the evolutionary history of the nath-10 polymorphism , we determined the allelic distribution in a set of C . elegans natural isolates and related species ( Figure 5C , Table S5 ) . The N2 allele was only found in two other strains , CB4555 and TR389 , which were likely derived by contamination from the N2 lab reference strain [49] . The AB1 allele was found in all other C . elegans isolates and conserved in other nematode species , fly , human , or yeast . Thus , nath-10 ( N2 ) is a derived allele relative to the ancestral nath-10 ( haw6805 ) allele . The observed polymorphism distribution raised the possibility that the nath-10 ( N2 ) allele did not appear in the wild . This hypothesis was confirmed by the presence of nath-10 ( haw6805 ) in the LSJ1 laboratory strain , which is likely derived from the same Bristol wild isolate as N2 [34] , [37] , [38] . The so-called “N2 ( ancestral ) ” strain ( CGC ) , which is only about six generations away from the earliest frozen stock of N2 , presents the nath-10 ( N2 ) allele ( Table S5 ) . The nath-10 ( N2 ) allele thus most probably arose in a period spanning the initial separation of the N2 and LSJ1 strains in the Dougherty lab at UC Berkeley ( between 1957 and 1960 ) to the first freezing of N2 in Sydney Brenner's laboratory around 1968 . With the aim of understanding the evolutionary factors underlying the fixation of the nath-10 ( N2 ) allele in the N2 strain , we enquired whether other traits were affected by the nath-10 polymorphism in the absence of the let-23 ( sy1 ) sensitizing mutation . We focused on life history traits that were known to vary among wild isolates and were likely to affect individual fitness , such as the environmental regulation of dauer diapause entry , lifetime fecundity , minimal generation time , or egg laying rate . We observed that the frequency of dauer formation at 27°C [50] was much higher in AB1 than in N2 . However , two lines carrying the nath-10 ( haw6805 ) allele introgressed into the N2 background did not display any phenotypic difference for this trait compared to N2 ( Table S6 ) . Therefore , the dauer entry variation between N2 and AB1 is not caused by the nath-10 polymorphism . In contrast to dauer formation , the nath-10 polymorphism resulted in variation in three key traits related to population growth: age at maturity , brood size , and egg laying speed ( Figure 6A–C ) . These traits were measured in parallel in N2 , AB1 , and near isogenic lines with the nath-10 ( haw6805 ) allele introgressed from the AB1 background into the N2 background ( JU2003 , JU1648 , and JU1961 ) or from the LSJ1 background into the N2 background ( JU2002 ) . The introgressions were performed from these two genetic backgrounds to ensure that any phenotypic difference with N2 could be attributed to nath-10 polymorphism and not to other polymorphisms in the introgressed regions ( Table S2 ) . N2 presented a significantly higher age at maturity ( Figure 6A ) , brood size ( Figure 6B ) , and maximal egg laying rate ( Figure 6C ) compared to AB1 . For all three traits , a significant , albeit sometimes lower difference with N2 was also observed in the introgressed nath-10 ( haw6805 ) lines . These results strongly suggest that in addition to its cryptic role on vulval induction , the nath-10 polymorphism also affects some life history traits non-cryptically . A simple hypothesis to explain nath-10 effects on lifetime fecundity and age at maturity was that both resulted from the regulation of spermatogenesis duration in young hermaphrodite adults ( Figure 7A ) . In C . elegans hermaphrodites , spermatogenesis occurs between the late L4 and early adult stage and is followed by an irreversible switch to oogenesis . The number of sperm approximates the total number of progeny in the absence of mating with males , and is a limiting factor for lifetime fecundity . Therefore , a longer spermatogenesis leads both to an increased number of self-progeny and to a delayed oogenesis onset , creating a trade-off between brood size and age at maturity [51] , [52] . In order to test whether the nath-10 polymorphism affected the timing of the sperm-oocyte switch , we compared the number of sperm produced in N2 to that of an introgressed nath-10 ( haw6805 ) line . N2 did generate about 10% more sperm than the JU2002 introgressed line ( Figure 7B ) , consistent with the observed difference in brood size and an effect on sperm-oocyte switch ( Figure 6B ) . In addition , nath-10 ( RNAi ) applied to adult hermaphrodites led to complete sterility of all progeny and to an absence of oocytes at high penetrance ( Figure S4A–D ) , confirming a role of nath-10 in germ line development . In these animals , sperm cells were often spread throughout the proximal gonad as visualized by DAPI staining , probably because of the absence of oocytes normally pushing them into the spermatheca ( Figure 7C–D , Figure S4C–D ) . We thus conclude that the mutation to the nath-10 ( N2 ) allele resulted in an increase in sperm number in the laboratory N2 strain , which displays a larger brood size than most wild isolates [53] . The above results strongly suggested that the nath-10 polymorphism could affect fitness . The fact that the N2 allele appeared in the laboratory gave us the unique opportunity to test whether it could contribute to the adaptation of the N2 strain to its environment . Indeed , the specific environment where this genetic variation arose is better known , controlled , and reproducible than natural habitats . Therefore , we were able to perform competition experiments between strains carrying different alleles of nath-10 in culture conditions resembling those when the derived nath-10 ( N2 ) allele first appeared . N2 was competed for several generations against JU1648 ( mfIR16[nath-10 ( haw6805 ) ] ) on 6 cm diameter culture plates in two different growth conditions , namely continuous growth or alternation of growth and starvation ( 40 replicates per treatment ) . Starting at 50% , the frequency of nath-10 ( haw6805 ) individuals decreased across generations in both culture conditions ( Figure 8 ) . Indeed , after 24 transfers to new culture plates in continuous growth conditions ( ≈12 generations ) , JU1648 frequency reached 4 . 5% . The allele dynamics over generations fitted a 25 . 9%±4 . 5% selective advantage of the N2 strain . In the starvation treatment , its selective advantage was estimated to be 13 . 5%±8 . 7% . Note that these values are estimates based on approximating the number of generations per transfer . The number of generations and the treatment both presented a significant effect on the frequency of JU1648 individuals in a generalized linear model , while the interaction term was not significant ( Table S7 ) . The competitive advantage of N2 could either be due to the nath-10 ( N2 ) allele or to another polymorphism in the introgressed region of JU1648 . To distinguish between these two possibilities , N2 was competed in continuous growth conditions against two other strains ( JU2041 and JU2047 ) with very fine introgressions of nath-10 ( haw6805 ) into the N2 genetic background . nath-10 ( haw6805 ) is the only allele shared by JU2041 , JU2047 , and JU1648 that differs with N2 ( Figure S5A ) . Furthermore , JU2041 is expected to present only two nucleotide polymorphisms with N2 , namely the nath-10 allele and an intergenic SNP that is specific to LSJ1 ( Table S2 and Figure S5A ) . The frequencies of JU1648 , JU2041 , or JU2047 individuals all decreased when competed against N2 ( Figure 8 ) , which strongly suggests that nath-10 ( N2 ) contributes to the increased fitness of N2 . In the experiments with JU2041 and JU2047 , the selective advantage of N2 per generation was respectively 9 . 8%±8 . 2% and 9 . 6%±8 . 3% . The difference with the 25 . 9% estimated from the independent experiment with JU1648 may be due to environmental factors , very recent mutations , epigenetic effects , or another polymorphism in the larger introgressed region of JU1648 . A candidate is the coding polymorphism in the gld-2 gene , which also appeared during N2 laboratory culture [38] . Indeed , while the finer introgressions in JU2041 and JU2047 carry the derived gld-2 ( N2 ) allele ( Table S2 ) , JU1648 kept the wild gld-2 ( haw7249 ) allele . gld-2 is known to regulate germ line development [54] , [55] . The presence of gld-2 ( haw7249 ) may also explain possible phenotypic differences between JU1648 and other introgressed lines ( not significant in our analyses , but reproducibly observed ) , such as a stronger reduction of fertility in JU1648 ( Figure 6B ) . To conclude , these experiments show that the derived nath-10 ( N2 ) allele confers a strong competitive advantage in two different laboratory conditions . This result raises the possibility that nath-10 ( N2 ) evolved as an adaptation to the laboratory environment , although it is impossible to show this with certitude .
Phenotypic evolution is characterized in many phylogenetic lineages by periods of stasis followed with rapid diversification that do not correlate with genetic divergence . This non-linear relationship between genetic and phenotypic diversity is best explained by the expression of standing cryptic variation when a strong environmental or genetic perturbation occurs . The release of cryptic genetic variation in stressful conditions could facilitate adaptation to novel environments , as suggested by a recent study in which an artificial ribozyme population with accumulated cryptic variation displayed faster adaptation to a new substrate than a population without standing cryptic genetic variation [56] . Importantly , in this experiment , the increased evolutionary rate relied on extensive epistasis among cryptic polymorphisms . While individual mutations do not strongly affect fitness , rare beneficial combinations of several alleles occurred at higher frequency in the population that previously accumulated cryptic genetic variation [56] . Studying the genetic architecture of cryptic variation ( i . e . , its prevalence , the direction of its effects , and the epistasis between loci ) and its molecular nature in more natural systems is thus crucial to assess its potential evolutionary role . Cryptic genetic variation has previously been mapped for flowering traits in wild teosintes [17] and for the determination of the somatic sex in two C . elegans strains [7] . Both studies showed a polygenic basis for cryptic variation of these developmental traits , with alleles of opposite effects found in the same wild strain and no significant epistatic interactions between loci . These results confirmed experimentally that cryptic variation was prevalent in robust systems . However , the underlying molecular polymorphisms were not identified . In a higher resolution but less global study , association mapping was used to identify at the nucleotide level some of the polymorphisms responsible for cryptic variation of photoreceptor differentiation in wild Drosophila melanogaster lines [18] . A significant part of the phenotypic variation revealed with a dominant gain-of-function Egfr allele was explained by several interacting SNPs located at the Egfr locus itself . Interestingly , the rarer alleles tended to display more severe effects , suggesting that cryptic variation may be affected by purifying selection . More recently , several QTLs for which the effect on growth rate depended on both activity of the Hsp90 chaperone and culture conditions were detected in a cross between a laboratory strain and a wild isolate of Saccharomyces cerevisiae . Four causative polymorphisms were subsequently mapped to the gene level [19] . A major difference with our study is that yeast growth rate is much less robust to environmental and genetic variation than the C . elegans vulval index . The C . elegans nath-10 polymorphism most probably arose in conditions where it did not affect the vulva , whereas it is not clear whether the QTLs detected in yeast accumulated cryptically regarding growth rate . In our study , we detected few QTLs , whose effect on vulval induction depended both on the presence of a sensitizing mutation and on temperature . Other loci of smaller effect were probably missed due to low power of our analysis , as suggested by the fraction of genetic variance that still remains unexplained . However , we were able to precisely map one major effect QTL to a coding polymorphism in the nath-10 gene and another to the region of npr-1 . The two QTLs display opposite additive effects on vulval induction , with nath-10 ( haw6805 ) increasing vulval index and npr-1 ( g320 ) ( or another closely linked allele ) decreasing it . The role of these genes in vulval induction was previously unknown , showing that cryptic variation does not necessarily affect the same genes that were found to affect the trait in classical genetic screens . The non-synonymous nath-10 polymorphism affects both vulval induction and germ line development . In order to understand how vulval and germ line development are affected by this polymorphism , it will be crucial to determine the expression pattern of nath-10 , as well as its site of action , the molecular activity of the NATH-10 protein and its binding partners . Based on sequence similarity with orthologs , NATH-10 belongs to the GNAT superfamily of protein N-acetyltransferases . The best conserved part between human NAT10 and C . elegans NATH-10 corresponds to the putative N-acetyltransferase domain , making it likely that NATH-10 possesses a protein acetyltransferase activity . The amino-acid change caused by the nath-10 polymorphism is located in this domain . Histones are well-known acetyltransferase substrates and their acetylation is usually associated with transcriptional activation [57] . NATH-10 could thus regulate gene expression through histone acetylation . However , other proteins can be acetylated and constitute potential targets for NATH-10 . For instance , the activity of signaling pathways can be controlled by acetylation of some of their components , as is the case for Wnt signaling [58] . Vulval induction can be modulated through a change in the activity of the EGF/Ras , Delta/Notch , or Wnt/βcat signaling pathways in Pn . p cells [20] . We did not detect a significant effect of the nath-10 polymorphism on expression of the egl-17::cfp reporter of the EGF/Ras pathway activity ( unpublished data ) , either because the nath-10 polymorphism acts at other levels in the signaling network or because of too little power to detect small reporter variations . NATH-10 could affect vulval induction and germ line development either cell-autonomously or not . A transcriptional nath-10::gfp reporter [59] is expressed in many tissues during larval stages or adulthood , including the Pn . p cells and intestine . Germ line expression could not be detected , yet this may be due to germ line transgene silencing . It is possible that NATH-10 functions in a single tissue to control both vulval and germline development . For instance , four proteins required in the germ line for spermatogenesis ( FBF-1 , FBF-2 , FOG-1 , and FOG-2 ) were shown to inhibit vulval induction through translational repression of the egf/lin-3 mRNA in the germ line [60] . Further work will be required to study the biological functions of the essential nath-10 gene and to understand how these functions are affected by the nath-10 coding polymorphism . The inactivation of nath-10 either with the null allele tm2624 or by RNAi indicates that the coding polymorphism only affects a subset of all gene functions . Indeed , nath-10 ( tm2624 ) leads to fully penetrant embryonic lethality at the homozygous state . Depending on the intensity of the treatment , nath-10 ( RNAi ) causes complete developmental arrest at the L1 stage or strong sterility accompanied by partially penetrant absence of oogenesis and diverse gonad malformations . These defects are consistent with previous results showing that nath-10 ( RNAi ) led to abnormal expression of sex-specific gonadal markers [43] . Remarkably , total inactivation of nath-10 causes sterility , while the partial loss-of-function caused by the nath-10 ( N2 ) allele increases fertility . The introduction of wild isolates into the environment of the laboratory strongly impacts their evolutionary trajectory and especially may increase their rate of phenotypic evolution [61]–[66] . The laboratory is a novel and usually more uniform and benign environment , with altered dynamics of population growth compared to natural habitats . Some adaptations to laboratory conditions were phenotypically characterized in Drosophila species but the underlying genetic bases were not identified [67] , [68] . In C . elegans , only recently were the consequences of the early laboratory evolution of the N2 reference strain considered [34] , [49] . N2 evolved a preference for high O2 and low CO2 concentrations on food , which strongly affects the behavior of the laboratory strain compared to wild isolates . This phenotypic variation was associated with two polymorphisms in the npr-1 and glb-5 genes [34] . Two other laboratory strains of C . elegans and one strain of C . briggsae that were cultivated for years at high population density display parallel evolution for insensitivity to pheromone-induced dauer formation [38] . Here , we show that the laboratory-derived N2 allele of nath-10 confers a strong selective advantage in competition assays performed in laboratory conditions . Direct assessment of the adaptive role of the nath-10 polymorphism was possible thanks to fine introgressions of nath-10 ( haw6805 ) from different wild isolates into the N2 background and to direct quantification of allele frequencies by pyrosequencing . This method avoids the use of a tester fluorescent strain whose fitness might be affected by the presence of the reporter gene [69] , [70] . Despite its strong positive fitness effects in laboratory conditions , the nath-10 ( N2 ) allele would likely be outcompeted in the long term in wild conditions , since it modifies an otherwise broadly conserved amino-acid . Different traits may explain the fitness effect of the nath-10 polymorphism in the laboratory environment . First , the nath-10 polymorphism finely modulates the number of sperm produced in young adult hermaphrodites , with the N2 allele resulting in a 10% increase . As expected , this effect on sperm production is associated with a longer minimal generation time and an increased lifetime fecundity in N2 , two phenotypes with opposite effects on population growth rate , resulting in a fitness trade-off [51] , [71] . Using a different assay to evaluate fitness ( the “eating race” ) , a 50% increase in sperm production was previously shown to be a disadvantage in the N2 genetic background [51] . Our results , which are not inconsistent with this observation , suggest that a 10% decrease of brood size relative to N2 is also a disadvantage . Therefore , the total number of sperm produced by N2 hermaphrodites seems to have evolved toward a new optimum in the laboratory . The optimal sperm number is likely to depend on environmental conditions and on the genetic background [52] , [72] . Indeed , theoretical modeling and experiments based on competition between genotypes obtained through artificial mutagenesis indicated that production of more sperm was favored in some environmental conditions but not others [72] . Importantly , hermaphrodite fertility is not always sperm-limited: sperm are produced in excess when worms are grown on compost or other food than E . coli [73] and temperature variations may reduce brood size independently of sperm number [72] . Therefore , the production of more sperm should be selectively favored in laboratory strains maintained on E . coli at 20°C , compared to wild isolates for which sperm number may not be limiting fertility . Consistently , most wild C . elegans isolates display a smaller brood size than the N2 strains from the Caenorhabditis Genetics Center [53] , [74] . In addition , the earlier frozen “ancestral N2” strain presents a lower brood size than the standard N2 strain ( D . Gems , personal communication ) . Both N2 strains carry the nath-10 ( N2 ) allele , suggesting that sperm number may have repeatedly increased in the laboratory through the fixation of several successive mutations . Although this increased sperm production could be involved in the adaptation of N2 to the laboratory environment , it is probably not the only factor contributing to the competitive advantage conferred by the nath-10 ( N2 ) allele . Indeed , a 10% increased sperm number that presents both positive and negative effects on fitness can hardly explain a 10% to 25% selection coefficient . Moreover , for an increased lifetime fecundity to be advantageous , the adults must be able to produce all their progeny before being eliminated , which was rarely the case in our competition assays due to the frequency of transfers . A second character that may contribute to the strongly adaptive role of the nath-10 polymorphism in laboratory conditions is the rate of egg laying . Indeed , nath-10 ( N2 ) can confer up to 20% faster egg laying in the middle of adult reproductive life , which is expected to directly increase fitness . Since nath-10 ( RNAi ) leads to strong oogenesis defects , the effect of the nath-10 polymorphism on egg laying rate must also be mediated through a subtle regulation of nath-10 activity in oogenesis . Finally , uncharacterized phenotypes might also participate in the competitive advantage of nath-10 ( N2 ) in the laboratory environment . Our results suggest that pleiotropic selection may play an important role in the evolution of cryptic genetic variation . Pleiotropic selection should occur when several characters share common genetic regulators and the evolution of one of these characters is driven by selection acting on another character [75] , [76] . In the present case , the nath-10 polymorphism that cryptically affects vulval development may have evolved due to pleiotropic selection on sperm production and egg laying rate . Our results open interesting avenues for thinking about the relationship between pleiotropy and the evolution of robust systems . Robustness to mutations could contribute to alleviate the so-called “cost of complexity” according to which complexity decreases the rate of adaptation due to pleiotropy [77] . Indeed , the more genetic robustness is widespread in biological systems , the less deleterious are the pleiotropic effects of a random mutation , on average . Conversely , non-cryptic pleiotropic effects influence the accumulation of genetic variation . Cryptic mutations with pleiotropic effects should on average be more readily eliminated by natural selection than strictly cryptic ( neutral ) polymorphisms , while at the same time those whose non-cryptic effects are positively selected should accumulate at a faster rate than strictly cryptic polymorphisms . Thus , pleiotropy should in theory restrain and bias the accessible genotypic space for cryptic genetic variation . The prevalence and the evolutionary impact of cryptic genetic variation could thus be influenced by the distribution of pleiotropy [78] . Finally , a central assumption of evo-devo is that adaptive mutations mainly affect cis-regulatory regions because of a more restricted pleiotropy compared to coding changes [79] , [80] . This idea is currently debated due to the accumulation of empirical data showing that phenotypic evolution involves both regulatory and coding mutations [81] , [82] . In this context , the nath-10 polymorphism is remarkable as an example of adaptive evolution that affects a coding sequence and at the same time displays restricted pleiotropy . Indeed , this polymorphism only affects a subset of all traits altered by the inactivation of the essential gene nath-10 . The restricted pleiotropy of a coding mutation can be explained either by an altered interaction of the protein with tissue-specific factors or by different degrees of genetic robustness among the phenotypes regulated by the protein . The latter case applies concerning vulval cell fate pattern versus the timing of sperm-oocyte transition . In the future , molecular identification of cryptic variation in other systems will be required to determine its degree of pleiotropy and its cis-regulatory versus coding nature .
Recombinant strain genotypes are listed in Tables S1 and S2 . Transgenic strains are listed in the section on transgenesis below . Strains were thawed less than six generations before phenotypic observation to avoid mutation accumulation . The strains were bleached at the first generation after thawing to eliminate possible contaminants . Well-fed strains were maintained at 20°C on standard 55 mm NGM plates , all poured the same day and seeded with the same liquid culture of Escherichia coli OP50 for food . Adults were shifted on fresh plates at the relevant temperature one generation prior to observation . Strains were scored on the same day in parallel for each experiment or replicate . The number of Pn . p cells that adopted a vulval fate was scored in L4 larvae , as described previously [83] . Briefly , worms were mounted on pads of 5% noble agar , 10 mM sodium azide in M9 . The number and orientation of cells of the vulval epithelium were observed under Nomarski optics ( 100× objective ) . These cell lineage outputs at the L4 stage allowed us to infer the number of Pn . p cells that were induced at the L3 stage . For a given strain , the vulval index represents the mean number of induced cells in different animals . The wild-type vulval index is 3 , and upon perturbation can range from 0 to 6 ( when P3 . p to P8 . p cells are all induced ) . The let-23 ( sy1 ) allele was previously introgressed into the genetic background of several wild isolates [10] . JU605 and JU606 carry this artificial mutation in the N2 and AB1 backgrounds , respectively . Sixty recombinant inbred lines ( RILs ) were generated from a cross between JU605 hermaphrodites and JU606 males . F1 cross-progeny were distinguished from F1 self-progeny by genotyping two RFLP markers ( pkP1071 and pkP5082 ) in the corresponding F2 larvae . The RILs were initiated from 60 F2 individuals randomly isolated among the offspring of 3 F1 cross-progeny . The 60 lines were isogenized through 12 generations of selfing of one random animal per generation and frozen down . RILs were genotyped for 50 single nucleotide polymorphisms ( SNPs ) distinguishing N2 and AB1 and distributed along most of the genome ( Table S1 ) . Most SNP markers were chosen from genotyping data on C . elegans wild isolates [49] , except mfP11 , mfP12 , and mfP13 , which were deduced from the whole-genome sequencing of AB1 ( L . Stein et al . , personal communication ) . Forty-eight SNP markers were genotyped by the Integragen company using SNPlex technology and two SNP markers were genotyped by pyrosequencing using a PyroMark Q96 ID instrument ( Biotage ) . All genotypes were determined from purified genomic DNA prepared using the DNeasy Blood & Tissue Kit ( Qiagen ) . The vulval index was determined in the 60 RILs grown at 20°C ( two replicates ) and at 25 . 5°C ( two replicates ) . For each replicate , five gravid adults were picked on 3 plates per RIL and all lines were cultured in parallel at the appropriate temperature ( 20°C or 25 . 5°C ) . After 52 ( 20°C ) or 40 h ( 25 . 5°C ) , all plates were transferred to 7°C in order to stop further development of the progeny past the L4 stage . Scoring at the L4 stage could be performed up to 2 d after transfer at 7°C . Two experimenters scored the vulval index of 30 L4 larvae per RIL for the 60 lines , following the method described above . This treatment allowed us to score all RILs in parallel and thus minimize environmental effects . From these genotypic and phenotypic data ( Table S1 ) , QTL analyses were performed using composite interval mapping [84] in QTL cartographer v1 . 16 [85] , [86] , with model 4 for markers used as cofactors . Under this model , the most significant marker on each chromosome ( except for the tested chromosome ) is used to control for genetic background . Four analyses were performed using each phenotypic replicate ( two at 20°C and two at 25 . 5°C ) . A fifth analysis was performed using as trait value the difference in vulval index between 25 . 5°C and 20°C ( in the replicates that were scored in parallel ) to map the phenotypic plasticity to temperature change . Several near-isogenic lines ( NILs ) were established to finely map the chromosome I QTL . Several hermaphrodites from the three RILs that presented the highest vulval index at 20°C ( RIL5 , RIL15 , and RIL38; Table S2 ) were crossed to JU605 males . In F2 , L4 larvae that displayed a normal vulval invagination under the dissecting microscope were backcrossed to JU605 males . Three rounds of vulval phenotype selection and backcross in F2 were followed by 13 generations of selfing to obtain homozygous near-isogenic lines . Worms were grown at 20°C instead of 25 . 5°C during NIL construction because the temperature effect had not yet been found . The NILs that showed the highest vulval index at 25 . 5°C shared a region of AB1 genotype in the center of chromosome I ( Table S2 ) . To further narrow down the QTL region , we selected 20 lines with a recombination event in the QTL interval on chromosome I . Hermaphrodites from NIL11 ( cross A ) and NIL13 ( cross B ) were crossed to JU605 males . 312 ( cross A ) and 320 ( cross B ) F2 progeny were isolated and selfed until the F5 generation . One F5 adult from each plate was genotyped for two SNP markers surrounding the QTL region: markers haw6686 and haw7143 for cross A and markers mfP11 and haw7143 for cross B ( AB1 alleles in NIL11 and NIL13 ) . Twenty lines ( 10 for each cross ) presented the N2 allele at one marker and the AB1 allele at the other marker . The 20 lines were genotyped for several additional SNPs in the QTL region and scored for vulval index at 25 . 5°C ( Table S3 ) . This restricted the QTL to a 186 kb interval . Three such lines were used for further studies ( JU1620 and JU1624 from cross A and JU1610 from cross B ) . SNP genotyping in the NILs was performed by pyrosequencing using a PyroMark Q96 ID instrument . To confirm the effect of the nath-10 polymorphism , we established a NIL ( JU2000 ) from a cross between LSJ1 hermaphrodites and JU605 males . nath-10 ( haw6805 ) ; let-23 ( sy1 ) F2 progeny were backcrossed 10 times to JU605 males to introgress the LSJ1 nath-10 allele into the N2 background , with molecular selection of nath-10 ( haw6805 ) . To generate the JU1961 , JU1648 , JU2003 , and JU2002 strains , the let-23 ( sy1 ) mutation was removed by crosses of N2 males with JU1620 , JU1648 , JU1610 , and JU2000 , respectively . The let-60 ( n1046 ) mutation was introduced into the JU1624 background by a cross with JU601 males to generate the JU1756 line . The construction of JU601 and JU473 strains was previously described [10] . Finally , JU2041 and JU2047 strains present finer introgressions of nath-10 ( haw6805 ) from the LSJ1 and AB1 backgrounds into N2 . These two strains were obtained by crossing JU2002 or JU2003 hermaphrodites to N2 males and by selecting for F5 individuals that carried the nath-10 ( haw6805 ) allele and a N2 allele at an adjacent marker ( mfP17 for JU2041 and haw6686 for JU2047 ) . The let-23 ( sy1 ) allele was introduced into JU2041 and JU2047 backgrounds by crossing the two lines with JU605 , yielding the JU2133 and JU2135 strains . From these crosses , we also selected as a control individuals presenting the nath-10 ( N2 ) genotype that founded the JU2134 and JU2136 strains . The genotypes of all NILs are presented in Table S2 . N2 and AB1 sequences corresponding to the 183 kb QTL region ( region spanning from 5190795 bp to 5376700 bp on chromosome I ) were compared to find all polymorphisms present in this genomic interval . N2 sequence was obtained from wormbase ( www . wormbase . org ) and AB1 sequence was obtained through whole-genome Illumina sequencing of the AB1 strain used to build the JU606 strain ( L . Stein et al . , personal communication ) . Nine SNPs could be detected by comparing these N2 and AB1 sequences , including the nath-10 polymorphism . Sanger sequencing revealed that six of these SNPs were false positive due to errors in the AB1 sequence ( at positions 5315591 , 5330853 , 5333385 , 5333386 , 5336190 , and 5340310 ) and two were false positive due to errors in the N2 sequence ( at positions 5221052 and 5301101 ) . In addition , the AB1 sequence presented 149 gaps in the QTL region ( ranging from 1 to 50 bp ) that were not covered by the Illumina sequencing . Sanger sequencing of the 149 gaps in AB1 revealed two additional SNPs in the QTL region named haw6786 and mfP14 ( see Table S2 for alleles ) . SNP genotyping based on pyrosequencing technology ( PyroMark Q96 ID instrument from Biotage ) was used to select the homozygous nath-10 ( haw6805 ) F2 ( or F3 ) individuals in the different lines described above and to determine the distribution of the nath-10 polymorphism in C . elegans wild isolates . Single worm PCRs were performed in 50 µl reactions [87] using GoTaq DNA polymerase ( Promega ) , with the following primers: forward 5′-GCCGGGAACGAGGAAAAGTCAAATG-3′ and biotinylated reverse 5′-[Btn]TTCGGACTCACTGTTCC-3′ . The purification of single-stranded PCR amplicons and the pyrosequencing reactions were performed according to the manufacturer's instructions using the following sequencing primer: 5′-GTTCGAGTCCTTTCAG-3′ . Transgenic lines with non-integrated arrays were established according to standard techniques [88] . The coding sequence of nath-10 plus upstream and downstream intergenic regions were amplified by PCR from JU605 or JU606 genomic DNA using Phusion DNA polymerase and the following primers: forward 5′-ATGGCCAATGATTGGGATGCTG-3′ and reverse 5′-CTGAAGATTACGGTACGAGGTCTCG-3′ . PCR products were gel-purified using the Wizard SV Gel and PCR Clean-Up System ( Promega ) . Three different mixes of DNA were independently injected into the gonad of adult worms: mix 1 and mix 2 contained , respectively , 0 . 2 ng/µl of nath-10 PCR product from JU605 or JU606 , 10 ng/µl of pWD47 , and 140 ng/µl of pBluescript; mix 3 contained 10 ng/µl of pWD47 and 140 ng/µl of pBluescript and served as a negative control . pBluescript phagemid was used as carrier DNA and the Pmyo-2::DsRed construct ( pWD47 plasmid ) as coinjection marker . nath-10 PCR products were injected at only 0 . 2 ng/µl because higher concentrations ( ≥1 ng/µl ) led to sterility of the F1 progeny . Each mix was injected into JU605 and JU1620 and for each of the four possible combinations two independent transgenic lines were scored for vulval index . Overexpression of nath-10 ( N2 ) in a nath-10 ( N2 ) endogenous context: JU1953: nath-10 ( N2 ) I; let-23 ( sy1 ) II; mfEx54[nath-10 ( N2 ) , myo-2::DsRed]; JU1954: nath-10 ( N2 ) I; let-23 ( sy1 ) II; mfEx55[nath-10 ( N2 ) , myo-2::DsRed] . Overexpression of nath-10 ( haw6805 ) in a nath-10 ( N2 ) endogenous context: JU1887: nath-10 ( N2 ) I; let-23 ( sy1 ) II; mfEx46[nath-10 ( haw6805 ) , myo-2::DsRed]; JU1888: nath-10 ( N2 ) I; let-23 ( sy1 ) II; mfEx48[nath-10 ( haw6805 ) , myo-2::DsRed] . Overexpression of nath-10 ( N2 ) in a nath-10 ( haw6805 ) endogenous context: JU1951: nath-10 ( haw6805 ) I; let-23 ( sy1 ) II; mfEx52[nath-10 ( N2 ) myo-2::DsRed]; JU1952: nath-10 ( haw6805 ) I; let-23 ( sy1 ) II; mfEx53[nath-10 ( N2 ) myo-2::DsRed] . Overexpression of nath-10 ( haw6805 ) in a nath-10 ( haw6805 ) endogenous context: JU1889: nath-10 ( haw6805 ) I; let-23 ( sy1 ) II; mfEx47[nath-10 ( haw6805 ) , myo-2::DsRed]; JU1890: nath-10 ( haw6805 ) I; let-23 ( sy1 ) II; mfEx49[nath-10 ( haw6805 ) , myo-2::DsRed] . For each line , five culture plates containing 10 adult worms expressing myo-2::DsRed were grown at 25 . 5°C for 44 h . The vulval index was scored on progeny that express myo-2::DsRed , and also on progeny that spontaneously lost the transgene and did not express myo-2::DsRed ( for lines injected with mix 1 and 2 ) . This additional control allowed us to distinguish zygotic effects from maternally or epigenetically inherited effects by directly comparing the vulval index of animals sharing the same mother . The animals were fed with bacteria from the Ahringer library [89] expressing dsRNA targeted against nath-10 or with control bacteria containing the empty RNAi vector L4440 . In the case of JU605 , JU606 , and JU1624 , five adults were placed on four RNAi plates for each worm line and for each bacterial strain in two replicate experiments . After 44 h at 25 . 5°C , L4 progeny were scored for vulval induction . RNAi against nath-10 could not be applied for several generations because it led to strong sterility of the progeny . In the case of N2 , several adults were grown at 25°C on RNAi plates in parallel to control plates . The worms had to be grown at 25°C so that the progeny reach the adult stage . Indeed , when applied to adult worms cultured at 20°C , nath-10 ( RNAi ) led to complete arrest of the progeny at the L1 stage . After 100 h of growth at 25°C , adult progeny were either directly mounted on pads of 5% noble agar , 10 mM sodium azide in M9 ( Figure S4 ) , or fixed and mounted in DAPI Vectashield ( Figure 7C and 7D ) . Images of the gonads were acquired on a Zeiss AxioImager M1 microscope equipped with a Photometrics CoolSnap ES CCD camera driven by the Metaview 6 . 3r7 software . Vulval induction of heterozygous F1 cross-progeny ( nath-10 ( N2 ) /nath-10 ( haw6805 ) ) was compared to that of control homozygous cross-progeny to determine the dominance relationship between the two alleles . Practically , we scored reciprocal crosses between JU605 and JU606 or JU1620 as well as control crosses of JU605 , JU606 , and JU1620 strains . For each cross , one 8-d-old ( sperm depleted ) hermaphrodite was mated to five young males on each of 10 plates . The mating plates were grown at 25 . 5°C for 40 h and the vulval induction index of L4 hermaphrodite progeny was scored from plates that showed about 50% of males . The effect of the null allele nath-10 ( tm2624 ) on vulval induction was assessed in heterozygous nath-10 ( N2 ) /nath-10 ( tm2624 ) animals carrying the egfr/let-23 ( sy1 ) sensitizing mutation . First , as the tm2624 deletion is embryonic lethal , it was maintained in an heterozygous state using the szT1 balancing translocation between chromosomes I and X [90] . The JU1982 strain ( tm2624/szT1[lon-2 ( e678 ) ] I; +/szT1 X ) was obtained by crossing heterozygous nath-10 ( N2 ) /nath-10 ( tm2624 ) hermaphrodites generated by the National BioResource Project to AF1 males ( +/szT1[lon-2 ( e678 ) ] I; dpy-8 ( e1321 ) unc-3 ( e151 ) /szT1 X ) . JU1988 ( tm2624/szT1[lon-2 ( e678 ) ] I; let-23 ( sy1 ) /let-23 ( sy1 ) II; +/szT1 X ) was then established from a cross between JU1982 and JU605 . The JU1989 strain ( +/szT1[lon-2 ( e678 ) ] I; let-23 ( sy1 ) /let-23 ( sy1 ) II; dpy-8 ( e1321 ) unc-3 ( e151 ) /szT1 X ) obtained by crossing JU605 to AF1 was used to control for the effect of the szT1 translocation on vulval induction . The tm2624 allele leads to a deletion of 618 bp ( replaced by a TCA triplet ) in the nath-10 coding region that could be followed by PCR using the forward 5′-CGACCACCATAGCCCATTGAC-3′ and reverse 5′-GGTCGTGGACGTGGAAAGTCT-3′ primers . The vulval induction index of JU1988 and JU1989 was scored at 25 . 5°C as described above . The JU1803 line ( mfIR16[nath-10 ( haw6805 ) ]; lin-15A ( n767 ) ) was obtained from a cross between MT1806 ( nath-10 ( N2 ) ; lin-15A ( 767 ) ) hermaphrodites ( from CGC ) and JU1648 ( mfIR16[nath-10 ( haw6805 ) ] ) males . F2 individuals with the correct genotype were selected after pyrosequencing of nath-10 and Sanger sequencing of lin-15 . The same method was employed to establish the JU1804 line ( mfIR16[nath-10 ( haw6805 ) ]; lin-15B ( n744 ) ) from a cross between MT2495 ( nath-10 ( N2 ) ; lin-15B ( n744 ) ) hermaphrodites ( from CGC ) and JU1648 males . The MT1642 ( nath-10 ( N2 ) ; lin-15AB ( n765 ) ) strain ( from CGC ) was used to show the effect of a double mutant of class A and B SynMuv genes . The vulval induction index was scored in strains grown in parallel at 25 . 5°C . A local alignment was performed on the Expasy proteomics server using the BLOSUM62 comparison matrix with default settings ( gap open penalty = 12 , gap extension penalty = 4 ) and displayed using the LALNVIEW graphical viewer program . GNAT-related N-acetyltransferase domain ( amino-acids 558–753 ) and a putative ATP binding domain ( amino acids 284–291 ) were identified using bioinformatic tools [39] . The npr-1 ( g320 ) allele was introduced into the genetic background of JU605 ( nath-10 ( N2 ) ; let-23 ( sy1 ) ; npr-1 ( N2 ) ) and JU1624 ( nath-10 ( haw6805 ) ; let-23 ( sy1 ) ; npr-1 ( N2 ) ) strains . To this end , DA650 ( npr-1 ( g320 ) ) hermaphrodites ( from CGC ) were crossed to JU605 males . Several egg laying defective F2 progeny were isolated at the L4 stage and a single F3 progeny from a plate that presented a majority of egg laying defective and clumping adults was used to establish the JU1617 strain ( nath-10 ( N2 ) ; let-23 ( sy1 ) ; npr-1 ( N2 ) ) . JU1617 hermaphrodites were then crossed to JU1624 males and a similar strategy was employed to generate the JU1650 line ( nath-10 ( haw6805 ) ; let-23 ( sy1 ) ; npr-1 ( g320 ) ) with pyrosequencing of the nath-10 allele in the F3 progeny . The vulval induction index was scored in JU605 , JU1617 , JU1624 , JU1650 , and JU606 strains grown in parallel at 25 . 5°C . The frequency of P12 to P11 cell fate transformation was scored in strains carrying the lin-45 ( n2018 ) /raf mutation combined with either the N2 or the AB1 nath-10 allele . In these strains , the reduction of Ras pathway activity can lead the P12 cell to adopt a P11-like cell fate . The penetrance of this phenotype was assessed by counting the number of P11 . p-like and P12 . pa-like cells at the L4 stage under Nomarski optics ( 100× objective ) based on the morphology and position of cell nuclei [91] . Strains were synchronized by 2 h of egg laying on several plates at 20°C and progeny were incubated for 44 h at 27°C . On each plate , dauer and non-dauer larvae were enumerated under the dissecting microscope based on the characteristic morphology of dauers . The strains were synchronized by 1 h of egg laying of 20 adults on one plate , for two consecutive generations ( because the second generation appeared to lay eggs that were better synchronized ) . For each strain , 20 larvae were isolated on separate 55 mm culture plates 24 h after the second synchronization . From 58 h post-synchronization , plates were checked every hour for laid eggs until all isolated hermaphrodites reached reproductive maturity . The age at maturity had been calculated as the difference between the time when the first eggs were observed and the time when the parent itself was laid ( estimated as the middle time point of the 1 h egg laying period ) . All plates were subsequently kept at 20°C for fertility assessment . The animals were grown at 20°C . Brood size was assessed in three replicate experiments , following the protocol described for the scoring of the age at maturity . The three replicates were treated similarly , except that the strains were synchronized for one generation in two replicates and for two consecutive generations in the last one ( both age at maturity and fertility are shown here for this last replicate ) . After maturation , adults were transferred twice per day on fresh plates during 3 d and then once per day until no more fertilized eggs were laid . The total brood size of a given adult was calculated as the sum of the progeny that reached the L3–L4 stage , as counted on each plate . For each strain , 20 adults were grown in parallel at 20°C and the rare ones that died prematurely were discarded from the analysis . The transfer of adults to new plates during the fertility experiments allowed us to estimate the egg laying rate at different broad periods of their reproductive life . This rate was calculated by dividing the number of progeny that reached the L3–L4 stage on a given plate by the duration of adult egg laying on that plate . The egg laying rate varied during adulthood and usually reached its maximum in the period spanning 20 to 30 h after sexual maturity . The total number of spermatids produced per gonad arm was counted in young N2 and JU2002 adults ( 39 per strain ) fixed in −20°C ethanol and stained with DAPI . Briefly , the strains were synchronized by 2 h of egg laying on 10 plates per strain with 20 adults per plate and the resulting progeny were fixed after 62 h of culture at 20°C . Worms were then mounted on Vectashield DAPI and Z-series fluorescence images of selected gonad arms were acquired on a Zeiss AxioImager M1 microscope ( 100× objective ) . Individual spermatid DNA could be clearly distinguished for only one gonad arm per animal ( the one closest to the coverslip ) . In order to score gonad arms where spermatogenesis was completed , but where fertilization did not yet start , we selected animals where ovulation started in only one gonad arm and scored the other arm . After acquisition , the Z-series ( 20 images spaced by 1 µm ) for each animal was projected onto a single plane using ImageJ 1 . 43r and spermatids were counted on the screen . Four competition experiments involving different strains and culture conditions were performed to assess the adaptive value of the nath-10 ( N2 ) allele in the laboratory . In the first two assays , individuals of the N2 strain were allowed to compete against individuals of the JU1648 strain ( Table S3 ) that present the nath-10 ( haw6805 ) allele introgressed from the AB1 background into the N2 background . In these experiments , worms were grown in parallel in two different environmental conditions that could potentially reflect the culture conditions when the nath-10 polymorphism first appeared , namely continuous growth on OP50 or alternation of growth and starvation . In addition , two competition experiments were performed with different strains in continuous growth conditions in order to control for the effect of the introgressed regions . For this purpose , two near-isogenic lines were constructed as described above and allowed to compete against N2 . JU2041 ( mfIR24 ( I;LSJ1>N2 ) was obtained from a cross between JU2002 and N2 , while JU2047 ( mfIR27 ( I;AB1>N2 ) ) was obtained from a cross between JU2003 and N2 ( Table S2 ) . nath-10 ( haw6805 ) is the only polymorphism with N2 shared by JU1648 , JU2041 , and JU2047 . For each assay , 40 replicates were cultured in parallel on 6 cm diameter NGM dishes seeded with one drop of OP50 . All replicate cultures were started with seven L4 individuals of each of the two competing strains placed in the center of the E . coli lawn . For the continuous growth treatment , populations of worms were transferred to fresh plates by cutting out a chunk of agar at fixed intervals before bacteria depletion . A 0 . 5×0 . 5 cm2 piece of agar containing at least 100 individuals was cut out from the middle of the bacterial lawn of old plates and deposited at the edge of the bacterial lawn on fresh culture plates . The first transfer was made 78 h after the beginning of the experiments to allow sufficient growth of the initially small population . The next transfers were performed approximately every 42 h . For the growth/starvation treatment , populations were transferred by cutting out an agar chunk ( containing at least 200 individuals ) once a week at a fixed time point . Worms were fed for the 2–3 d following each transfer and then starved for the next 4–5 d . C . elegans populations were grown at 20°C for all competition assays . For each replicate , the proportion of N2 individuals was assessed at different time points during the competition experiment ( Figure 8 ) through quantification of the frequency of nath-10 alleles using pyrosequencing . For the population in continuous growth , allele frequencies were determined from old plates before starvation and after the transfer to the new dish . For the growth/starvation treatment , subcultures were initiated each week in parallel to the experimental populations to determine allele frequencies from non-starved plates . For DNA preparation , 5 µl of M9 suspensions containing about 100–300 mixed-stage individuals from each culture plate were mixed with 25 µl of worm lysis buffer and proteinase K ( 100 µg/ml ) . After 1 . 5 h of lysis at 60°C and 15 min of inactivation at 95°C , 0 . 5 µl of worm lysate were used as PCR template . The primers and PCR conditions were as described above for nath-10 polymorphism genotyping . Allele frequencies were obtained from the height of the pyrogram peaks using the Allele Quantification tool supplied with the pyrosequencing software of Biotage . To measure the accuracy of this quantification method , a standard curve was performed with different known proportions of alleles . The correlation between observed and real allele frequencies exceeded 0 . 993 and the average standard deviation calculated from a triplicate of observed frequencies was 4% . Except for QTL analyses , all statistical tests were performed with R ( http://www . r-project . org/ ) . For the competition assays between N2 and JU1648 , we used a generalized linear model ( GLM ) to assess the variation of nath-10 ( haw6805 ) allele frequency over time and across growth conditions . This response variable was assumed to follow a Gaussian distribution and a log link function was used . Effects included in the model were generation treated as a number , treatment treated as a nominal variable , and the generation×treatment interaction . The effect of replicates was nested within treatment . For the competition experiments involving JU2041 and JU2047 strains , allele frequencies were assessed at only a few time points . Therefore , we compared the nath-10 ( haw6805 ) frequency at the first and at the last time points using a Mann-Whitney-Wilcoxon test . The relative fitness of nath-10 ( N2 ) over nath-10 ( haw6805 ) was estimated for all assays using the method described previously for selection in haploid organisms , with correction for continuous growth when necessary [92] . Our populations behave as haploid as very few males are present during the competition experiments . The mean generation time in the continuous growth conditions was estimated to be 86 h , which corresponds roughly to 0 . 5 generations per transfer . For the alternated growth/starvation treatment , the growth rate was considered to be one generation per transfer ( worms start to starve about 72 h after transfer to a new plate ) .
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Robustness is a property of biological systems that ensures the production of reproducible phenotypes in spite of underlying environmental , stochastic , and genetic variability . A consequence of robustness is that potentially functional genetic variation is free to accumulate in natural populations because it is buffered at the phenotypic level . Even if this so-called “cryptic” genetic variation has no obvious effects under standard conditions , it may become phenotypically expressed upon major genetic or environmental perturbations . Here we used the model organism Caenorhabditis elegans to identify genetic variations involved in the cryptic evolution of vulval cell fate induction between wild strains . We found that a mutation in the essential nath-10 gene not only contributes to cryptic genetic variation in the vulval system , but also affects key life history traits that are expected to be under a strong selective pressure ( brood size , age at sexual maturity , sperm number and rate of progeny production ) . Indeed , an allele of nath-10 that emerged during the laboratory domestication of C . elegans about 50 years ago confers a strong competitive advantage over the ancestral allele under laboratory conditions . A genetic variation that is cryptic for a robust trait can therefore affect more sensitive phenotypes and thus evolve under selection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
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"animal",
"genetics",
"population",
"genetics",
"evolutionary",
"selection",
"quantitative",
"traits",
"epistasis",
"animal",
"models",
"evolutionary",
"developmental",
"biology",
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"biology",
"caenorhabditis",
"elegans",
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"organisms",
"genetic",
"polymorphism",
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] |
2012
|
Role of Pleiotropy in the Evolution of a Cryptic Developmental Variation in Caenorhabditis elegans
|
Noncoding RNAs ( ncRNAs ) are important functional RNAs that do not code for proteins . We present a highly efficient computational pipeline for discovering cis-regulatory ncRNA motifs de novo . The pipeline differs from previous methods in that it is structure-oriented , does not require a multiple-sequence alignment as input , and is capable of detecting RNA motifs with low sequence conservation . We also integrate RNA motif prediction with RNA homolog search , which improves the quality of the RNA motifs significantly . Here , we report the results of applying this pipeline to Firmicute bacteria . Our top-ranking motifs include most known Firmicute elements found in the RNA family database ( Rfam ) . Comparing our motif models with Rfam's hand-curated motif models , we achieve high accuracy in both membership prediction and base-pair–level secondary structure prediction ( at least 75% average sensitivity and specificity on both tasks ) . Of the ncRNA candidates not in Rfam , we find compelling evidence that some of them are functional , and analyze several potential ribosomal protein leaders in depth .
Recent discoveries of novel noncoding RNAs ( ncRNAs ) such as microRNAs and riboswitches suggest that ncRNAs have important and diverse functional and regulatory roles that impact gene transcription , translation , localization , replication , and degradation [1–3] . In the last few years , several groups have performed genome-scale computational ncRNA predictions based on comparative genomic analysis . In particular , Barrick et al . [4] used a pairwise , BLAST-based approach to discover novel riboswitch candidates in bacterial genomes , many of which now have been experimentally verified . Similar studies have been conducted in various bacterial groups [5–8] . More recent work has extended these searches to eukaryotes [9–13] , discovering a large number of known microRNAs while producing thousands of novel ncRNA candidates . With some exceptions , such as [4] and [13] , these approaches follow a similar paradigm , which is to search for conserved secondary structures on multiple-sequence alignments that are constructed based on sequence similarity alone . Typically , these schemes use measures such as mutual information between pairs of alignment columns to signal base-paired regions . However , the signals such methods seek , namely compensatory base-pair mutations , are exactly the signals that may cause sequence-based alignment methods to misalign , or alternatively refuse to align , homologous ncRNA sequences . Even local misalignments may weaken this key structural signal , making the methods sensitive to alignment quality , which is especially problematic on diverged sequences . In this paper , we present a novel structure-oriented computational pipeline for genome-scale prediction of cis-regulatory ncRNAs . It exploits , but does not require , sequence conservation . The pipeline differs from previous methods in three respects . First , it searches in unaligned upstream sequences of homologous genes , instead of well-aligned regions constructed by sequence-based methods . Second , we predict RNA motifs in unaligned sequences using a tool called CMfinder [14] , which is very sensitive to RNA motifs with low sequence conservation , and robust to inclusion of long flanking regions or unrelated sequences . Finally , we integrate RNA motif prediction with RNA homology search . For every predicted motif , we scan a genome database for more homologs , which are then used to refine the model . This iterative process improves the model and expands the motif families automatically . In this study , we apply this pipeline to discover ncRNA elements in prokaryotes . We chose prokaryotes mainly because of the large number of fully sequenced genomes and the great sequence divergence among the species , which can be well-exploited by our approach . Our approach has two key advantages . First , it is efficient and highly automated . Earlier steps are more computationally efficient than later steps , and we can apply filters between steps so that poor candidates are eliminated from subsequent analysis . Thus , even though we use some computationally expensive algorithms , the pipeline is scalable to larger problems . Besides providing RNA motif prediction , the pipeline also integrates gene context and functional analysis , which facilitates manual biological evaluation . Second , this pipeline is highly accurate in finding prokaryotic ncRNAs , especially RNA cis-regulatory elements . To demonstrate the performance of this approach , we report our search results in Firmicutes , a Gram-positive bacterial division that includes Bacillus subtilis , a relatively well-studied model organism with many known ncRNAs . The method exhibits low false-positive rates on negative controls ( permuted alignments ) , and low false-negative rates on known Firmicute ncRNAs . The RNA family database ( Rfam ) [15] , a partially hand-curated database of noncoding RNAs , includes 13 ncRNA families categorized as cis-regulatory elements with representatives in B . subtilis . Of these , 11 are included among our top 50 predictions and a 12th appears somewhat lower in our ranking . Two other Rfam families are also represented among our top 50 predictions . In addition , both the secondary structure prediction and identified family members are in excellent agreement with Rfam annotation . For the 14 Rfam families mentioned above , we achieved 91% specificity and 84% sensitivity on average in identifying family members , and 77% specificity and 75% sensitivity in secondary structure prediction . Many promising novel ncRNA candidates were also discovered and are discussed below .
To evaluate how many of our top candidates could have arisen by chance , we performed a randomized control experiment . We first computed CLUSTALW alignments of the 100 sequence datasets having the highest motif scores ( before the RaveNnA scan ) . We then randomly permuted the alignments 50 times , maintaining the approximate gap pattern ( see the online supplement at http://bio . cs . washington . edu/supplements/yzizhen/pipeline ) . After degapping each permuted alignment ( treating it as a set of unaligned sequences ) , we applied CMfinder , retaining the top-ranking motif from each randomized dataset . We used this collection of 5 , 000 motifs to estimate the background score distribution , and to infer p-values for predicted motifs in the original datasets . Results are shown in Figure 2 . By this measure , all 100 top-scoring motifs have p-values less than 0 . 1 , with the median at 0 . 016 . In addition , 73 of the 100 candidates in the original dataset score higher than all motifs in the corresponding randomized datasets . Note that this estimation of p-values is imperfect . In particular , with the scoring scheme we used , datasets containing phylogenetically close sequences tend to score well in comparison to more diverged sets , because permuting the CLUSTALW alignments preserves their sequence conservation . ( Independently permuting individual sequences instead of alignments would be less realistic , since in practice cis-regulatory RNA motifs are often embedded in regions exhibiting some sequence conservation for other reasons . ) Although imperfect , the significance of real motifs tends to be underestimated by this method . To roughly assess the sensitivity with which the method discovers true ncRNAs , we looked at its recovery of known Rfam ( version 7 . 0 ) families . We masked matches to Rfam's tRNA and rRNA models , since otherwise these widespread , strong motifs might hide nearby , weaker , but still interesting ncRNA structures . Other Rfam families were not masked and serve as a positive control for our methods . Table 1 shows the distribution of known Rfam families in our candidate list , together with their ranks after running FootPrinter , CMfinder , and RaveNnA . We used the refined motifs as the final output . According to Rfam , B . subtilis contains members of 21 families , categorized into 13 cis-regulatory families , one intron element , and seven RNA gene families . We masked tRNAs and rRNAs ( four of the seven gene families ) . Of the 17 remaining families , 13 appear within our top 50 candidates: 11 cis-regulatory families present in B . subtilis , together with two of the gene families ( RNaseP_bact_b and SRP_bact ) . The four families not represented are two cis-regulatory elements ( ykkC-yxkD and ydaO-yuaA ) , one RNA gene ( tmRNA ) , and one intron element ( Intron_gpI ) . The exclusion of Intron_gpI is not surprising , as we did not search intragenic regions . The ydaO–yuaA motif escaped detection because it is present in only three of the 68 sequences in its CDD group . The ykkC–yxkD and tmRNA motifs , although not among our top 50 , would still have been ranked high enough to be discovered in a blind test . Note that , although our computational pipeline is oriented toward discovery of cis-regulatory elements , we sometimes find RNA genes such as RNaseP , SRP , and tmRNA because they happen to be conserved in synteny . We also found a partial tRNA motif , not masked since parts of the tRNA lie outside of the collected upstream sequences . We can potentially filter the candidates at each step to scale this pipeline for larger genomes . In particular , we could have applied CMfinder to only the top half of the datasets according to FootPrinter , and performed genome scans on only the top 500 motifs , without missing any real Rfam families as listed in Table 1 . On average , it takes FootPrinter less than 1 min , and CMfinder 10 min to process each dataset , while it takes RaveNnA 4 . 8 h to scan each motif . We could save considerable computation time by running expensive algorithms only on good candidates . As shown in Table 1 , the ranks for most known ncRNAs improve at each successive step of the pipeline , as more supporting evidence is found . Starting from FootPrinter motifs , CMfinder improves the alignment and identifies consensus secondary structure , while genome scans locate many more motif instances , typically providing still better alignments and additional clues to their functions . To measure the quality of our automatically constructed motif models , we compared them with Rfam alignments for the same families . Rfam's covariance models are built from hand-curated “seed” alignments/structure annotations . These in turn are used to build Rfam's “full” alignments by automatically searching RFAMSEQ ( http://www . sanger . ac . uk/Software/Rfam/ftp . shtml ) , a high-quality , nonredundant subset of EMBL ( http://www . ebi . ac . uk/embl ) , and automatically aligning all hits . For the 14 Rfam families in Table 1 for which we found good matching motifs , we selected the top two motifs from each family , and performed full-genome scans on RFAMSEQ , the same sequence database used to construct the Rfam full alignment . To reduce computation time , we did not scan eukaryote genomes , and the Rfam hits from these genomes were excluded from the following analysis . ( This treatment affects only a few eukaryotic Cobalamin and Lysine hits , all believed to be Rfam errors or bacterial contamination in the genome sequences , plus a few THI hits , which are real . ) For each motif , we selected scan hits at an E-value cutoff of 100 , reconstructed the motif alignments using CMfinder , and removed the low-scoring instances ( <20 bits ) . We compared these predicted motifs to corresponding Rfam full alignments , which serve as the gold standard in this test . Table 2 shows the accuracy of our motifs in membership prediction , motif coverage , and secondary structure prediction . Secondary structures were compared at the base-pair level , and only the base pairs with at least one end falling into the overlapped regions are counted . For both predicted motifs and Rfam full alignments , we removed noncanonical base pairs from each sequence . Of the two motifs chosen for each family , we report the one with better results . For membership prediction , we achieved an average of 84% sensitivity and 91% specificity . The overlapped regions between predicted motif members and corresponding Rfam members account for 81% of the length of the predicted members , and 82% of the length of Rfam members . In the overlapped regions , the secondary structure prediction has 75% sensitivity and 77% specificity . These results suggest our predicted motif models are very accurate compared with Rfam models , which are learned from the hand-curated seed alignments . For many riboswitch families , the main differences between our motif models and Rfam models are located in boundary regions . Our predicted motifs tend to include the transcription terminator ( if present ) , which is a stable hairpin followed by a stretch of U's ( e . g . , Lysine , S_box , T-box ) . Although transcription terminators are functionally important , the Rfam riboswitch models do not include them . On the other hand , CMfinder tends to miss the closing helix of large multiloop structures ( e . g . , Cobalamin , ykoK ) . Most other differences are local perturbations such as small shifts or extra base pairs . As shown in Table 2 , we achieved more than 80% membership sensitivity for all families except yybP–ykoY , Glycine , and Cobalamin . The predicted yybP–ykoY motif differs from Rfam's motif mainly at the multiloop closing helix . Cobalamin and Glycine are two riboswitches with poor sequence conservation ( 46% and 51% average sequence identity , respectively ) . While our motifs from the initial full-genome scan may be too specific , sensitivity increases significantly with only a small loss in specificity after another iteration of RaveNnA scan and refinement ( unpublished data ) . For ykkC–yxkD and T-box , we predicted more members than Rfam . The predicted ykkC–ykxD motif includes the transcription terminator , which caused false positives in our full-genome scans . These false positives , however , all have much less significant E-values than the true positives , and hence are relatively easy to eliminate by inspection . In contrast , for T-box we believe most “false positives” ( with respect to Rfam 7 . 0 ) are actually real . Out of 291 members not included in the Rfam full alignment , 127 are upstream of and on the same strand as aminoacyl-tRNA synthetase genes , where most T-box leaders are found , and the others are largely in poorly annotated regions . We examined the best-scoring motif ( see RNA motif discovery in Materials and Methods and the online supplement at http://bio . cs . washington . edu/supplements/yzizhen/pipeline for details of the motif-scoring function ) in each of the top 200 motif clusters . Of these 200 motifs , 116 were deemed unlikely to represent novel ncRNAs: they have covariance model scores less than 40 bits , single hairpin structures , and most were shorter than 30 nucleotides . ( Many of these 116 are nevertheless biologically relevant . Many correspond to transcription terminators of upstream genes , and others contain known inverted repeat motifs targeted by DNA binding proteins . ) Of 84 remaining motifs , 20 correspond to Rfam families , and 11 to hypothetical transposons . The remaining 53 are candidates for novel ncRNAs . Literature review suggests that many of these candidates are functional . We manually removed the redundant candidates with the same functional roles ( for details , see Manual inspection and ribosomal protein leader analysis in Materials and Methods ) , and present the rest in Table 3 .
In this study , we have presented a method for automatically finding cis-regulatory RNA motifs in prokaryotes . In a careful test with available sequenced Firmicutes , the method exhibited excellent rejection of negative controls ( randomly permuted alignments ) and excellent recovery of known , experimentally validated ncRNAs , including most riboswitches known in this bacterial group , as well as RNA elements such as 6S that have only recently been recognized there . Careful inspection and refinement of several novel motifs in ribosomal protein leaders provides compelling evidence that they are indeed conserved structures involved in regulation of these important operons . In addition , our computational pipeline found dozens of other good RNA motifs that constitute strong candidates for novel functional elements , consistent with the increasing appreciation of the importance of RNA in all living organisms . Finally , our method is sufficiently scalable to be applied to all sequenced prokaryotes . We are in the process of doing so , and preliminary results include several novel riboswitch candidates . We attribute the power of this pipeline to two key characteristics—a relaxation of the constraints on sequence conservation imposed by most previous methods , and integration of motif inference with genome-scale search . Our method performs motif inference on regions that are not defined by sequence conservation: we search unaligned sequences upstream of homologous genes , instead of multiple-sequence alignments constructed by sequence comparison tools . In addition , both the RNA motif–finding algorithm CMfinder and the RNA homology search algorithms RaveNnA/Infernal exploit structural information . Sequence conservation can be used as well , but is not required . Finally , automatic refinement of motifs to incorporate genome-scale search results has proven to be a powerful component of the pipeline ( as in other contexts , such as PSI-BLAST [37] ) . The integration of these tools enables us to discover RNA motifs with low sequence conservation , and to expand the motif family with remote homologs . For example , the predicted motif for the Glycine Riboswitch has only 35% average pairwise sequence similarity . Remote RNA homologs with appropriate gene context are particularly important , as they are the strongest evidence , short of experiments , that a motif is functional , as well as providing clues to that function . Future work will seek to strengthen this pipeline by improved exploitation of phylogeny and by an improved scoring system . Phylogeny is crucial in all comparative genome analysis , without which the concept of conservation is meaningless . It is important in our work because the sequences upon which motif inference is performed are not evolutionarily equidistant , and the significance of conserved nucleotides and compensatory mutations are distance-dependent . Building on the classic phylogenetic likelihood model of Felsenstein [38] , Pfold [39] and Evofold [12] use an RNA-oriented phylogenetic model to select from a given multiple-sequence alignment the regions that fit the structural model best . Unfortunately , in our application , neither an alignment nor an evolutionary tree is initially available , and , for our application , use of the corresponding species tree is inadequate in the common case when there are multiple sequences per species . Incorporating phylogeny into motif search is another challenge . We would also like to improve our scoring scheme . As predicted motifs are subject to expensive manual evaluation and experiments , automatic candidate evaluation to guide resource investment is critical . Our current composite scoring system attempts to discriminate among potential RNA motifs by considering a set of features , including species distributions , structure stabilities , motif sizes , and local sequence conservation patterns . While we can easily recognize motifs that are significant in all these aspects , it is more difficult to order those that are only good by some , but not all , criteria . We have tried to combine the features automatically using machine-learning algorithms such as support vector and logistic regression . However , due to the heterogeneity of the features and limitations of available training data , the results were not as good as our handcrafted composite scoring function . One particular issue is that many of our top-scoring motifs are short single hairpins . They score well because they are widespread , structurally stable , and contain limited but clear sequence conservation . Although short motifs can be functionally important , many do not contain sufficient signal for genome scale homology scans , resulting in false positives that degrade the motif . Other complications include transposons , transcription terminators , DNA–protein binding sites , RNA-polymerase and RNA-ribosome binding sites , etc . The key challenge here is to design a metric that is correctly normalized across various known features and various types of ncRNAs with different sizes , structures , and phylogenetic divergence . These opportunities for improvement notwithstanding , the approach described in this study has proven itself to be highly effective in discovering noncoding RNA elements in prokaryotes , and promises more discoveries to come .
We obtained genome sequences from 67 fully sequenced Firmicute species from the NCBI microbial database ( RefSeq [40] release 14 , 20 November 2005 ) . We first collected amino acid sequences from all annotated protein-coding genes in these species , and categorized them based on NCBI's CDD ( version 2 . 05 ) [16] . The CDD domain models are curated from various resources , including Pfam , SMART , and COG . In the NCBI microbial database , 92% of all functionally annotated proteins ( i . e . , with nonhypothetical description field ) are assigned to at least one CDD group , as are 32% of “hypothetical” proteins . By definition , all members of a CDD group contain a conserved domain in their protein sequences . A group typically includes both orthologs and paralogs . We assigned proteins to a CDD group using “rpsblast” from the NCBI BLAST package ( http://www . ncbi . nlm . nih . gov/BLAST ) , with an E-value cutoff threshold of 0 . 01 . To reduce redundancy , we removed near-duplicate genomes from analysis . To do this , we created a vector for each complete genome , whose ith component was the number of predicted occurrences of the ith conserved domain in that genome . We normalized these vectors to have unit ( Euclidean ) length , and measured their similarity in terms of the projection of one CDD vector onto another ( i . e . , the dot product between them ) . Beginning with records assigned the lowest accession numbers , we then assembled a set of genomes by accepting each subsequent genome only when its similarity index with all selected datasets was less than 0 . 95 . After removing redundancy in this way , 44 complete genomes remained for processing in subsequent steps . We removed CDD groups that contained too few members ( four or less ) , since motif discovery is unreliable on such small groups . We also removed 145 groups with too many members ( 70 or more ) , since motif discovery is expensive on such large groups . For each gene in a CDD group , we collected a few hundred nucleotides upstream of its start codon , which typically includes both 5′ UTR and promoter sequences . The prevalence of operons in prokaryotic genomes complicates the extraction of the regulatory regions , as the desired regulatory region may be upstream of the entire operon rather than immediately upstream of the selected gene . To handle this complication in a conservative manner , we extracted the noncoding sequences upstream of the gene and upstream of its plausible operon using MicroFootPrinter [41] . Specifically , if the next coding region upstream is in the same orientation and fewer than 100 nucleotides upstream , this short intergenic sequence is included in our sequence dataset , and the same procedure is applied to the upstream gene . This process continues until interrupted either by a coding region in the opposite orientation or an intergenic region longer than 100 nucleotides . Finally , up to 600 nucleotides of the last intergenic region are included in the sequence dataset . After collecting the upstream sequences , we removed redundant sequences ( 95% sequence identity across 80% of the sequence according to BLAST ) , and masked regions that match tRNA or rRNA models in the Rfam database . FootPrinter [17] identifies conserved sequence motifs in a set of unaligned homologous sequences using phylogenetic analysis . We scored each FootPrinter motif by the number of motif instances minus the corresponding parsimony score , and scored each dataset as the sum of its top 30 motif scores . The resulting scores are used to rank all datasets . This ranking is performed by MicroFootPrinter [41] , a front end to FootPrinter [17] . We used CMfinder version 0 . 2 [14] for RNA motif prediction in unaligned sequences . For each dataset , we produced up to five single stem-loop motifs , five double stem-loop motifs , and used CMfinder heuristics to combine the motifs into more complicated structures if possible . At various subsequent points , we ranked all CMfinder motifs using a heuristic scoring function that favors motifs with instances in diverged species , stable secondary structure , and local sequence conservation . We used local sequence conservation to discriminate trustworthy alignments with reliable anchors from purely structural motifs ( e . g . , alignments of single hairpins ) that could easily arise by chance , while penalizing global sequence conservation , as highly similar sequences are more likely to be conserved by selection pressure on primary sequence than on structure . We refer to these scores as composite scores . The details of the scoring function are described in the online supplement at http://bio . cs . washington . edu/supplements/yzizhen/pipeline . Next , we filtered the motif set to remove poor motifs and combine redundant ones . Operationally , a “motif” is a covariance model ( CM ) , and a “motif instance” is a sequence that matches the CM with a score above a specified threshold . For each motif , we removed instances with CM score less than ten bits , and removed all but one copy of completely identical instances . Then , we ranked the motifs by composite scores , as outlined above and detailed in the online supplement at http://bio . cs . washington . edu/supplements/yzizhen/pipeline . We further removed motifs with at most four instances and pairwise similarity greater than 0 . 95 , and motifs with composite scores below 50 . Afterwards , we selected up to four motifs for each dataset , selected in decreasing score order so that the lower ranking motifs do not overlap significantly with any higher ranking selected motif . By our definition , motif A overlapped significantly with another motif B if the number of nonoverlapping instances of A was less than 30% of the number of overlapping instances , and the average length of the nonoverlapping regions in the overlapped instances of A was less than half of the average length of the overlapped regions . Next , we removed redundant motifs from different datasets . We called motif A redundant with motif B if A overlapped significantly with B and the number of its predicted bases pairs not in B was less than 30% of the number of its base pairs in B . If A and B are redundant with each other , we chose the higher-ranking motif . Finally , we clustered overlapping motifs as follows . We identified the overlap between motifs according to the genomic coordinates of their instances . One motif was grouped with another if at least half of its instances overlapped , and the overlapped regions are longer than half of the motif length . The motifs were clustered progressively , with high-ranking motifs processed first . We ranked clusters based on their highest-scoring motifs . One of the key strengths of our method is its integration of motif discovery with motif search . Motif discovery is focused on groups of orthologs defined by common CDD membership , since such groups seem likely to be enriched for common cis-regulatory elements . However , many cis-regulatory elements such as riboswitches will be found near a variety of operons involved in a coherent pathway , which may not share a common CDD group . Hence , genome-scale search for additional motif instances is an important component of our approach . Additional instances allow us to construct more accurate motif models , as well as giving insight into potential biological roles for the elements . Given RNA motifs produced by CMfinder , we searched for additional instances using Infernal CMs [21] accelerated with the ML-heuristic filter [20] implemented in RaveNnA 0 . 2f . For reasons of speed , two levels of search were used . The initial search database was derived from all 75 finished Firmicute genomes in RefSeq17 ( 30 April 2006 ) [40] , a total of approximately 200 million nucleotides . Based on sequence annotations , we extracted only intergenic regions for searching , but extended each by 50 nucleotides in each direction to account for common errors in protein-coding gene annotations . The resulting database contained approximately 34 million nucleotides . This small database made it feasible to perform searches for all motifs ( averaging 4 . 8 CPU h per motif ) , and reduced false positives when compared with the full-genome database . After motif refinement ( incorporating hits from this “mini” scan ) , we performed “full” scans with selected motifs . Full scans examined the prokaryotic subset of the 8 GB RFAMSEQ dataset ( version 7 . 0 , March 2005 ) , a total of approximately 900 MB . In particular , comparisons to Rfam ( e . g . , Table 2 ) were based on full scans , since Rfam full alignments are also derived from scans of RFAMSEQ . For model refinement , we ran CMfinder on all hits with RaveNnA E-values < 10 . E-values were calculated as in [42] . The necessary extreme value distribution calculations dominate the run times for mini-scans , but not for full scans . The refined motif set is again postprocessed and ranked as described above . To find which of our predicted motifs were already known , we compared them against the Rfam database . Specifically , we BLASTed our motif instances against Rfam full family members ( produced by scanning Rfam covariance models on the RFAMSEQ genomic database; see [15] ) . For BLAST , we used a word size 12 , and selected the hits with length greater than 30 nt , E-value < 10 , and sequence identify exceeding 90% . These permissive BLAST thresholds resulted in a few isolated hits that we believe to be false positives . These motifs match fragments , each of about 30 bases , of the Rfam RNA-OUT , Intron-gpII , QaRNA , and RNaseP_bact_a families . In general , they are too short , weak , and/or isolated to be compelling , in sharp contrast to the matches reported in Table 1 . The genomic contexts of the refined motif instances were drawn using the Bio::Graphics modules of BioPerl [43] . For the ribosomal motifs , CMfinder structural alignments were trimmed to relevant regions and manually revised before conducting standard genome scans against the microbial subset of the RefSeq17 database . Hits with the correct genomic context were aligned according to the starting covariance model and manually revised once more to create final sequence alignments ( available in the online supplement at http://bio . cs . washington . edu/supplements/yzizhen/pipeline ) . The Neural Network Promoter Prediction program [44] ( version 2 . 2 ) was used to predict putative transcription start sites , and programs from the Vienna RNA package [45] were used to examine possible regulatory conformations . Additional datasets and technical details are available at http://bio . cs . washington . edu/supplements/yzizhen/pipeline .
Five of the ribosomal protein leaders discussed in the Results section appear in Rfam release 8 . 0 ( http://www . sanger . ac . uk/Software/Rfam ) , with the following accession numbers: L10 r-protein leader ( RF00557 ) , L13 r-protein leader ( RF00555 ) , L19 r-protein leader ( RF00556 ) , L20 ( IF-3 ) r-protein leader ( RF00558 ) , L21 r-protein leader ( RF00559 ) .
|
For decades , scientists believed that , with a few key exceptions , RNA played a secondary role in the cell . Recent discoveries have sharply revised this simple picture , revealing widespread , diverse , and surprisingly sophisticated roles for RNA . For example , many bacteria use RNA elements called “riboswitches” to switch various gene activities on or off in response to extremely sensitive detection of specific molecules . Discovery of new functional RNA elements remains a very challenging task , both computationally and experimentally . It is computationally difficult largely because of the importance of an RNA molecule's 3-D structure , and the fact that molecules with very different nucleotide sequences can fold into the same shape . In this paper , we propose a computational procedure , based on comparing the genomes of multiple bacteria , for discovery of novel RNAs . Unlike most previous approaches , ours does not require a letter-by-letter alignment of these diverse genomes , making it more applicable to RNA elements whose structure , but not nucleotide sequence , has been preserved through evolution . In an extensive test on the Firmicutes , a bacterial phylum containing well-studied organisms such as Bacillus subtilis and important pathogens such as anthrax , we recover most known noncoding RNA elements , as well as making many novel predictions .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"rna",
"motif",
"prediction",
"noncoding",
"rna",
"rna",
"structure",
"riboswitch",
"computational",
"biology",
"high",
"throughput"
] |
2007
|
A Computational Pipeline for High- Throughput Discovery of cis-Regulatory Noncoding RNA in Prokaryotes
|
Paromomycin-based topical treatments were shown to be effective in curing cutaneous leishmaniasis ( CL ) lesions caused by Leishmania major in Tunisia . Cure rates of an index lesion were approximately 80% . As a follow on , we conducted a similar Phase 3 trial in Panama to demonstrate the efficacy of these treatments against New World species . The primary objective was to determine if a combination topical cream ( paromomycin-gentamicin ) resulted in statistically superior final clinical cure rates of an index lesion compared to a paromomycin alone topical cream for the treatment of CL , primarily caused by Leishmania panamensis . We conducted a randomized , double blind , Phase 3 trial of topical creams for the treatment of CL caused by Leishmania spp . Three hundred ninety nine patients with one to ten CL lesions were treated by topical application once daily for 20 days . The primary efficacy endpoint was percentage of subjects with clinical cure of an index lesion confirmed to contain Leishmania with no relapse . The clinical cure of the index lesion for paromomycin-gentamicin was 79% ( 95% CI; 72 to 84 ) and for paromomycin alone was 78% ( 95% CI; 74 to 87 ) ( p = 0 . 84 ) . The most common adverse events considered related to study cream application were mild to moderate dermatitis , pain , and pruritus . Superiority of paromomycin-gentamicin was not demonstrated . However , the approximately 80% cure rates for both topical creams were similar to those demonstrated in Tunisia and previously reported with parenteral antimonials .
Leishmaniasis , a neglected parasitic infection transmitted by the bite of a female sand fly , is endemic in 98 countries or territories with approximately 0 . 7 to 1 . 2 million cutaneous leishmaniasis ( CL ) cases occurring each year [1] . CL results from parasitisation of skin macrophages by Leishmania ( L ) species and generally presents as a papule that enlarges to a nodule that often ulcerates over 1–3 months [2] . The illness has a variety of skin manifestations including small , dry , crusted lesions; ulcerative lesions that are shallow and circular with well-defined borders and a bed of granulated tissue; and large , deep , mutilating ulcers [3] . There are at least five Leishmania species that cause CL in the Old World and 12 species in the New World [4] . Also , in Panama , leishmaniasis is an important parasitic disease with an average estimated 2 , 200 new cases of CL reported per year , although this number is likely a 4-fold underestimate due to underreporting [1 , 5] . Among the cases reported in Panama from 2005–2009 the majority were diagnosed as L . panamensis . L . panamensis typically causes CL lesions [1 , 6] . However , it does have the potential to progress to mucocutaneous leishmaniasis in approximately 5% of cases [3] . CL can create substantial morbidity due to the continued presence of a skin ulcer and the psychological impact of disfigurement [7] . The first line of treatment for CL in Panama is pentavalent antimony , either meglumine antimoniate or sodium stibogluconate , given parenterally for 20 to 28 days [8] . The cure rates for L . panamensis CL in adults treated with systemic antimony have been reported in the range from 25–93% [9 , 10] . However , these systemic regimens are associated with toxicities that can limit the patient from receiving a full course of treatment [11] . Alternative therapies are needed particularly for patients with mild disease , no mucosal involvement , and who are not immunocompromised , and for patients living in areas with scarce infrastructure ( most CL endemic areas ) where laboratory monitoring and trained health personnel needed for correct management of pentavalent antimony ( SbV ) treatments are limited . Children also represent a large part of the affected population in Panama and in other endemic regions and there is evidence that pediatric patients with CL have a significantly lower response rate to pentavalent antimonials [8 , 12] . In the registry of leishmaniasis cases from the Ministry of Health-Panama in 2014 , 77% of those affected were 19 years of age or younger and 60% were under 10 years of age [8] . Therefore , the availability of a topically applied drug , instead of a parenteral therapy , offers a potentially safer and more easily administered treatment . In the Phase 3 study in Tunisia , 15% paromomycin-0 . 5% gentamicin ( called WR 279 , 396 ) topical cream and 15% paromomycin alone topical cream were equally effective but statistically superior to a vehicle control ( paromomycin-gentamicin , paromomycin alone , and vehicle-control final clinical cure rates of 81% , 82% versus 58% , P<0 . 001 , respectively ) [13] . However , results from a mouse study suggested gentamicin would provide an added benefit in New World Leishmania species [14] . In addition , a Phase 2 study conducted in Panama showed a trend toward superiority of paromomycin-gentamicin over paromomycin alone against L . panamensis [15] . The results of these studies were supportive of testing the superiority of paromomycin-gentamicin over that of paromomycin alone in the New World CL caused by L . panamensis .
The protocol was approved by the Gorgas Institutional Bioethics Committee , the National Committee of Bioethics for Research , Panama and by the Human Research Protections Office , U . S . Army Medical Research and Materiel Command . All patients or their legal representatives provided written informed consent , and minors also provided assent . This study was a pivotal Phase 3 , randomized , double-blind , two-group trial assessing the efficacy and safety of paromomycin-gentamicin and paromomycin alone topical cream in a hydrophilic vehicle ( designed to enhance drug penetration while maintaining high tolerability ) in subjects with CL in Panama . A vehicle-control group was not included as it was considered unethical to withhold treatment based on the standard of care in Panama and the results of the Phase 3 Tunisian study , which showed the statistical superiority of paromomycin-gentamicin and paromomycin alone compared with the vehicle-control [13] . This study was conducted between May 2013 and March 2016 at three sites in Panama: Penonomé , Panama City , and Changuinola . The same investigational products were used in Tunisia and in this study . Paromomycin-gentamicin and paromomycin alone in a hydrophilic vehicle were manufactured by Teva Pharmaceuticals USA , Sellersville , Pennsylvania in accordance with Good Manufacturing Practices . For each patient , all lesions ( i . e . , the index lesion , as defined below , plus non-index lesions ) were treated topically once daily for 20 days by a member of the study staff who documented treatment application . ( For details of the application procedure , see Supporting information , S2 Appendix . ) Study subjects were males or non-pregnant non-lactating females , ages 2 and older , and with 10 or fewer lesions . For each subject , an index lesion was selected with the following characteristics: ulcerative , from 1–5cm in diameter , and confirmed to contain Leishmania parasites via culture or microscopic examination of lesion material . Subjects were otherwise healthy and without clinical evidence of mucosal involvement . Whenever possible , infecting species of Leishmania were determined by polymerase chain reaction ( PCR ) followed by restriction fragment length polymorphism ( RFLP ) using the heat shock protein 70 for discrimination of Leishmania species [16] and isoenzyme analysis [multilocus enzyme electrophoresis ( MLEE ) ][17] . Eligibility criteria and study procedures are described in the Supporting information , S2 Appendix . The original sample size was 300 subjects . During the conduct of this trial , new Leishmania species were identified that were not found in the Phase 2 trial previously performed in Panama . Of 149 subjects randomized to the trial for which speciation data were available , 74% of subjects had L . panamensis and the others were split between L . guyanensis and L . braziliensis . Since it was not clear what impact various species may have had on overall treatment effect , it was felt that a more conservative approach to trial power was needed . The sample size of the study was adjusted to 400 total subjects , adding 50 subjects to each study arm to maintain at least 90% power with a two-sided alpha of 0 . 05 to detect statistically significant superiority of paromomycin-gentamicin over paromomycin alone for L . panamensis patients . The modified intention-to-treat ( mITT ) population ( N = 399 ) and the safety population consisted of all subjects who received any administration of investigational product and was used as the primary analytic population for efficacy and safety analyses . The evaluable population ( N = 387 ) included all subjects who received daily doses of investigational product for at least 18 of the total 20 days and did not have missing lesion measurements at Day 63 and 168 . Final clinical cure rates of the index lesion and all lesions ( proportions ) were compared between the two treatment groups by uncorrected chi-square test using the mITT group . The Kaplan Meier product-limit method was used to determine the median time to initial clinical cure . The time to initial clinical cure curves were compared using the log-rank test . Within subgroup level two treatment groups were compared by uncorrected chi-square test using the mITT group . A Cochran-Mantel-Haenszel was used to test if there were treatment differences across the subgroup levels . A two-sided alpha of 0 . 05 was used to demonstrate statistical significance . No adjustments were made to correct for multiplicity of comparisons of secondary efficacy endpoints . ( The complete Statistical Analysis Plan is provided in Supporting information , S3 Appendix ) .
Of the 399 patients who received treatment , a total of 16 subjects , 9 in the paromomycin-gentamicin group and 7 in the paromomycin alone Group missed at least 1 day of application of investigational product . Two patients missed treatment due to adverse events of mild and transient hypoacusia or vomiting , neither of which were considered to be related to study cream . There was no significant difference in the primary efficacy endpoint , final clinical cure rate of an index lesion , between groups ( 79% vs . 78% of subjects; paromomycin-gentamicin vs . paromomycin alone; p = 0 . 84 , a difference of -0 . 83% ( 95% CI -8 . 93 to 7 . 27 ) ( Table 2 ) . The evaluable population showed similar results ( 81% vs . 80% of subjects; paromomycin-gentamicin vs . paromomycin alone; p = 0 . 94 ) . The typical response of a treated lesion is shown in Fig 2 . Of the 87 subjects in both groups who were final clinical failures of the index lesion , 71 ( 34 in the paromomycin-gentamicin group and 37 in the paromomycin alone group ) had documented clinical failure ( disease persistence , disease worsening , or disease relapse ) , and the other 16 were failures due to withdrawal of consent or lost to follow-up without meeting the protocol definition of failure to cure . The primary reasons for failure in both groups were lack of initial clinical response of disease by Day 100 ( 49 subjects ) or recurrence of disease ( 32 subjects ) . There was no significant difference in the percentage of subjects with all lesions cured between groups in the mITT ( 75% vs . 76%; paromomycin-gentamicin vs . paromomycin alone; p = 0 . 79 , a difference of 1 . 14% ( 95% CI -7 . 28 to 9 . 55 ) nor in the evaluable population ( 77% vs . 79%; paromomycin-gentamicin vs . paromomycin alone; p = 0 . 68 , a difference of 1 . 72% ( 95% CI -6 . 56 to 10 . 00 ) . Although the final clinical cure rate was the same between the two treatment groups , the median time to initial clinical cure of the index lesion was 36 days ( 95% CI 35 to 49 ) for paromomycin-gentamicin and 48 days ( 95% CI 36 to 49 ) for paromomycin alone . However , this difference was not significant ( p = 0 . 22 ) ( Table 2 ) . There were no significant differences in the final clinical cure rate of the index lesion by age group , under 12 years; 12–17 years; and over 17 years ( p = 0 . 92 ) . Of 399 subjects , 398 were typed using PCR/RFLP . Of those , a total of 312 ( 78% ) of subjects were identified as infected with L . panamensis , 78 ( 20% ) with L . guyanensis , and 8 ( 2% ) with L . braziliensis . There was no significance difference in the final clinical cure rate between treatment groups for any of the species identified ( Table 2 ) . All of the AEs were either mild ( 98 . 5% ) or moderate ( 1 . 5% ) in severity and none were severe or life-threatening . Adverse events that occurred with at least 5% incidence in any group are shown in Table 3 . Application site reactions constituted the majority of AEs considered at least possibly related to investigational products . In order of frequency , these were application site dermatitis , pruritus , erythema , pain , and burning sensation . Eleven subjects ( 2 . 8% , 95% CI 1 . 1–4 . 4 ) developed nasal mucosal lesions that were positive for Leishmania by histopathology , culture , or PCR . Four of these cases were in the paromomycin-gentamicin group and 7 were in the paromomycin alone group . Mucosal lesions were mild in all cases , with erythema and superficial ulcerations in most of the patients . No septal perforation or nasal deformity was detected . In 9 of the 11 cases , subjects were treated with meglumine antimoniate and all nasal lesions resolved . The other two subjects were lost to follow up .
Neither the primary nor secondary efficacy endpoints provided evidence for the superiority of paromomycin-gentamicin over paromomycin alone for the treatment of CL in Panama . Rather , the results of this study mirror the results of the Phase 3 study in Tunisia , which demonstrated virtually identical final clinical cure rates for both topical creams . Phase 3 clinical trial results against epidemiologically important Old World and New World species make it clear that the addition of gentamicin to paromomycin topical cream provides no additional clinical benefit [13] . Children had a favorable response to the paromomycin investigational products . The percentage of subjects under 12 years and 12 to 17 years of age who achieved final clinical cure rate of the index lesion was 84% and 82% , respectively . A high cure rate in children with a topical treatment is important because of poor adherence and higher rates of metabolic elimination with parenteral antimonials both of which contribute to lower cure rates [18] . Neither of the two topical creams was associated with any serious or severe systemic toxicity . Specifically , no aminoglycoside-related nephrotoxicity or ototoxicity was observed . Application site reactions associated with the topical therapy and contact dermatitis related to the tape dressing were common . However , no patient had to withdraw from the study because of these local adverse events . These findings were in agreement with those reported in other studies [13] . The significance of mucosal lesions detected in eleven subjects is unclear , but it warrants evaluation of the nasal mucosa in all patients with New World CL caused by the subgenus Viannia , in order to consider whether systemic therapy is appropriate . To date there is no conclusive evidence that systemic treatment of CL prevents the development of mucosal leishmaniasis [19 , 20] . This trial demonstrates that topical therapy with a paramomycin-based cream offers a potential alternative to the current standard of care for the treatment of CL in Panama . A topical therapy offers possible advantages over systemic treatments , such as pentavalent antimonials , and might be an alternative to treat CL in children or in settings where parenteral therapy is not feasible . Topical treatment could also be studied in future trials as part of combination treatment with oral or parenteral agents . A topical treatment for uncomplicated CL is also of great interest in the United States , where current treatment options all have suboptimal risk/benefit profiles for this disease .
|
Leishmaniasis , a neglected parasitic infection transmitted by the bite of a female sand fly , is endemic in 98 countries or territories with approximately 0 . 7 to 1 . 2 million cutaneous leishmaniasis ( CL ) cases occurring each year . In Panama , most of the CL cases are caused by L . panamensis and , the first line of treatment is pentavalent antimony , given parenterally for 20 days . These systemic regimen is associated with toxicities that can limit the patient from receiving a full course of treatment . Alternative therapies are needed particularly for patients with mild disease , no mucosal involvement , no immunosuppression , and for patients living in areas with scarce infrastructure . Therefore , less toxic , non-parenteral new therapies against CL are urgently needed . We conducted a comparative clinical study that evaluated Paromomycin topical creams ( Paromomycin alone versus Paromomycin+Gentamicin ) for the treatment of cutaneous leishmaniasis ( n = 399 ) in three sites of country . Our study demonstrated the efficacy of these preparations against New World leishmanial species ( mostly L . panamensis ) with a cure rate close to 80% . Our trial supports Paromomycin as a viable alternative treatment for CL caused for the New World Leishmania species .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2019
|
Topical paromomycin for New World cutaneous leishmaniasis
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We propose to use bifurcation theory and pattern formation as theoretical probes for various hypotheses about the neural organization of the brain . This allows us to make predictions about the kinds of patterns that should be observed in the activity of real brains through , e . g . , optical imaging , and opens the door to the design of experiments to test these hypotheses . We study the specific problem of visual edges and textures perception and suggest that these features may be represented at the population level in the visual cortex as a specific second-order tensor , the structure tensor , perhaps within a hypercolumn . We then extend the classical ring model to this case and show that its natural framework is the non-Euclidean hyperbolic geometry . This brings in the beautiful structure of its group of isometries and certain of its subgroups which have a direct interpretation in terms of the organization of the neural populations that are assumed to encode the structure tensor . By studying the bifurcations of the solutions of the structure tensor equations , the analog of the classical Wilson and Cowan equations , under the assumption of invariance with respect to the action of these subgroups , we predict the appearance of characteristic patterns . These patterns can be described by what we call hyperbolic or H-planforms that are reminiscent of Euclidean planar waves and of the planforms that were used in previous work to account for some visual hallucinations . If these patterns could be observed through brain imaging techniques they would reveal the built-in or acquired invariance of the neural organization to the action of the corresponding subgroups .
Visual perception , computational or biological , depends upon the extraction from the raw flow of images incoming on the retina of a number of image features such as edges , corners , textures or directions of motion , at a variety of spatio-temporal scales . All these features involve comparing some functions of the incoming intensity values at nearby spatio-temporal locations and this points very strongly to the notion of derivatives . The idea of constructing the image representations from various derivatives of the intensity flow is at the heart of the concept of the primal sketch put forward in the seventies by the late David Marr [1] or the concept of -jets borrowed from mathematics by Jan Koenderink and his colleagues [2] , [3] . A quick look at the computer vision or image processing literatures will convince anyone of the universal use of image derivatives in feature extraction algorithms [4] , [5] , [6] , [7] . There is also strong evidence that the visual system of many species is organized in such a way that quantities related to image derivatives are extracted , and hence represented , by neuronal activity [8] . The notion of derivative is misleading though because it often implies in people's minds the idea of linearity . But of course it does not have to be the case , computer vision algorithms are usually highly nonlinear even if they use derivatives , and nonlinearities are omnipresent in the brain and in the parts of it that are dedicated to visual perception . If we accept these two ideas , 1 ) that image derivatives are represented in the visual pathway and 2 ) in a nonlinear fashion , this immediately raises the related questions of the coordinate system ( s ) in which they are represented and the effect of changing such coordinate system ( s ) . Changes of coordinate systems are described by group actions such as those of the familiar groups of translations and rotations in the Euclidean plane . This leads naturally to the idea of group invariance: one can argue that the image features representations should be somewhat robust to these groups actions . This is of course only a hypothesis albeit a likely one , we think . In computer vision this idea is not new and there was a time when a significant part of this community was actively designing feature representations that were invariant with respect to a variety of group actions [9] . What is interesting in the case of biological vision is that this hypothesis has consequences that may be testable experimentally: If the visual pathway is organized so as to support invariance of feature representations at the mesoscopic level , say the hypercolumn in V1 , we may be able to predict the appearance of certain patterns of activity in the involved neuronal populations that are a direct consequence of the invariance hypothesis . In this article we begin the development of a mathematical theory of the processing of image edges and textures in the hypercolumns of area V1 that is based on a nonlinear representation of the image first order derivatives called the structure tensor . Assuming that this tensor is represented by neuronal populations in the hypercolumns of V1 that interact in a way that can be described by equations similar to those proposed by Wilson and Cowan [10] , bifurcation theory allows us to predict the formation of specific patterns in the cortical medium that are related to the assumed invariant properties of the underlying cortical representation of the structure tensor .
The structure tensor is a way of representing the edges and texture of a 2D image [11] , [12] . Let be the two-dimensional Gaussian function with 0 mean and variance . We consider the regularized image obtained by convolving the image with , we note , where the symbol represents the convolution operation . The gradient of is a two-dimensional vector which emphasizes image edges: within a flat region , at a pronounced edge , the Euclidean norm of is large , and points in the normal direction of the edge . The parameter is called the local scale . One then forms the symmetric matrix , where indicates the tensor product and indicates the transpose of a vector . By convolving componentwise with a Gaussian we obtain the matrix . It is not hard to verify that this symmetric matrix is positive , i . e . for all vectors in . It is called the structure tensor . When there is no ambiguity we will use instead of . Note that the construction of the structure tensor involves two spatial scales . The first one , defined by , is the one at which the image derivatives are estimated . The structure tensor is insensitive to noise and irrelevant details at scales smaller than . The second one , defined by , is the one at which the averages of the estimates of the image derivatives are computed , it is the integration scale , and is related to the characteristic size of the texture to be represented , and to the size of the receptive fields of the neurons that may represent the structure tensor . Being symmetric and positive , has two orthonormal eigenvectors and and two positive corresponding eigenvalues and which we can always assume to be such that . The distribution of these eigenvalues in the plane reflects the local organization of the image intensity variations . Indeed , one can establish a correspondence between local intensity patterns and relative values of and . For example constant areas are characterized by , straight edges give , their orientation being that of , corners yield . The difference becomes large for anisotropic textures . These simple examples are intended to show the richness of the structure tensor when it comes to representing textures and edges at a given spatial scale , . This representation of the local image orientations and textures is richer than , and contains , the local image orientations model which is conceptually equivalent to the direction of the local image intensity gradient . The local image orientation is a one-dimensional representation which can be obtained from the local image intensity gradient , which is two-dimensional , as the ratio of the gradient components . The structure tensor itself is three-dimensional . Its three dimensions can be either pictured as its three entries or as the collection of its two eigenvalues and the direction of one of its eigenvectors , e . g . the one corresponding to the largest eigenvalue . In particular , it should be clear from the above that the structure tensor can discriminate local intensity patterns that would be otherwise confused by the local orientations model: For example , given an isotropic structure localized in an image neighbourhood of size of the order of the integration scale with no preferred direction of gradient , the local gradients average out resulting in a zero magnitude . An example of such an isotropic structure is a black disk of diameter on a white background . There is clearly gradient information; however , since there is no preferred phase , it zeros itself out as in the case of a uniformly grey pattern . The eigenvalues of the structure tensor turn out to be both equal to some strictly positive number in the case of the disk and both equal to 0 in the case of the uniformly grey pattern . This is an extreme example but one may also think of a texture pattern made of short line elements pointing in roughly the same direction . The local gradients average to a direction roughly perpendicular to the average direction of the line elements . The length of the resulting vector is an indication of the average contrats across these line elements . In the case of the structure tensor , the unit eigenvector , together with its corresponding largest eigenvalue , contains the same information but the second eigenvalue contains information about the spread in the directions of the line elements , the difference between the two eigenvalues being , as mentioned above , an indication of the anisotropy of the texture . This discussion should have made it clear that the structure tensor contains , at a given scale , more information than the local image intensity gradient at the same scale . The question of whether some populations of neurons in such a visual area as V1 , can represent the structure tensor cannot be answered at this point in a definite manner but we hope that the predictions of the theory we are about to develop will help deciding on this issue . We can nonetheless argue as follows . We know that orientation hypercolumns in V1 represent local edge orientations in receptive fields whose size vary between 0 . 5 and 2 degrees . This corresponds to values of between 0 . 5 and 2 centimeters at a viewing distance of 57 centimeters . For a given orientation , the two orientations and are also represented in the orientation hypercolumn and this is very much the same as representing the three components of the stucture tensor at this scale . Indeed , let us denote by the component of the smooth gradient in the directions . It is easy to show that and it follows that the product is a linear combination of , , and . This remains true of the local averages of these quantities obtained by convolution with the Gaussian of standard deviation . We note that these three components are represented in the Euclidean coordinate system defined by the orientation and the orthogonal direction . So we may say that the joint activity of the populations of neurons in the hypercolumn representing these three orientations is in effect an encoding of the structure tensor . This reasoning applies to any orientation and it follows that the joint activity of all triplets of populations of neurons in the hypercolumn that encode the triplets of orientations for all possible values of between 0 and are a representation of the structure tensor that is roughly invariant to the choice of the orientation of the coordinate system in which it is represented or more accurately that contains all such representations which differ by a rotation of the coordinate system , up to the accuracy of the orientation representation in the orientation hypercolumn . Where in V1 could one find populations of neurons that encode the structure tensor ? Cytochrome oxydase ( CO ) blobs and their neighbourhoods seem to be good candidates since their distribution appears to be correlated with a number of periodically repeating feature maps in which local populations of neurons respond preferentially to stimuli with particular properties such as orientation , spatial frequency , brightness and contrast [13] , [14] , [15] , [16] , [17] , [18] , [19] . It has thus been suggested that the CO blobs could be the sites of functionally and anatomically distinct channels of visual processing [20] , [21] , [22] , [23] . Recently Bressloff and Cowan [24] , [25] introduced a model of a hypercolumn in V1 consisting of orientation and spatial frequency preferences organized around a pair of pinwheels . One pinwheel is centered at a CO blob and encodes coarse to medium coarse scales , the other is centered at a region that encodes medium coarse to fine scales . Despite the fact that these authors do not consider the encoding of brightness and contrast , it has been suggested by other authors [26] that this might also be the case . Such a hypercolumn is therefore a good candidate for representing the structure tensor at several scales as well as , as these authors claim , the local orientations at various spatial frequencies . As a consequence of this discussion we assume that the structure tensor is represented by the activity of the populations of neurons in a hypercolumn , where the word represented is to be understood as explained above . Let therefore be a structure tensor . We assume that there is some quantity which we associate to an average membrane potential , noted , and is a function of and the time abd which is , e . g . , high if reflects the actual intensity values in the column receptive fields and low otherwise . We assume that its time evolution is governed by an equation of the Wilson and Cowan [10] or Amari [27] type . ( 1 ) where the integral is taken over , the set of possible structure tensor . We provide below a precise mathematical definition of this set . is the corresponding area element , also defined below , and is an input current . The positive coefficient can be normalized to 1 by a suitable choice of time scale . is a sigmoidal function which after normalization may be expressed as: ( 2 ) where is a positive coefficient which governs the stiffness of the sigmoid . The function . called the connectivity function , is defined as follows . If we assume further that the neuronal population representing the value of the structure tensor excites ( respectively inhibits ) the neuronal population representing the value if the distance is small ( respectively large ) , a natural form of the connectivity function is obtained from the following function , a difference between two pseudo-Gaussians: ( 3 ) where , , and is a monotonously increasing function from the set of positive real numbers to . For example , if we obtain the usual difference of Gaussians . One then defines is clearly invariant to the action of the isometries of :We will see that with such a choice of connectivity function , the integral in ( 1 ) is well-defined because is small at “infinity” . This is similar in spirit to the ring model described in [28] , [29] , see the Discussion Section . There are of course many loosely defined terms in the presentation so far , including the definition of the set of structure tensors , of the distance between two such tensors that plays a central role in the construction of the connectivity function , and the definition of the isometries of the set of structure tensors , i . e . the transformations that leave the distance between two tensors unchanged . We provide below precise answers to all these questions . Before doing this we explain how equation ( 1 ) which describes the dynamics of a neural mass , e . g . a hypercolumn of V1 , can be “spatialized” in order to provide a neural or cortical field model ( see [30] , [29] for reviews of neural fields ) that could describe the spatio-temporal activity of V1 related to the representation of edges and textures . Indeed let us assume the existence a continuous distribution of such columnar systems in a regular bounded open set of , modeling a piece of a flat cortex . We note the spatial variable . Equation ( 1 ) can be generalized to the following ( 4 ) where is the usual Euclidean area element . The average membrane potential depends on the position in the continuum , i . e . on the position of the hypercolumn in V1 , on the time and on the possible local values of the structure tensor . The connectivity function is now a function of the structure tensors at point of the continuum and at point . We do not deal any further with this equation , leaving it for future work , but see the Discussion section . Considering equation ( 1 ) we will study how its solutions change when the slope parameter increases from the value 0 . This study , together with the formulation of hypotheses about the invariance of the average membrane potential with respect to the action of some subgroups of the group of isometries of the set of structure tensors , predicts , through bifurcations of the solutions to ( 1 ) , the appearance of certain patterns displaying the kind of symmetries described by these subgroups . If such patterns can indeed be observed by actual measurements , e . g . , optical imaging [31] , then this would be a strong indication that the neural “hardware” is built in such a way that its state is insensitive to the action of these subgroups . To say things differently , bifurcation theory and pattern formation could potentially become theoretical probes for the validity of various hypotheses about the neural organization of the brain , allowing to make predictions about the kinds of patterns that should be observed in the activity of real brains , and opening the door to the design of experiments to test these hypotheses . This is indeed an exciting perspective . We now proceed to flesh up the theory . We present some important properties of the set of structure tensors . These properties are somewhat scattered in the literature and are relevant to our forthcoming discussion of pattern formation in cortical tissues . The key observation is that the structure tensors naturally live in a hyperbolic space of dimension 3 that can be peeled , like an onion , into sheets of dimension 2 , each sheet corresponding to a constant value of the determinant of the elements inhabiting it . We are therefore led to study hyperbolic spaces of dimension 2 which turn out to enjoy a very simple representation in the open unit disk of the complex plane , the so-called Poincaré disk , with its fascinating non-Euclidean geometry that arises from the Riemannian structure of the set of structure tensors . This geometry has been studied in depth by mathematicians and theoretical physicists and is still a very active research area with many open difficult questions . We then establish the dictionary that will allow us to translate statements about the structure tensors of determinant equal to one into statements about complex numbers of magnitude less than or equal to 1 . The fundamental new item in this section is the group of isometries of the Poincaré disk , analog to the group of rigid displacements in the Euclidean plane , whose action on complex numbers can be translated ( the technical word is lifted ) into meaningful actions on structure tensors . We explain in Text S1 how to put things back together , that is to say , how to reconstruct in a mathematically coherent fashion the onion representing the whole set of structure tensors from the description of one of its sheets , or peels , i . e . the one corresponding to the unit determinant structure tensors . The final touch is a somehow deeper analysis of some subgroups of the group of isometries of introduced previously . These subgroups arise naturally when one examines the kinds of invariances that the cortical representations of the structure tensors should enjoy . The mathematical structure that emerges in this context is that of a Fuchsian group , introduced by Henri Poincaré in 1882 [32] . Consider the set of symmetric positive-definite matrices ( see glossary in table 1 ) . Indeed , let ( 5 ) be an element of . We refer to ( respectively , ) as the -coordinate ( respectively the - -coordinate ) of . If we scale by , is also an element of . Hence is a positive cone . It is open because it is defined by two strict inequalities . It is also a three-dimensional Riemannian manifold in which the distance is defined as follows [33] . Given and in , the Riemannian distance can be expressed as the Frobenius norm ( the Frobenius norm of a real matrix is the square root of the sum of the squares of its elements ) of the principal logarithm of : ( 6 ) where the s are the eigenvalues of the matrix . This expression is symmetric with respect to and since and the s are positive since is conjugate to the symmetric positive definite matrix . This definition of the distance between two tensors can be motivated from a biological viewpoint . A tensor is a symmetric matrix , hence it can be thought of a a three-dimensional vector . The “natural” distance between two such vectors ( representing the tensors and ) is the usual Euclidean distance . This distance has the following problem . A tensor defines a quadratic form . If we change the coordinate system in which we express the coordinates of two tensors and they become and , where is the matrix defining the change of coordinate system . It can be verified that this transformation does not leave in general the Euclidean distance invariant whereas it does leave invariant . This invariance is a very desirable feature since the measure of similarity between two tensors ( their distance ) should not depend on the particular coordinate system used to evaluate their components . Hence it is very likely that evolution would rather select than the simpler but sometimes misleading Euclidean distance . From yet another perspective it can be shown , see e . g . [34 , Volume 1 , Chapter X , Theorem 9] , that there exists a change of coordinates , i . e . , a matrix such that in the new coordinate system and . In other words , the distance ( 6 ) , is a measure of how well and can be simultaneously reduced to the identity matrix by a change of coordinate system . This change of coordinate system is not in general a pure rotation but a combination of a pure rotation and a scaling of the coordinates . If we picture the structure tensor as the elliptic blob defined by the equation , , the two tensors and are represented by two elliptic blobs as shown in the lefthand part of figure 1 . After the coordinate transform defined by , is represented by a unit disk and by an elliptic blob whose major axes are the eigenvalues and that appear in ( 6 ) , as shown in the righthand part of the same figure . There is a unique geodesics ( curve of shortest length ) between two elements of . Its expression is given in Text S3 . If we now consider the two-dimensional submanifold of the special positive definite matrixes whose determinant is equal to 1 , it is clear that . We detail this point in Text S1 . It can be shown that equiped with the Riemannian metric induced by that of is a Riemannian surface with constant sectional curvature equal to −1 , see Text S1 for details . This indicates that it is isomorphic to the two-dimensional hyperbolic space , noted , for which we now provide three different models . There are three main models of , the two-dimensional hyperbolic space . Each model has its advantages and disadvantages . We first present the hyperboloid model which is the most natural for the set of structure tensors , next the Poincaré disk model which is the most convenient for carrying out analytic computations . We relegate in Text S2 the third model , called the Poincaré half-plane model and noted , which is not as convenient as the second for visualizing important geometric transformations such as rotations . The hyperboloid model is defined as the hyperboloid sheet in of equationassociated to the quadratic form which yields by polarization the bilinear form . The corresponding Riemannian distance is given byGeodesics are the curves intersections of the hyperboloid sheet with planes through the origin . The Poincaré disk model is conveniently obtained by stereographic projection on the plane of equation through the point of coordinates of the hyperboloid model . This establishes a one to one mapping of the hyperboloid sheet onto the open unit disk . Given two points and of corresponding to the points and of the hyperboloid , the corresponding Riemannian distance is given by ( 7 ) and satisfies . We may also write ( 8 ) Geodesics in are either diameters of the unit circle or circular arcs orthogonal to it . The surface element in is given byIn the rest of the paper we use the Poincaré disk model . This is a subjective choice essentially driven by the fact that this model exhibits in an obvious manner the rotational symmetry of the hyperbolic plane . We now detail the relationships between SSDP ( 2 ) and its representation in the Poincaré unit disk . We also describe how the action of the direct isometries of on this representation lifts to SSDP ( 2 ) . This is important since it allows us to give an interpretation in terms of image-based operations , hence biological and computational , of the action of an isometry in . This will turn out to be most important in the sequel . A unit determinant structure tensor is a symmetric positive definite matrix defined by ( 5 ) and satisfying . This implies because . The linear change of variables ( 9 ) establishes a one to one mapping from the set of structure tensors to the hyperboloid model of from which we deduce the correspondences with the Poincaré disk . The corresponding point in is represented by the complex number ( 10 ) satisfiesWe note the trace of . This shows that the border of , the unit circle , corresponds to the tensors such that . Conversely , given a complex number representing a point of , the corresponding tensor coordinates are given by ( 11 ) Note that equation ( 10 ) is the “Tensor to dictionary” that allows us to translate statements about structure tensors to statements about points in the unit disk and equations ( 11 ) are the “ to Tensor” dictionary . Also note that we havefor all pairs of unit determinant structure tensors represented by in the hyperboloid model , in the Poincaré disc model , and in the Poincaré half-plane model ( see Text S2 ) . In particular , the distance ( 6 ) defined between two structure tensors is equal to the Hyperbolic distance between their representations in the Poincaré half-plane or unit disk . We now describe the isometries of , i . e . the transformations that preserve the distance . Here again we recall some basic facts , now focusing on the hyperbolic geometry of the Poincaré disc . We refer to classical textbooks in hyperbolic geometry for details , e . g . , [35] . The direct isometries ( preserving the orientation ) in are the elements of the special unitary group , noted , of Hermitian matrices with determinant equal to 1 . Givenan element of , where indicates the complex conjugate of the complex number , the corresponding isometry in is defined by ( 12 ) Orientation reversing isometries of are obtained by composing any transformation ( 12 ) ) with the reflection . The full symmetry group of the Poincaré disc is therefore ( see table 1 ) The action of the group on the Poincaré disc , is equivalent to the conjugation on the set of structure tensors . We call it the lifted action of to the set of structure tensors . Indeed , letbe an element of , whose action on is given by ( 12 ) , then it can be shown by an easy computation that the lifted action on the corresponding structure tensor is ( 13 ) where ( 14 ) Equation ( 13 ) is important . It shows that the “lifted” action on a given structure tensor of an isometry of is simply a change of coordinates in the image plane , where the relation between and is given by equation ( 14 ) . We show below that these changes of coordinate systems have very simple interpretations for many of the subgroups that generate . Because isometries are conformal maps , they preserve angles . However they do not transform straight lines into straight lines . Given two points in , there is a unique geodesic passing through them: the portion in of the circle containing and and intersecting the unit circle at right angles . This circle degenerates to a straight line when the two points lie on the same diameter . Any geodesic uniquely defines the reflection through it . Reflections are orientation reversing , one representative is the complex conjugation ( reflection through the geodesic ) : . Let us now describe the different kinds of direct ( orientation preserving ) isometries acting in . Thanks to ( 13 ) , they induce some interesting lifted actions on the set of structure tensors that we also describe . We first define the following one-parameter subgroups of :
We therefore consider equation ( 16 ) . The next step in the analysis of the bifurcations of its solutions is to look at the linearized equation and determine the critical values of the slope at which the trivial solution is destabilized under the influence of some biologically admissible ( hence bounded ) perturbations . For this we would like to proceed as in the Euclidean case , that is , by looking for perturbations in the form of elementary plane waves , the superposition of which defines a periodic pattern in the space ( or in the Euclidean case ) . Let us first recall the Euclidean setting . In this case plane waves are called planforms and have the general form where is any vector in ( the “wave vector” ) . Each planform is an eigenfunction of the Laplace operator corresponding to a real eigenvalue ( is the Euclidean norm of the vector ) :The fact that the eigenvalue does not depend upon the direction of the wave vector reflect the rotational invariance of the Laplace operator . Moreover , a given planform is clearly invariant under translations in by any vector satisfying the condition where ( it clearly does not depend upon the coordinate along the axis orthogonal to ) . It is an elementary but fundamental fact of Euclidean geometry that given any two vectors , of equal length , we can define the periodic lattice spanned in the plane by and such that , and that any smooth function in the plane which is invariant under translations in can be expanded in a Fourier series of planewaves , . Therefore in a suitable space of lattice periodic functions the spectrum of the Laplace operator is discrete with real eigenvalues of finite multiplicities , the corresponding eigenfunctions being planforms , and we can proceed to classical bifurcation analysis if the equations do not have additional degeneracies or singularities ( this was the approach of [44] for the analysis of visual hallucinations formation in the cortex ) . Our aim is to apply similar ideas to the case when the problem is defined in the Poincaré disc instead of the Euclidean plane . A first remark is that we cannot define a periodic lattice in by just assigning two basic wave vectors ( is not a vector space ) . There exist however a large number of periodic lattices in . Those are defined by discrete subgroups of , and there are many such groups ( called Fuchsian groups , see above ) . We may therefore consider functions which are invariant under the action of a Fuchsian group . Thanks to their invariance under the action of we know that our equations can be restricted to such functions . Moreover , if the fundamental domain of a Fuchsian group is compact ( see above ) , it is known that the Laplace-Beltrami operator restricted to this class of functions has a discrete spectrum of real eigenvalues with finite multiplicities . However before we go further in this direction , we first need to analyze the effect of perturbations in the form of elementary waves , the hyperbolic counterpart of planforms . Such hyperbolic plane waves have been introduced by Helgason [45] and are defined as follows: Let be a point on the circle , which we may take equal to by a suitable rotation . For , we define the “inner product” to be the algebraic distance to the origin of the ( unique ) horocycle based at going through . This distance is defined as the hyperbolic ( algebraic ) length of the segment where is the intersection point of the horocycle and the line ( geodesic ) , see figure 4 . Note that does not depend on the position of on the horocycle . In other words , is invariant under the action of the one-parameter group ( see definition above ) . One can check that the functionsare eigenfunctions of the Laplace-Beltrami operator in with eigenvalues . Helgason [45] used these functions to define the Fourier transform in pretty much like the elementary functions , , , are used to define the usual Fourier transform in the plane . We now define the Helgason hyperbolic planforms ( or H-planforms ) as the functions with or , . The first case corresponds to a real eigenvalue of . In the second case , the eigenvalue is complex and equal to . The reasons for introduction of these H-planforms will become clear from the following properties: It is readily seen from the definitions and formula ( 8 ) that . Therefore , in these coordinates , the H-planforms with base point read . In particular if , then is periodic with respect to the coordinate with period . Of course the same property holds at any base point by simply rotating the planform by the angle . The H-planform is said to be periodic in this case . Figure 5 shows the pattern of a periodic H-planform . If , the eigenfunction is not periodic due to the factor in front of . It does however correspond to a physically relevant wavy pattern in the sense that its “energy density” is expressed as and is therefore bounded ( here we applied the expression for the surface element in horocyclic coordinates , see [45] ) . We now proceed with the linear step of our bifurcation analysis . The linearisation of equation ( 16 ) at the trivial solution , with no input and with , reads ( 19 ) where and is the “hyperbolic” measure in defined in equation ( 17 . Since equation ( 16 ) is invariant with respect to the isometries of , we can look for solutions which are invariant under the action of the subgroup . It is then appropriate to express in horocyclic coordinates: , . The hyperbolic surface element in these coordinates is expressed as [45] ( 20 ) The invariance then reads ( 21 ) The integral term in ( 19 ) defines a linear operator , noted , on the set of average membrane potential functions , which can be expressed as follows ( the last identity following from the change of variable and the relation [45] ) :This shows that does not depend on the coordinate ( as expected ) . We have reduced the problem to an integro-differential equation in the single coordinate . Moreover , if we defineand assume that the integral is convergent for ( this is the case with defined by the function in ( 3 ) ) , then equation ( 19 ) leads to the eigenvalue problem ( 22 ) where is a convolution product and we have set . This problem can be solved by applying the Fourier transform in which is defined as ( see [45] ) :for a function such that this integral is well-defined . Thanks to the rotational invariance we can restrict ourselves to the case , which gives , in horocyclic coordinates: ( 23 ) Rotational invariance implies that the same equations would be obtained if an H-planform with another base point were chosen . This can be seen directly on the expression of H-planforms from the relation ( see [45] ) It follows that for a given and eigenvalue , there is in fact a full “circle” of eigenfunctions , . We assume in this section . This means that we are looking for solutions of ( 22 ) of the form , . The H-planforms are not only invariant along horocycles , but also periodic with respect to the coordinate as shown above . If a bifurcation occurs with such a planform , the corresponding solutions of equation ( 16 ) will be -invariant and -periodic . We first look at the critical eigenvalue problem for such H-planforms . Applying the Fourier transform to ( 22 ) leads to the following expression for the eigenvalues: ( 24 ) where is the Fourier transform of . Numerical calculation has been performed to compute in the case when is defined by the “Mexican hat” given in ( 3 ) ) . Note that the function is not even ( hence the operator is not symmetric ) . The following two properties of are therefore not surprising ( they would be false if the system were defined in the Euclidean plane instead of the Poincaré disc , because in this case would be a symmetric operator ) : ( i ) the eigenvalues are complex in general , ( ii ) the graph of shows maxima and minima . Figure 6 below shows the graph obtained with , , , and in equation ( 3 . All eigenvalues come in pairs of complex conjugates and of course . The most unstable eigenvalues are those corresponding to the maximum of , that is , in the case of Figure 6 , with . The critical value of is obtained by setting the real part of equal to 0 . The corresponding critical eigenvalues are with ( with the parameter values of Figure 6 , and ) . When , small fluctuations around the trivial state of equation ( 16 ) are damped , while as crosses the critical value , perturbations with period will grow . In fact a continuum of wave numbers close to may also give rise to unstable modes , however we now restrict our analysis to functions which are -periodic in with period . This allows us to reduce the problem to an equation bearing on functions of the time and the single variable , which are square integrable in the interval of periodicity . It follows that a Hopf bifurcation occurs from the trivial state of equation ( 1 ) at . Applying a procedure which is classical in the Euclidean case [46] , we formulate the problem in operator terms as follows . Let be close to 0 , then ( 25 ) where the operators , and are defined as follows is the function , and stands for the higher order terms in and . These operators are defined in the Hilbert space of square integrable , -periodic functions . and are compact operators in and . The critical eigenvalues of are simple . It follows from general Hopf bifurcation theory [47] that a branch of periodic solutions bifurcates from the trivial state at , i . e at , with a period where is close to , and the leading order of which has the formwhere is an ( arbitrary ) phase . Plugging this into equation ( 25 ) and passing in Fourier space at the value we obtain the bifurcation equationfrom which it follows thatand is readily deduced from this by taking the imaginary part of the bifurcation equation . The branching is therefore supercritical ( for ) and the bifurcated , periodic solutions are stable against perturbative modes which respect the symmetries of the solutions ( “exchange of stability principle” , [48] ) . At this stage however , no general stability statement can be made . One last remark should be made about these periodic solutions . In a suitable space of time-periodic functions ( as chosen to perform the Hopf bifurcation analysis , see [46] ) the invariance under time translations of the problem induces a “temporal” symmetry by the action of the group . This group simply acts by time shifts mod ( the time period of the bifurcated solutions ) . On the other hand , another copy of acts on ( 25 ) by shifts along the coordinate mod ( “spatial” periodicity ) . These two groups act as follows on the leading term of the bifurcated solutions:Therefore this term , which is also the complex eigenmode for the linear part of the equation , is fixed under the action of the one-parameter subgroup of defined by setting . By the general theory of Hopf bifurcations with symmetry [49] ) , this property propagates to the full solutions of ( 25 ) . The interpretation is that , for an observer moving along the coordinate with velocity , the solution looks stationnary . Solutions which have this property are called relative equilibria [50] , [46] , and in the present case they can also be named H-traveling waves . These solutions resemble a train of H-planforms propagating from the “source” at infinity which is the tangency point of the horocycles , see Video S1 . In the previous section we found bifurcated solutions which were periodic along the geodesics emanating from a point at infinity ( i . e . on ) and invariant along the orthogonal direction ( that is , along the horocycles ) . This pattern corresponds to the Euclidean “strip” or “roll” pattern , with the noticeable difference that the latter are usually steady , while in our case they are uniformely traveling from the source at infinity . Is it possible to go further in the analogy with the Euclidean case ? Is it possible to find bifurcating patterns which are invariant with respect to a periodic lattice ( or “tesselation” ) in , in other words patterns which are invariant under the action of a discrete subgroup of with a compact fundamental domain . This would be of physical relevance because it would correspond to bounded states . Moreover periodic tilings with certain types of compact “tiles” related for example to the groups may be specially relevant to our problem as described above . However the occurence of such groups and the requirement of compactness of their fundamental domain obeys very strict rules . In particular , an important difference with the Euclidean tilings is that fundamental polygons for a given group have a fixed area: applying some rescaling to the domain will in general destroy the tiling property . In any case , it results from general spectral theory on the hyperbolic plane that the spectrum of the Laplace-Beltrami operator restricted to -invariant eigenfunctions , with a compact fundamental domain , is discrete and its eigenvalues have finite multiplicity [38] , [37] . Any smooth ( square integrable ) -invariant function ( or “automorphic function” ) in can be expanded in a series of eigenfunctions of . These eigenfunctions can be expressed in terms of H-planforms ( ) as follows:where is a distribution defined on the boundary of the unit disc which in addition satisfies certain equivariance relations with respect to the action of on . Here is an eigenfunction for the eigenvalue , but the values of depend on and there is no known simple or explicit way to compute these values and the corresponding distribution . We can nevertheless determine the threshold at which perturbations along the elementary H-planforms will lead to instability of the trivial state for equation ( 19 ) . The method is completely similar to the one for periodic H-planforms . The eigenvalues are given by equation ( 24 ) . Figure 7 shows an example of the function . As expected it takes only real values corresponding to the fact that the eigenvalues are real in this case . The most unstable eigenvalue corresponds to the maximum of the blue curve , the corresponding abscissa being the “critical” wave number . The critical value of the parameter is then defined by the relation , for which all eigenvalues are negative but one , the critical eigenvalue , which is at 0 . Therefore when crosses this threshold the system undergoes a steady-state bifurcation . The next question is to look for discrete groups such that this critical value also corresponds to invariant eigenfunctions . We have not carried out this program yet . The computation of the eigenvalues and invariant eigenfunctions can only be achieved by numerical approximation . Only a few cases have been investigated in detail , for example the case when is the octagonal Fuchsian group ( see [51] , [36] ) . This group , which we note , is spanned by four “boosts” ( hyperbolic elements of ) with and , . Its fundamental domain is the regular octagon which defines a tesselation of , of which two elements are shown as black continuous lines in Figure 8 . In order to illustrate what an eigenfunction for the regular octagonal group does look like , we have computed one such eigenfunction following the method exposed in [36] . The result is shown in Figure 8 . Note the pattern which consists of pairs of blue and red spots uniformly distributed around the central octagon ( which is materialized by a dark line as well as the image under the generator of this octagon ) . This pattern is reproduced at infinity toward the boundary of the disc ( which , in hyperbolic geometry , is at infinity ) by acting with the elements of . In this figure the resolution becomes rapidly bad when approaching the boundary , but in Figure 9 we show a magnification of the sector in which the transformed octagon under lies . In this figure we can nicely see how the pattern inside the central octagon has been transformed under . If one is interested in the interpretation of these images in terms of structure tensors rather than in terms of points in the Poincaré disk , one can use the “ to Tensor dictionary” defined by equations ( 11 ) . As an example , looking at figure 9 , we see that the centers and of the red and blue blobs in the “main octagon” are symmetric with respect to the horizontal axis and such that and . This corresponds to the two structure tensorswhose distance is equal to 0 . 81 . We should now take into account the symmetry group of the octagon , isomorphic to the dihedral group which contains 16 elements generated by the rotation and by the reflection through an axis of symmetry of the octagon . These transformations are all elements of . The fundamental domain of in the octagon is th piece of the cake . It follows from the calculations of [36] that the eigenvalues of in this fundamental domain ( with suitable boundary conditions ) are simple , therefore the eigenvalues in the octogon with suitable periodic boundary conditions are either simple or double depending on the way in which the rotation acts on these eigenvectors . From the bifurcation point of view , this means that we may look for solutions in which are invariant under the action of and which transform like these eigenvectors under the action of , henceforth reducing the problem to a simple or double eigenvalue problem with symmetry . The theory of symmetry breaking bifurcations ( an integer ) is well established , see [49] . We list below the generic situations which can occur according to the type of action of rotations and reflections in on the eigenvectors at a critical parameter value . We show in table 2 the generic bifurcations of -periodic patterns . We note an eigenvector of the Laplace-Beltrami operator at a critical parameter value . Note that the octagon has two different types of symmetry axes: those joining opposite vertices and those joining the middle of opposite edges . The first case corresponds to points which are fixed under the reflection ( or a conjugate of in ) . The second case corresponds to points which are fixed under the reflection ( or a conjugate of in ) . Note that the periodic pattern illustrated in Figure 8 corresponds to what a bifurcated state would look like in the case of the second line of table 2 . We are however unable at this stage to tell without further and quite involved computations , which type of symmetry breaking will occur as the parameter crosses the stability threshold .
Our investigations are somewhat related to some of the issues raised by Ermentrout [29] . They are also related to the work of Bressloff , Cowan , Golubitsky , Thomas and Wiener [52] , [44] on a model where either the connectivity kernel does not depend at all on the image features or is only sensitive to the ( local ) direction of the lines in it . This has led to beautiful results on the “spontaneous” occurence of hallucinatory patterns under the influence of psychotropic drugs . In further studies , Bressloff and Cowan have attempted to extend the theory to models taking into account not only the directional feature but also the spatial frequency in the images [53] , [54] , [24] . Based on the experimental observation that hypercolumns seem to be organized around “pinwheels” in the visual cortex ( points at which neurons are sensitive to any direction ) , they derived a model where direction and frequency define a point on the unit sphere and the connectivity kernel is invariant under the group of rotations of the sphere . Our approach differs in that we model edges and textures simultaneously at a given scale through the structure tensor . The underlying feature space and its transformations are more complicated than the sphere and its rotation group . We showed that they can be represented by the Poincaré disk and its group of hyperbolic isometries . This naturally leads to a model of visual edges and textures where the equations are invariant by isometries in the ( hyperbolic ) space of structure tensors . Spatial scale can probably be included as well , this is the subject of future work . There are also connections between our work and some previous work by Ben-Shahar , Zucker and colleagues [55] who discuss the representation and processing in V1 of a larger set of visual features including edges , textures , shading , stereo . They do not deal at all with the problems of group invariance and of bifurcations of neural states , most likely because their underlying mathematical machinery , relaxation labelling [56] , [57] , cannot easily address these questions . Ben-Shahar and Zucker pursue these ideas of “good continuation” of the texture flow from a more engineering viewpoint in [58] and in [59] from the viewpoint of differential geometry as beautifully described in the book by Petitot [60] and in some of his earlier papers [61] . It is clear that these complementary approaches should be brought together at some point and unified but this is the subject of future work . The previous analyses and results use the assumption that the average voltage is invariant with respect to the action of the subgroup of . Thanks to this hypothesis we were able to reduce the dimension of the neural mass equation ( 1 ) from 2 to 1 and to use classical Fourier analysis to describe the process of pattern formation and of bifurcation of the solutions . One may argue that the action of the subgroup on the set of structure tensors does not have a natural interpretation , unlike that of and and , for that matter , that of . On the other hand the subgroup features a very simple set of invariant functions , the H-planforms that can be used to represent the solutions of ( 1 ) that are invariant with respect to its action . As far as we know similar functions are not known for the groups whose action on the set of structure tensors does have a nice interpretation . This implies that the putative invariance of the average voltage with respect to this action would be most interesting to test through an analysis of the bifurcations of the solutions of ( 16 ) in the line of what we did for the group but is currently hampered by the lack of good functions for representing these solutions . Another remark is that the “energy density” of these solutions tends exponentially fast to as tends to , due to the term in the expression of the hyperbolic surface element in horocyclic coordinates , see equation ( 20 ) . Such solutions may therefore not be physically admissible . This objection drops out for the H-planforms of the form with , as noted previously . Unfortunately one cannot carry out a simple bifurcation analysis for these H-planforms . On the other hand we have seen above that such H-planforms can be associated , in a non trivial way , to periodic patterns with respect to the action of a discrete subgroup of . This problem needs further investigation . The preliminary discussion about the octagonal group could a priori be transposed to many other kinds of hyperbolic patterns , and we do not know which one would be preferred , if any . These examples are a few among many of an analysis that would have important implications in terms of the actual neural representation of the structure tensor ( and at bottom of the image intensity derivatives ) . For example , given a subgroup of , assume that the mathematical analysis of the bifurcations of the solutions of equation ( 16 ) that are invariant with respect to the action of predicts the formation of certain patterns having the kind of symmetries represented by . If such patterns can indeed be observed by actual measurements , e . g . , optical imaging [31] , then this would be a strong indication that the neural “hardware” is built in such a way that its state is insensitive to the action of . For example , in equation ( 16 ) , the state is the average membrane potential . The observation of the above pattern formation would come in support of the hypothesis that for all elements of the group , for all structure tensors and for all time instants . In other words , bifurcation theory and pattern formation can be considered as theoretical probes of various hypotheses about the neural organization of the brain , allowing to make precise predictions about the kinds of patterns that should be observed in the activity of real brains , and opening the door to the design of experiments to test these hypotheses . Specific examples of such groups are the groups we gave a few examples of and the octagonal group discussed previously . The restriction to the hyperbolic plane instead of the three-dimensional space of structure tensors looks like an oversimplification , which should be only considered a useful first step . Our plan is to extend this analysis to the full tensor space , making use if necessary ( and this will certainly be the case ) of numerical simulations in order to get a better idea of the phenomenology . As mentioned in the Methods Section , it is natural to consider a spatial extension of our analysis that would analyze a spatial distribution of the kind of structure tensor hypercolumns that we have described in this paper , see equation ( 4 ) . This would lead in particular to an analysis of “hyperbolic hallucinatory patterns” that could be compared against those described in the work of Bressloff , Cowan , Golubitsky and collaborators [52] , [44] . This requires first to better understand our a-spatial model and is the subject of some of our future investigations . One may also speculate what such an array of structure tensors would offer compared to an array of orientations . Even if this has not yet been worked out to our knowledge in the context of neural fields , it is likely that an array of orientations can support the perception of extended contours in an otherwise “flat” image , like a cartoon [62] , [63] . This can be achieved by such connectivity functions as those that enforce the Gestalt law of good continuation . As mentioned above some of these ideas can be found in the work of Steve Zucker and his associates . An array of structure tensors would add to this the possibility of perceiving extended texture edges such as those encountered in natural images where sharp variations in the texture are likely to indicate boundaries between objects . This is certainly a very important area of investigation from the psychophysical , neurophysiological and mathematical perpectives . A final remark is that all this analysis assumes a perfectly invariant problem under the group of isometries in the space of structure tensors , a situation which is of course very unlikely , but which has the great advantage to allow for computations and to highlight fundamental properties and features of the problem at hand . A next step would be to look at the “imperfect” case in which symmetries are not perfectly satisfied , but this , even in the simplified context of the Poincaré disc , may be a formidable challenge .
|
Our visual perception of the world is remarkably stable despite the fact that we move our gaze and body . This must be the effect of the neuronal organization of the visual areas of our brains that succeed in maintaining in our consciouness a representation that seems to be protected from brutal variations . We propose a theory to account for an invariance that pertains to such image features as edges and textures . It is based on the simple assumption that the spatial variations of the image intensity , its derivatives , are extracted and represented in some visual brain areas by populations of neurons that excite and inhibit each other according to the values of these derivatives . Geometric transformations of the retinal image , caused say by eye movements , affect these derivatives . Assuming that their representations are invariant to these transformations , we predict the appearance of specific patterns of activity which we call hyperbolic planforms . It is surprising that the geometry that emerges from our investigations is not the usual Euclidean geometry but the much less familiar hyperbolic , non-Euclidean , geometry . We also propose some preliminary ideas for putting our theory to the test by actual measurements of brain activity .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"neuroscience/cognitive",
"neuroscience",
"neuroscience/sensory",
"systems",
"mathematics",
"neuroscience/natural",
"and",
"synthetic",
"vision",
"neuroscience",
"neuroscience/theoretical",
"neuroscience"
] |
2009
|
Hyperbolic Planforms in Relation to Visual Edges and Textures Perception
|
Strongyloides stercoralis infects human hosts mainly through skin contact with contaminated soil . The result is strongyloidiasis , a parasitic disease , with a unique cycle of auto-infection causing a variety of symptoms and signs , with possible fatality from hyper-infection . Australian Indigenous community members , often living in rural and remote settings , are exposed to and infected with S . stercoralis . The aim of this review is to determine barriers to control of strongyloidiasis . The purpose is to contribute to the development of initiatives for prevention , early detection and effective treatment of strongyloidiasis . Systematic search reviewing research published 2012 and earlier was conducted . Research articles discussing aspects of strongyloidiasis , context of infection and overall health in Indigenous Australians were reviewed . Based on the PRISMA statement , the systematic search of health databases , Academic Search Premier , Informit , Medline , PubMed , AMED , CINAHL , Health Source Nursing and Academic was conducted . Key search terms included strongyloidiasis , Indigenous , Australia , health , and community . 340 articles were retrieved with 16 original research articles published between 1969 and 2006 meeting criteria . Review found barriers to control defined across three key themes , ( 1 ) health status , ( 2 ) socioeconomic status , and ( 3 ) health care literacy and procedures . This study identifies five points of intervention: ( 1 ) develop reporting protocols between health care system and communities; ( 2 ) test all Indigenous Australian patients , immunocompromised patients and those exposed to areas with S . stercoralis; ( 3 ) health professionals require detailed information on strongyloidiasis and potential for exposure to Indigenous Australian people; ( 4 ) to establish testing and treatment initiatives within communities; and ( 5 ) to measure and report prevalence rates specific to communities and to act with initiatives based on these results . By defining barriers to control of strongyloidiasis in Australian Indigenous people , improved outcomes of prevention , treatment of strongyloidiasis and increased health overall are attainable .
Strongyloidies stercoralis , a nematode parasite , is well documented as a potentially fatal soil transmitted helminth , described as a unique and complex human parasite in Speare [1] . S . stercoralis is a cosmopolitan parasite , but is more prevalent in tropical regions of the world , including tropical Australia . Rural and remote regions of Australia , in particular , Queensland , Northern Territory , Western Australia , north of South Australia and northern areas of New South Wales , endemic rates [1]-[5] . Australia's Indigenous communities have high prevalence of strongyloidiasis ( disease resulting from S . stercoralis ) as do immigrants from other endemic countries , travellers to these countries and military personnel who have spent time in endemic regions [6] , [7] . Soulsby , Hewagama and Brady [8] report four cases of strongyloidiasis in non-Indigenous people resulting from work-related exposure presenting at Alice Springs Hospital and by implication acquired indirectly from Indigenous populations . Those infected included a teacher at an Indigenous school , a child care worker , an ex-nurse and a paediatrician . Very high prevalence rates are reported for Australian Indigenous communities [3] , [4] , [6] , [7] , [9] , [10] . Johnston , Morris , Speare , et al . [7] describe strongyloidiasis as a clinically important condition in Australia . Kline , McCarthy , Pearson , et al . [11] discuss major neglected tropical diseases in Oceania and emphasize strongyloidiasis as an important infection despite the lack of data on overall prevalence rates and clinical impact . Strongyloidiasis in a community is evidence that individual ( s ) in that community has been exposed to S . stercoralis from soil contaminated by human faeces [6] . Infected individuals pass first stage larvae in the faeces; these develop on the soil to infective larvae which penetrate the skin of the next host . After a blood-lung migration , parasitic adult females ( there is no parasitic male ) molt and develop into adult female worms in tunnels in the small intestinal mucosa [12] . Eggs are then laid in the tunnels , hatch , and produce first stage larvae in the intestinal lumen . Most of these pass out in the feces . A small number , however , change to infective larvae in the gut . These autoinfective larvae penetrate the wall of the large intestine and re-enter the body . Hence , S . stercoralis is a very unusual nematode , producing infective larvae not only externally in the soil , but also internally [12] . The occurrence of the autoinfective larvae is the main reason strongyloidiasis is such a serious disease [12] , [13] . Infection is life-long since adult worms are replaced by young worms and the infection does not end when the original crop of adults die . Worm numbers can rise incrementally to produce severe disease , known as the hyperinfection syndrome . Autoinfective larvae , migrating from the lumen of the large intestine , can carry enteric bacteria into the body , resulting in sepsis in any organ . Of patients with the hyperinfection syndrome , 50% present with a septic event ( pneumonia , septicaemia , meningitis , peritonitis ) usually caused by an enteric bacteria or polymicrobial suite of enteric bacterial [14] . Complicating this is that S . stercoralis has an immunosuppressive effect [15] , [16] . Hyperinfection occurs mainly , but not exclusively , in the people who are immunocompromised or immunodeficient with a high case fatality rate of hyperinfection , at least 60% [6] , [7] , [9] , [10] , [13] , [17] , [18] . Strongyloidiasis is usually symptomatic [14] but most signs and symptoms are non-specific . The exception is with larva currens , a rapidly moving urticarial linear rash that marks the passage of an autoinfective larvae through the skin [14] , [19] . This is pathognomonic of strongyloidiasis . The other non-specific signs and symptoms can include gastrointestinal ( e . g . , abdominal pain , nausea , diarrhea , weight loss ) , respiratory ( e . g . , cough ( productive and non-productive ) , haemoptysis , cutaneous ( e . g . , urticara ) and general malaise [7] , [10] , [14] , [20] . Hyperinfective strongyloidiasis , in addition to the spectrum of acute-infection symptoms , can also clinically present as paralytic ileus , pulmonary haemorrhage , pneumonia , meningitis , septicaemia or other bacterial infections [6] , [10] , [14] , [16] , [18] , [20]–[22] . Diagnostic testing includes serology and faecal examination . Once diagnosed , strongyloidiasis can be eradicated with specific anthelmintics , ivermectin being the drug of choice [6] , [7] , [12] , [17] . The recommended treatment for strongyloidiasis has changed with the development of more effective anthelmintic drugs . Thiabendazole was the first moderately effective anthelmintic introduced in the mid-1970s [23] , [24] . Albendazole , a benzimidazole like thiabendazole , was recommended as the treatment of choice for strongyloidiasis about the mid-1990s [25] . It was replaced by ivermectin as first line recommended anthelmintic in the early 2000s [10] . In Australia , ivermectin is not licensed for children <5 years or for use in pregnancy [26] , [27] , although there is no evidence of harm in these groups [10] . Albendazole is used for > 6 months and <10 kg to adults , not licensed for use during pregnancy [26]–[28] . Fatality from strongyloidiasis most often results from missed or late diagnosis , inadequate treatment and/or the use of immunosuppressant drug therapy in high risk groups [6] , [10] , [17] . Co-infection of strongyloidiasis with HTLV-1 is associated with more serious strongyloidiasis and potential resistance to treatment [10] , [15] . In addition , HTLV-1 carriers are more likely to develop T-cell leukaemia when infected with S . stercoralis [29]–[32] . There are questions about the limited information available about the prevalence , clinical picture , diagnosis and public health approaches to manage strongyloidiasis in rural and remote Indigenous communities in tropical regions of Australia [5] , [33] . Programs based on the treatment of stool positive individuals have also been associated with decreases in prevalence [7] . Researchers suggest that little published evidence of public health approaches to control strongyloidiasis exists [7] , [34] and there is a need to consider mass drug administration in Indigenous Australian communities with high prevalence of strongyloidiasis [10] , [11] . This systematic review attempts to answer the questions , what is the epidemiology of strongyloidiasis in Australian Indigenous people , and , what , if any , are the mentioned barriers to control ? The aim of this review is to identify research focused on strongyloidiasis in this specific population and to collect and analyse available data specific to symptoms , diagnosis and treatment to determine barriers to control of strongyloidiasis . For the purpose of this paper , we respectively use the term Indigenous to represent Australian Aboriginal people and Torres Strait Islanders .
The outline and focus of this paper is framed on the concept of a translational research framework described by Thomson [35] within the Australian Indigenous HealthInfoNet . This systematic review was designed as a narrative review of the evidence as a way to summarise , explain and interpret evidence with thematic analysis [36] . This systematic review was based on the PRISMA statement , a tool to summarize accurate , reliable , quality evidence by way of transparent reporting ( Checklist S1 ) [37] , [38] . A systematic search of health databases , Academic Search Premier , Informit , Medline , PubMed , AMED , CINAHL , Health Source Nursing and Academic was performed to search for all articles published 2012 and prior were included in the search . Articles were searched through the online academic search site , Google Scholar and internet searches for websites containing information about strongyloidiasis . Key search terms included strongyloidiasis , Indigenous , Australia , health , and community with search strategy developed to access the broadest range of articles about strongyloidiasis are presented in Table 1 . Reference lists of original articles , review articles , grey literature and websites were searched for potential articles to review for inclusion . Language restrictions were not imposed . To meet inclusion criteria , original qualitative or quantitative research articles contained content addressing one or more of the following: symptoms , diagnosis , treatment , and barriers to control of strongyloidiasis . The location of the studies had to be Australia and include Australian Indigenous people . Exclusion criteria included , review articles and non-peer reviewed literature , original research articles with animal only studies , pharmaceutical therapy only studies and studies not differentiating S . stercoralis or strongyloidiasis from amongst other parasites or parasitic infections . Based on these selection criteria , articles were reviewed in two stages . First stage , article titles and abstracts were screened to meet the requirements of strongyloidiasis as topic , Australian location and inclusion of Indigenous Australians . Second stage , articles were read as full text . Articles meeting final criteria were included in the study . Figure 1 represents the overall article search outcome . From the original research questions , ( 1 ) what is the epidemiology of strongyloidiasis in Australian Indigenous people ? and ( 2 ) what , if any , are the mentioned barriers to control ? Description of studies was collected and a thematic analysis conducted [36] . Key data extracted were: purpose of study , study design , participant description , symptoms , diagnosis , treatment , barriers to control , and author's conclusions . Articles were presented in a database with publisher details and summarized key data . The categories of symptoms , diagnosis , treatment and barriers to control were further assessed and coded using thematic analysis to determine recurring items in each . Symptoms were defined as manifestations of strongyloidiasis and included symptoms and signs due to strongyloidiasis and other existing concurrent conditions . Diagnosis was defined medical diagnoses including health status , tests performed and results . Assessment of treatment of strongyloidiasis was based on the recommended therapy at the time of publication and defined as details on therapy provided and the comments on outcomes . Barriers to control were defined as a medical context , symptom and/or condition , or social determinant ( derived from categories of symptoms , diagnosis , treatment and each authors' summary and conclusions ) that inhibited overall health and/or recovery from strongyloidiasis of the individual ( s ) . Once the barriers to control items were documented , they were then coded into barrier themes and health level . Detailing each barrier and the associating theme and level supports the translational knowledge concept by assisting to identify the relevant stakeholders [39] .
Figure 1 provides an overview of the literature search results . 340 articles were retrieved with a total of 16 articles , published between 1969 and 2006 , eligible for the systematic review and are summarized in Table 2 . Eleven eligible articles were from electronic library databases . Google Scholar revealed two additional eligible articles . The reference lists reviewed from published articles , grey literature and internet websites reporting on strongyloidiasis infections of Indigenous people of Australia revealed three eligible articles . Study design included case studies , retrospective and prospective comparison and non-comparison studies . Participant numbers ranged from 1 to 683 . Indigenous Australian children were reported in 12/16 studies , of those 8/12 reported children only . Indigenous Australian adults were reported in 7/16 studies , of which 4/7 reported adult only . Thirteen studies were conducted in hospital and four in Indigenous communities . Eleven studies examined strongyloidiasis only with the remaining discussing the parasitic infection in the context of other infections [40] , [41] or while examining gastrointestinal issues [42]–[44] . The 16 papers included 2537 Indigenous participants and 272 non-Indigenous participants . Eleven papers described manifestations of strongyloidiasis , including symptoms and signs due to strongyloidiasis as well as other concurrent conditions ( Table 3 ) . Studies noted strongyloidiasis symptoms such as diarrhoea , malnutrition and anorexia , abdominal pain , abdominal distension , anemia , septicaemia , and fever . Other concurrent conditions including Type 2 Diabetes , Lupus , Chronic Liver Disease and Chronic Lung Disease , Alcoholism , Pneumonia , Bronchitis , COPD , Acute Rheumatic Fever , Acute Renal Failure and/or general gastrointestinal , cardiac and respiratory problems were reported . Gunzburg , Gracey , Burke , et al . [43] reported only diarrheal symptoms as this was the scope of the study . Page , Dempsey , and McCarthy [28] and Prociv & Luke [5] , although studying strongyloidiasis specifically , did not focus on symptomology . Four studies [4] , [15] , [40] , [42] did not discuss symptomology due to the aim of the study . All sixteen studies provided data on diagnosis of strongyloidiasis determined by one or more tests ( Table 4 ) . Nine studies performed purposeful testing [4] , [5] , [21] , [28] , [40]–[43] . Five studies reported strongyloidiasis had been diagnosed when not suspected [15] , [22] , [42] , [45] , [46] . Articles were reviewed for the adequacy of treatment noting that recommended therapy has changed with time ( Table 5 ) . Eight articles discussed the use of one or a combination of albendazole , thiabendazole and ivermectin . Three articles described a subgroup of patients receiving no therapy [28] , [42] , [45] and one article mentioned the use of pyrantel only for strongyloidiasis [5] . Pyrantel is ineffective against S . stercoralis [47] . In two articles , prednisolone or prednisone , a treatment which suppresses the immune system and as a result can increase the severity of strongyloidiasis , was administered to patients . Walker-Smith [42] discussed diagnoses of giardiasis and strongyloidiasis in children and provided no data on treatment . Einsiedel & Fernandes [15] detailed treatment therapies across four case studies , of which , only one case received correct strongyloidiasis treatment with ivermectin . Overall , adequate treatment was documented in publications in only 5 . 2% of cases . Barriers to control of strongyloidiasis were summarized in terms of item , theme and health access level ( Table 6 ) . Three barriers themes emerged as items contributing to adequate management of strongyloidiasis: ( 1 ) health status; ( 2 ) socioeconomic status; ( 3 ) health care literacy and procedures . Theme 1 , health status was defined patients' health prior to and at the time of diagnosis of strongyloidiasis . This included concurrent infections ( e . g . , meningitis , pneumonia ) , concurrent chronic health conditions ( e . g . , Lupus , Chronic Liver Disease , Chronic Lung Disease , Acute Rheumatic Fever , HTLV-1 , Hepatitis B , alcoholism , immunocompromised , immunosuppressed ) and the phenomenon of strongyloidiasis ( e . g . , re-infection , hyperinfection , at times asymptomatic , chronic diarrhoea , septicaemia ) . Theme 2 , socioeconomic status included living conditions , racial disparities , communication ( e . g . , interaction between community , patients , health professionals/institutions ) . Theme 3 , health care literacy and procedures involved barriers that influence the diagnosis and treatment outcomes ( e . g . , delayed diagnosis , difficult to detect , failure to recognize symptoms , inadequate knowledge/treatment/treatment dose , serology test cut off , lack of communication , lack of screening , lack of follow-up , treatment non-compliance ) . Einsiedel & Fernandes [15] had the largest number of symptoms and signs and other conditions associated with barriers to control of strongyloidiasis . The top four barriers listed most often ( determined by the most barriers per article , total of 4 ) were delayed diagnosis , inadequate treatment , living conditions and malnutrition . Barriers to control are located across all four health access levels: ( 1 ) Individual; ( 2 ) Public/Community; ( 3 ) Organization; and ( 4 ) Healthcare system .
The broad spectrum of symptoms , as represented in manifestations of strongyloidiasis in Table 3 , illustrates the complex nature of Strongyloidiasis that is so often misdiagnosed . Many of these manifestations , such as diarrhoea , stomach pain , malnutrition , dehydration and vomiting are common to many illnesses and diseases . As described by researchers [6] , [15] , [16] , [20] , [43] , [45] , [46] , strongyloidiasis can present many varying symptoms or be asymptomatic [43] , [46] . It is important to recognize that strongyloidiasis can potentially exist for years presenting often with non-specific symptoms and signs ( e . g . , diarrhoea ) as well as at times with periods without symptoms . Delayed diagnosis , inadequate knowledge/treatment/treatment dose , lack of communication and lack of follow up by health professionals were described as particular issues in the majority of studies [5] , [15] , [16] , [22] , [29] , [40] , [44] , [45] , [50] , [51] . Infection should be suspected in every person with unexplained abdominal pain , diarrhoea , cutaneous symptoms or eosinophilia and the laboratory alerted of a provisional diagnosis [45] . Testing for strongyloidiasis is particularly important for patients from populations in S . stercoralis endemic areas . Rural and remote Indigenous communities ( more specifically northern Australia ) and including immunocompromised patients are at particular risk for hyperinfecion before administering immunosuppressive medication [22] . Protocol including clinical screening index , stool microscopy and culture , full blood count , immunoglobulin levels , and serological testing is recommended [22] . Majority of studies reported Indigenous Australian children with strongyloidiasis suggesting a diagnosis of strongyloidiasis should be considered when Indigenous children presenting with even non-suspecting general gastro-intestinal symptoms . Mucosal damage in Indigenous Australian children is possibly a result of damage produced by repeated episodes of gastroenteritis and/or parasitic infection , including strongyloidiasis [42] . Reduction in the frequency of gastroenteritis and parasitic infection in Indigenous children should greatly reduce incidence of small intestinal mucosal damage [42] . Working to eradicate or reduce strongyloidiasis infection in children with early detection and immediate treatment could decrease strongyloidiasis and mucosal damage . Given the challenges of diagnosing infection , standardizing treatment in communities for an extended period could potentially decrease infections rates [5] . Parasitic diseases have significant health risk and morbidity for Australian Indigenous people [11] , [20] . Rural and remote communities are the most affected [3] , [18]; mainly in children; and those immunocompromised with a number of cases of fatality reported [15] , [22] , [40] , [41] . Studies in 2002 and 2005 report there are limited published examples of community interventions in Australia to control strongyloidiasis [7] , [52] . Johnston , Morris , Speare , et al . [7] found no evidence of studies examining roles of environmental interventions and expressed the need to do so . The need for initiatives for housing and sanitation are imperative [15] . Issues of environmental health must be addressed concurrently with health service initiatives to develop long term and sustainable improvements in control of infectious parasitic and non-parasitic diseases in rural and remote Indigenous communities in Australia [10] , [11] , [20] . There may be increased risks associated with a casual approach to management and may be significantly higher for Indigenous Australian people living in HTLV-1 endemic Central Australia [10] , [40] . Einsiedel and Woodman [40] further state the risk of strongyloidiasis in Indigenous communities and HTLV-1 infection may further predispose people to complicated strongyloidiasis . Steps to address the barriers to control should include: ( 1 ) development of S . stercoralis and strongyloidiasis reporting protocols across health care system and communities ( e . g . , consistent case study reporting methods , documentation of current infection sites ) [6] , [40]; ( 2 ) testing all Indigenous Australian patients , immunocompromised patients and those exposed to or living in areas of strongyloidiasis ( e . g . , rural/remote communities ) presenting with gastrointestinal or respiratory symptoms ( take particular notice of individuals from these groups with repeated visits to hospital ) [7] , [15] , [16] , [48]; ( 3 ) requirement of health professionals to have detailed information and education regarding strongyloidiasis and the potential for exposure in Indigenous Australian communities ( e . g . , understanding of the expanse of symptoms and potential for asymptomology , difficulty in diagnosis , need for variety of tests and retesting , accurate follow-up to confirm patient cleared of infection ) [5] , [15] , [21] , [42]; ( 4 ) establishment of testing and treatment initiatives in the community ( e . g . , over extended periods and periodically and treat symptomatic and asymptomatic strongyloidiasis carriers ) [6] , [10] , [12] , [15] , [45]; ( 5 ) measure and report prevalence specific to Indigenous Australian communities and to act with initiatives based on these results [6] , [12] , [40] .
|
Strongyloides stercoralis , a nematode parasite , has a well-documented history of infecting human hosts in tropic and subtropic regions mainly through skin contact with inhabited soil . The result is strongyloidiasis , a human parasitic disease , with a unique cycle of auto-infection contributing to a variety of symptoms , of which , hyper-infection causing fatality may occur . In Australia , Indigenous community members often located in rural and remote settings , are exposed to and infected with strongyloides . Previous researchers report strongyloidiasis as a recurrent health issue for Indigenous Australians . This is a systematic review to determine the barriers to control for this pernicious pathogen . Barriers to control can be defined across three key themes: ( 1 ) health status , ( 2 ) socioeconomic status , and ( 3 ) health care literacy and procedure . By conceptualizing these barriers and addressing steps to control as outlined in this study , there is potential for improvement in prevention and treatment outcomes of strongyloidiasis and subsequently , overall health for Australian Indigenous people . This study contributes to furthering prevention and treatment of strongyloidiasis , increasing exposure to the issue of strongyloidiasis in Australian Indigenous people . It is the intent of this paper to express the need to have continued research and further health policy directed specifically to eradicate strongyloidiasis in Australian Indigenous communities .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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"medicine",
"and",
"health",
"sciences",
"tropical",
"diseases",
"geographical",
"locations",
"australia",
"parasitic",
"diseases",
"parasitology",
"health",
"care",
"ethnicities",
"indigenous",
"australians",
"neglected",
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"helminth",
"infections",
"environmental",
"health",
"oceania",
"systematic",
"reviews",
"strongyloidiasis",
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] |
2014
|
Strongyloides stercoralis: Systematic Review of Barriers to Controlling Strongyloidiasis for Australian Indigenous Communities
|
Once Aedes aegypti and Aedes albopictus mosquitoes that spread Chikungunya virus , dengue virus , and Zika virus are infected with Wolbachia , they have reduced egg laying rates , reduced transmission abilities , and shorter lifespans . Since most infected mosquitoes are only infectious in the last few days of their lives , shortening a mosquito’s lifespan by a day or two can greatly reduce their abilities to spread mosquito-borne viral diseases , such as Chikungunya , dengue fever , and Zika . We developed a mathematical model to compare the effectiveness of the wMel and wAlbB strains of Wolbachia for controlling the spread of these viruses . The differences among the diseases , mosquitoes , and Wolbachia strains are captured by the model parameters for the mosquito-human transmission cycle . Moreover , the model accounts for the behavior changes of infectious population created by differences in the malaise caused by these viruses . We derived the effective and basic reproduction numbers for the model that are used to estimate the number of secondary infections from the infectious populations . In the same density of Wolbachia-free Aedes aegypti or Aedes albopictus mosquitoes , we observed that wMel and wAlbB strains of Wolbachia can reduce the transmission rates of these diseases effectively .
The current pandemics of Chikungunya caused by Chikungunya virus ( CHIKV ) , dengue fever caused by dengue virus ( DENV ) , and Zika resulted from Zika virus ( ZIKV ) infect over one hundred million people each year [1] . In the past decade , CHIKV has spread around the world [2 , 3] and recently over a million cases occurred in the Caribbean and Latin America . Symptoms of infection with CHIKV include high fever and headache , with arthritis affecting joints , and may sustain for weeks or months [4] . Dengue fever has spread around the world and is endemic in South America and Asia [1] . People infected with DENV have symptoms ranging from mild headaches , severe headaches and joint pains to hemorrhagic or shock syndrome fever . Recently , ZIKV has spread through the Americas , starting with a 2015 explosive outbreak in Brazil . Although most people infected with ZIKV have mild symptoms , there is a correlation between infections in pregnant women and their children born with microcephaly ( an abnormally small brain ) . Currently no vaccines are commercially available for Zika and Chikungunya . The first dengue vaccine , Dengvaxia ( CYD-TDV ) , registered in Mexico in December , 2015 is not effective for the younger ones and for the seronegative population due to ethical concern of non-maleficence [5] . Although both Aedes aegypti ( Ae . aegypti ) and Aedes albopictus ( Ae . albopictus ) mosquitoes can transmit these viruses , Ae . aegypti mosquitoes are more abundant in urban areas and are the primary vectors . Current prophylactic measures include individual protection from mosquito bites , such as applying mosquito repellent and avoiding exposure to mosquitoes . Limited control options focus on reducing the mosquito populations , including spraying insecticides , treatments , and removal of mosquito breeding sites . These control strategies are hard to sustain because of the vigilance needed to eradicate the breeding sites , the expense of repeated spraying , and the mosquitoes developing resistance to the insecticides . The cost and difficulty of eliminating the mosquitoes motivate the need of developing more efficient strategies to mitigate and control the transmission of these viruses . Wolbachia is a genus of bacteria that can infect 25-75% of all insects [6] and recent studies have shown that some strains of Wolbachia can increase the resistance of mosquitoes being infected with these viruses [7] . Recent experiments have shown that wMel strain of Wolbachia infection in Ae . albopictus inhibits the growth of CHIKV [8] . Moreover , Wolbachia infection in mosquitoes reduces egg laying rates , reduces their ability of transmitting viral infections , and shortens their lifespans by a few days . Since many mosquitoes infected with DENV , ZIKV , or CHIKV are infectious for only a few days at the end of their lifespans , the shortened lifespans of Wolbachia-infected mosquitoes result in more mosquitoes dying before they can transmit the infection . This implies that Wolbachia-infected mosquitoes sustaining in a wild mosquito population will be less likely to transmit these viral diseases . Infected females can pass the bacteria to their offsprings and spread Wolbachia vertically from one generation to the next . Wolbachia disrupts the reproductive cycle of hosts through a cytoplasmic incompatibility between the sperms and eggs . Cytoplasmic incompatibility occurs when Wolbachia-infected male mosquitoes mate with Wolbachia-free female mosquitoes , and causes the Wolbachia-free females to produce fewer progeny [9 , 10] . These effects provide the Wolbachia a vertical transmission advantage . However , this is offset by a reduced lifespan and reduced number of eggs hatched by a Wolbachia-infected mosquito . When Wolbachia-infected mosquitoes are introduced in a wild population of uninfected mosquitoes , the infection is quickly wiped out unless the fraction of infected mosquitoes exceeds a threshold θ of the total population . Recent mathematical models have established these threshold conditions as θ = 0 . 15 , 0 . 24 , and 0 . 6 for wAlbB- , wMel- , and wMelPop-infected mosquitoes to establish a stable population , respectively [11] . Note that these threshold estimates are for an ideally controlled situation where mosquitoes do not mix with surrounding uninfected mosquitoes . The thresholds could be much higher for a release in the wild . Recent studies have found that maintaining a sustained wMelPop-infection requires continually introducing new wMelPop-infected mosquitoes into the wild population [12] . A recent research has reported that large-scale releases of Wolbachia-infected Ae . aegypti in the city of Cairns , Australia , invaded and spread through the populations , while Wolbachia infection at a smaller release site collapsed due to the immigration of Wolbachia-free mosquitoes from surrounding areas [13] . Population cage experiments indicated that the wAlbB strain can be successfully introduced into populations , and subsequently persist and spread [14] . Ndii et al . analyzed a first-order differential equation and found that a significant reduction in human dengue cases can be obtained by releasing wMel-infected mosquitoes , instead of wMelPop-infected mosquitoes due to the greatly reduced lifespans [15] . Ferguson et al . developed a mathematical model of DENV transmission incorporating the dynamics of viral infection in humans and mosquitoes , and predicted that wMel-infected Ae . aegypti mosquitoes have a substantial effect on transmission [16] . Ross et al . found that , in most situations , it was easier to establish wMel than wAlbB in mosquito populations , except when the conditions were particularly hot [17] . They also observed that the wMel infected larvae survived better than wAlbB infected larvae under starvation conditions [18] . Many mathematical models have been developed to explore conditions under which Wolbachia can be used to fight against the spread of viruses effectively . The analysis of a compartmental mathematical model showed that a significant reduction in human dengue cases can be obtained provided that Wolbachia-infected mosquitoes persist when competing with Wolbachia-free mosquitoes [15] . Zhang et al . developed an ordinary differential equation ( ODE ) model to assess how best to replace DENV vectors with Wolbachia-infected mosquito populations and the results showed that successful population replacement will rely on the selection of suitable strains of Wolbachia and careful design of augmentation methods [19] . The analysis for an impulsive model for Wolbachia infection control of mosquito-borne diseases with general birth and death rates showed that strategies may be different due to different birth and death rate functions , the type of Wolbachia strains , and the initial number of Wolbachia-infected mosquitoes [20] . Xue et al . [21] created a two-sex model that included an egg/aquatic stage for the mosquito lifecycle and observed that an endemic Wolbachia infection can be established only if a sufficient number of infected mosquitoes are released . Recently , this model was extended by Qu et al . [22] to better account for the cytoplasmic incompatibility by considering the fact that most female mosquitoes only mate once . They used the model to investigate the effectiveness of multiple releases of infected mosquitoes in sustaining an endemic Wolbachia infection . Manore et al . [23] used a mathematical model to compare the spread of DENV and CHIKV in Ae . aegypti and Ae . albopictus mosquitoes that are not infected with Wolbachia . Our study is based on extending these results to evaluate the effectiveness of infecting these mosquitoes with different strains of Wolbachia to show their different roles in controlling different vector-borne diseases . In our model , we assume that lifespans of the infected adult mosquitoes are slightly shorter than those of uninfected mosquitoes ( reducing transmission ) , and the larval survival rates of wAlbB-infected mosquitoes are less than those of wMel-infected mosquitoes ( making invasion somewhat potentially harder for wAlbB ) . We evaluated the effectiveness of infecting these mosquitoes with wMel and wAlbB strains of Wolbachia to show their different roles in controlling the transmission of DENV , ZIKV , and CHIKV . Since transmission of ZIKV is estimated to be similar to transmission of DENV but exact values of parameters are not available [24] , we assume that the parameter values for ZIKV are the same as those for DENV except the fraction of infectious humans exposed to mosquito bites . Our simulation results show that the differences between the spread of DENV and ZIKV lie in different behaviors of infectious humans , and wMel is more effective than wAlbB strain of Wolbachia in simulations with the available baseline parameters .
The basic reproduction number , R 0 , is defined as the number of new infections produced by one infected individual in a completely susceptible population . When the population is not fully susceptible , or more than one person is infected , then the effective reproduction number , R e f f ( t ) , estimates the number of secondary cases produced by a typical infected individual at any time during the epidemic . We derived the effective reproduction number from infectious point of view for DENV , ZIKV , and CHIKV to estimate the reproduction rate of an epidemic at any stage . Because this is a bipartite transmission cycle , mosquitoes only infect humans and humans only infect mosquitoes , we have different effective reproduction numbers for each part of the cycle . We define R h v ( t ) as the effective reproduction number for transmission from mosquitoes to humans , and is the average number of humans infected by one infectious mosquito . Similarly , R v h ( t ) defined as the effective reproduction number for transmission from humans to mosquitoes , is the average number of mosquitoes infected by one infectious human . These dimensionless numbers are defined by R h v ( t ) = P v α v ( t ) τ i v , ( 5 ) R v h ( t ) = P h α h ( t ) τ i h . ( 6 ) Here , in Eq ( 5 ) , Pv = νv/ ( νv + μv ) is the probability that an infected mosquito survives through the incubation period and becomes infectious , αv ( t ) is the average number of susceptible people infected by an infectious mosquito per day , and τiv = 1/μv is the average life span of a mosquito . Similarly for Eq ( 6 ) , Ph = νh/ ( νh + μh ) is the probability that an infected human becomes infectious , αh ( t ) is the average number of susceptible mosquitoes infected by an infectious person per day , and τih = 1/ ( γh + μh ) is the average time that a human remains infectious . The explicit expressions of R h v ( t ) and R v h ( t ) are: R h v ( t ) = ν v ( ν v + μ v ) β h v b i v S h ( t ) N v ( t ) 1 μ v , R v h ( t ) = ν h ( ν h + μ h ) β v h b i h S v ( t ) N h ( t ) 1 γ h + μ h . Because a full transmission cycle is consisted of two stages , and R e f f ( t ) measures the average effective reproduction number over one cycle . We take the geometric average of these two reproductive numbers to define: R e f f ( t ) = R h v ( t ) R v h ( t ) . We denote S h * as the population of susceptible people at the endemic equilibrium ( EE ) for Model ( 1 ) . We define the fraction of humans susceptible at the EE , S h * / H 0 of the population has never been infected , as susceptibility of humans at EE , S h * H 0 = 1 - ( 1 - π R 0 2 ) ν v σ v σ h β h v V 0 ν v σ v σ h β h v V 0 + μ h ( μ v + ν v ) ( σ h H 0 + σ v V 0 ) . To quantify the differences in impact of different strains of Wolbachia on an epidemic , we define the coefficient for effectiveness [15] as the relative decrease in the number of people predicted to be infected if the mosquitoes are infected with Wolbachia , HW , compared with the predicted number of people who will be infected if the mosquitoes are Wolbachia-free , HF; κ = H F - H W H F = 1 - H W H F . ( 7 ) If κ = 1 , then Wolbachia is predicted to be effective in stopping all the infections , while if κ = 0 , then it is predicted to have no effects on the epidemic . The basic reproduction number is the effective reproduction number at the disease free equilibrium where Sv ( 0 ) = V0 and Sh ( 0 ) = H0 , and all other states are zero: R 0 = R h v ( 0 ) R v h ( 0 ) . R h v ( 0 ) and R v h ( 0 ) are the effective reproduction numbers for the vectors and humans at the disease free equilibrium: R h v ( 0 ) = ν v ( ν v + μ v ) β h v b i v ( 0 ) 1 μ v , R v h ( 0 ) = ν h ( ν h + μ h ) β v h b i h ( 0 ) 1 γ h + μ h . The biting rates at the disease free equilibrium are biv ( 0 ) = b ( 0 ) /V0 and bih ( 0 ) = πb ( 0 ) /H0 , where b ( 0 ) = σ v V 0 σ h H 0 σ v V 0 + σ h H 0 . The basic reproduction number derived in this way is consistent with the R 0 computed using the next generation matrix approach in [23] . After an epidemic has run its course and the infection has died out , then the previously infectious people are immune to new infections . R e f f is the average number of new infectious individuals produced in one cycle when an infectious human or mosquito is introduced into the population where some of the population is immune to infection . We define ph = Rh ( 0 ) /H0 as the fraction of people who are immune to the infection , such as those who have already had the disease or have been immunized . If we reinitialize our model at t = 0 with an infection-free equilibrium , such as the beginning of a seasonal outbreak , where ph of the humans are immune to the infection , Rh ( 0 ) ≠ 0 , and Sh ( 0 ) + Rh ( 0 ) = H0 . For this case , the effective reproduction number for human-to-mosquito transmission , R v h ( 0 ) e f f = R v h ( 0 ) , is unchanged , while the effective reproduction number for mosquito-to-human transmission is reduced to R h v ( 0 ) e f f = R h v ( 0 ) ( 1 - p h ) . Therefore , the effective reproduction number for Model ( 1 ) with ph people immune to infection becomes R e f f ( 0 ) = R h v ( 0 ) e f f R v h ( 0 ) e f f = R h v ( 0 ) R v h ( 0 ) ( 1 - p h ) = R 0 1 - p h . Note that , unlike human-to-human transmitted disease where the R 0 is reduced by ( 1 − ph ) when ph of the population is immune , R 0 is only reduced by 1 - p h in this bipartite epidemic . In the simulations , the parameters are set to the baseline values in Table 2 , unless specifically stated otherwise . Most of the parameter values used in this study were derived , or extensively referenced , by Manore et al . [23] for disease transmission in Wolbachia-free mosquitoes . Manore et al . provided a comprehensive sensitivity analysis on how the model predictions change with respect to variations in the key parameters [23] . Although these baseline values are our best estimates for the parameters , they are scalar estimates from a distribution of possible values . To help quantify the uncertainty in the parameters , we will investigate the behavior of the model over a wide range of feasible parameters . The model predictions for a specific value of the basic reproduction number or the fraction of the population infected at the endemic equilibrium depend on the specific values used in the simulations . Although these specific values for these predictions are sensitive to the parameter values , we find that the qualitative differences between different diseases and strains of Wolbachia are fairly insensitive over the feasible ranges of parameters . We assume that the probability of transmission per bite from a mosquito to a human is related to the viral load in the mosquito . Recent experimental comparisons of the growth of DENV , ZIKV , and CHIKV in mosquitoes indicate that the viral loads and the extrinsic incubation period ( EIP ) for an infected mosquito to become infectious are comparable [34] . Because there are no experimental estimates for the infectivity of ZIKV-infected mosquitoes , we assume that the parameter values for infectivity of ZIKV are the same as those of DENV in our simulations . Note that , although we assume that the probability of transmission per mosquito bite is assumed to be the same for ZIKV- and DENV- infected mosquitoes . The behavior changes of humans infectious with ZIKV and DENV are different , leading to very different epidemics . That is , one must be very careful in extrapolating findings between ZIKV and DENV epidemics [24] . Duong et al . [26] showed that asymptomatic individuals infected with DENV may be infectious before the onset of symptoms and continue infecting mosquitoes as they visit multiple locations during the day . They also noted that sick people who are hospitalized or stay at home are only exposed to their residential mosquitoes . Grange et al . [25] summarized data from a large number of studies , showing that often 20–93% of DENV infected individuals are asymptomatic . In our simulations , we assume that 75% of DENV-infectious people continue exposing to mosquitoes ( π = 0 . 75 ) . Bloch et al . [27] concluded that about 62 . 5% CHIKV infections are symptomatic through extensive statistical analysis . They observed that about one-third of CHIKV-infected participants are asymptomatic , which is consistent with estimates of 3–39% asymptomatic cases in past outbreaks . Robinson et al . [28] also noted that 16 . 7–27 . 7% of the infections in Chikungunya outbreaks are asymptomatic . In our simulations , we assume that 30% of infectious people with CHIKV continue exposing to mosquitoes ( π = 0 . 30 ) . ZIKV infection is a self-limiting illness that is mostly asymptomatic . Lazear et al . [29] noted that approximately 20% of the individuals infected with ZIKV progress to a clinically apparent febrile illness , although rarely hospitalized . Rajah et al . [30] also observed that 20% of the people infected with ZIKV present mild symptoms . In our simulations , we assume that 80% of ZIKV-infectious people continue exposing to mosquitoes ( π = 0 . 80 ) . The Wolbachia infection changes the mosquito’s birth , death , biting rates , and the transmissibility of an infection . We account for the change in these parameters by including a scaling factor , ϕ* . We identify the rates of Wolbachia-free mosquitoes by a tilde , · ˜ , and define the factors for Wolbachia-infected mosquitoes as: The values for the factors ϕ* in Table 3 are used in Table 2 for the baseline parameter values used for this study . These factors coincide with the factors applied by [35] for comparing the effects of different strains of Wolbachia . The ranges of the lifespans for wMel-infected , wAlbB-infected , and Wolbachia-free mosquitoes in Table 2 coincide with the plot for longevity of wAlbB- and wMel- infected mosquitoes plotted by Joubert et al . [36] .
Fig 2 shows the cumulative number of infectious humans up to time t = 700 when 0 . 1% of humans are infected at t = 0 . The figure illustrates that the wMel-infected mosquitoes are more effective in slowing disease transmission than wAlbB-infected mosquitoes . For DENV and ZIKV , the number of people infected by Ae . aegypti mosquitoes is greater than the number of humans infected by Ae . albopictus mosquitoes carrying the same strain of Wolbachia . The opposite is true for CHIKV where the number of people infected by Ae . albopictus mosquitoes is greater than the number of people infected by Ae . aegypti mosquitoes carrying the same strain of Wolbachia . Note that in these simulations we assume the same mosquito populations for both genera . Typically the density of Ae . aegypti mosquitoes is much greater than the density for Ae . albopictus in urban areas , while the opposite is true in wooded rural areas . In this study , we only considered one mosquito genus at a time . When both mosquitoes are present , then the predictions will depend on the total mosquito population . As a first order approximation , the results are interpolated based on the fraction of each mosquito genus . The reproduction numbers depend on the ratio of mosquitoes to humans . The model predictions are scaled for all populations with the same ρvh = V0/H0 , V0 is the initial total number of mosquitoes , and V0 = Kv . In Fig 3 , the reproduction numbers are plotted as ρvh varies from a ratio of ρvh = 1 , with an equal number of mosquitoes as humans , to ρvh = 100 , with 100 times more mosquitoes than humans . Infecting mosquitoes with Wolbachia can reduce R 0 over the full range of mosquito to human ratios . When only few mosquitoes are present , then R 0 < 1 for all the diseases . As expected , R 0 increases as the number of mosquitoes increases , as more and more mosquitoes transmit the infection . When there are about 20 to 30 mosquitoes per human , then R 0 slowly decreases as the biting rate for the mosquitoes decreases . The rate of decrease depends upon the specific biting Eq ( 3 ) being used in the model . Table 4 lists the basic reproduction number computed with the baseline parameters . For this case , the R 0 of DENV ( ZIKV , or CHIKV ) transmitted by Wolbachia-free mosquitoes is the highest , followed by R 0 of DENV ( ZIKV , or CHIKV ) transmitted by mosquitoes infected with wAlbB strain of Wolbachia , and R 0 for mosquitoes carrying wMel strain is the smallest . The basic reproduction number for ZIKV is the largest in all cases . The basic reproduction number of DENV is greater than the basic reproduction number of CHIKV for mosquitoes carrying the same strain of Wolbachia or Wolbachia-free mosquitoes . The basic reproduction number is a function of the baseline parameters . Others may come up with different baseline values for different outbreaks . The readers can estimate the model response to different baseline values of a parameter using the sensitivity indices in Table 5 . The relative sensitivity index of the quality of interest , q , with respect to the parameter of interest , p is S p q≔p * q * × ∂ q ∂ p | p = p * = θ q θ p , as described in [23] , where the notation p* indicates that a variable is evaluated at the model baseline values . For example , S π R 0 = 0 . 0136 for DENV transmitted by wAlbB-infected Ae . aegypti mosquitoes , if we reduce π , by 10% , then R 0 will be reduced by 0 . 00136 , since −0 . 1 × 0 . 0136 = −0 . 00136 . Sensitivity indices of R 0 varying with the fraction of people exposed to mosquitoes are shown in Fig 4 . The effective reproduction number depends on the fraction of humans who are immune to the infection . Fig 5 shows the effective reproduction number varying with the immunity of humans , assuming that all mosquitoes are susceptible and the initial total mosquito population is V0 . The effective reproduction number decreases with the increase of the immunity of humans . When all humans are immune to the disease , then the effective reproduction number is the same as the basic reproduction number . Previous examples kept most of the parameters at their baseline values . If we allow all the parameters to vary over the entire feasible sampling space , we will obtain a distribution for R 0 . The distribution for R 0 is a function of the distributions for the model parameters as they vary within their allowed ranges . We assumed a triangular distribution that vanishes at the endpoints of the feasible region and has the mode at the baseline values in Table 2 . If we had assumed that the distribution was uniform over the range , where the parameter was just as likely to be at the upper or lower bound as our best guess ( the baseline case ) , then the ranges for the reproduction numbers in Fig 6 will not change , but the distributions will have fatter tails . The histograms of the distribution for R 0 for DENV , ZIKV , and CHIKV transmitted by Ae . aegypti are shown in Fig 6 . The means and medians of R 0 for wMel-infected mosquitoes are the smallest . R 0 for ZIKV is the largest , followed by DENV , and then CHIKV . In a similar analysis for Ae . albopictus , R 0 is the largest for ZIKV , followed by CHIKV , and the least is DENV . This is in agreement with the analysis where we varied the parameters one at a time over their feasible ranges . If Wolbachia is successful in reducing the spread of the viruses , then there will be more people uninfected at the EE . In Table 6 , the fraction of humans still susceptible at the EE for wMel-infected mosquitoes is the largest , while the susceptibility of Wolbachia-free mosquitoes is the smallest when a certain disease is transmitted by a certain genus of mosquitoes . For Ae . aegypti infected with the same strain of Wolbachia , the percentage of humans susceptible to CHIKV is higher than the percentage of humans susceptible to DENV or Zika . For Ae . albopictus infected with the same strain of Wolbachia , the percentages of humans susceptible to DENV and ZIKV are higher than the percentage of humans susceptible to CHIKV . Although the wMelPop-infected mosquitoes are the most effective in stopping an epidemic , it is unrealistic to consider a fully infected wild population of wMelPop-infected mosquitoes . Hence , we did not include the analysis for wMelPop strain of Wolbachia . This coefficient for effectiveness computed using Eq ( 7 ) listed in Table 7 shows that wMel is significantly more effective than wAlbB in reducing the number of infections in simulations with the baseline parameters in Table 2 .
A mosquito infected with the Wolbachia bacteria is less capable of transmitting DENV , ZIKV , and CHIKV , and one of the leading new mitigation strategies is to fight the spread of these viral infections by releasing Wolbachia-infected mosquitoes . We quantified the impact of wAlbB , wMel , and wMelPop strains of Wolbachia in reducing the transmission of CHIKV , DENV , and ZIKV . The model accounts for reduced fitness of the Wolbachia-infected mosquitoes , reduced ability of transmitting viruses , and the behavior changes of infected individuals caused by the infection . Because people infectious with DENV and CHIKV are more likely to have serious symptoms , we assumed that the people infectious with these viruses were less likely to be bitten by mosquitoes than the people infectious with ZIKV . The behavior changes of humans have significant impacts on the model predictions and , unfortunately , is often let out of most vector-borne disease models . The baseline model parameters are estimates for the general population and our best guess from the literature . The relative sensitivity indices for these parameters ( Table 5 ) can be used to predict how slightly different assumptions about these input parameters will change the basic reproduction number . The relative sensitivity analysis quantified the relative importance of the model parameters on the model predictions and can be used to quantify the importance of obtaining more accurate data to reduce the parameter uncertainty and improve the model’s predictability . Over the entire range of parameter values , our simulation results show that the R 0 for wMel-infected mosquitoes is the smallest . For Ae . aegypti , R 0 for ZIKV is the largest , followed by DENV , then CHIKV . In a similar analysis for Ae . albopictus , R 0 is the largest for ZIKV , followed by DENV , then CHIKV . This is in agreement with the analysis where we varied the parameters one at a time over their feasible range . Our simulation results show that the wMel strain is more effective in controlling these viruses than wAlbB strain in all of the situations we tested . We find that for the same mosquito densities , Ae . aegypti is more effective than Ae . albopictus in transmitting DENV and ZIKV , while the opposite is true for CHIKV . The results are based on the simulations with the parameter values available in current literature , which may vary for different locations at different times . Our model is a general model that can produce outputs for a specific location , once the data for the location are available to parameterize the model . Comparisons of the model predictions for Ae . aegypti versus Ae . albopictus must take into account the ratio of mosquitoes to humans . R 0 is sensitive to this ratio and the density of Ae . aegypti mosquitoes is typically higher in urban areas than in rural areas , while the opposite is true for Ae . albopictus mosquitoes [37] . When there are few mosquitoes per human , then R 0 < 1 . As the number of mosquitoes increases , then R 0 quickly increases to be greater than one . As the number of mosquitoes per human becomes very large , R 0 eventually decreases in our model where the number of times that humans allow themselves to be bitten is limited to a maximum number of times per day . The rate of decrease depends upon the specific biting rate in Eq ( 3 ) being used in the model . Although wMelPop-infected mosquitoes do not transmit these viruses , the increased death rate of wMelPop-infection has a high fitness cost . It is difficult for wMelPop-infected mosquitoes to survive in the wild mosquito populations because a much larger number of wMelPop-infected mosquitoes needs to be released in order to sustain in the wild mosquito population . The analysis of the basic reproduction number assumes that when the infections first enter a population , then everyone is fully susceptible to the infection . We derived the effective reproduction number for when the host population is partially immune to new infections , perhaps due to a previous epidemic . The effective reproduction number increases with the susceptibility of humans . When more people are immune to DENV and CHIKV than ZIKV , as happened in the 2015 Zika epidemic , then the numbers of dengue and Chikungunya cases tend to be stable , while the number of Zika cases exploded . Hence , the susceptibility of the human population must be taken into account in future seasonal outbreaks . Our analysis quantified how R e f f ( t ) depends upon a fraction of the population being immune to the infection in a vector-host transmission model . There are ongoing efforts for releasing Wolbachia-infected mosquitoes in the wild to fight against the spread of these viral infections . Wolbachia-infected mosquitoes could contribute to the reduction of transmission instead of elimination . Besides , the number of Wolbachia-infected mosquitoes released has to exceed the threshold and continual introductions are required . The real-world thresholds for sustaining an epidemic will be greater than the threshold estimates derived for ideal conditions where there is a homogenous population of infected and uninfected mosquitoes . These field tests suggest that the spatial heterogeneity of the populations must be considered before this model will be appropriate to help guide policy decisions . Also , our simulations are based on an environment of Wolbachia-infected mosquitoes where most of the wild mosquitoes are infected with Wolbachia . When introducing the wMel or wAlbB strains of Wolbachia into a wild mosquito population , it may take several weeks or months for it to reach the equilibrium level and may require several introductions [22] . Furthermore , the model parameter values are based on average estimates from the literature , and not the parameters for a specific location . Before this model can be applied to a specific location , then model parameters , such as the average number of mosquitoes per person , must be estimated for this location . In future studies , we will couple the model for the spread of Wolbachia [22] with the disease transmission model [23] to evaluate effectiveness of this approach for the situations where the mosquito population is only partially infected with Wolbachia and consider new human arrivals including people who are immune and infectious .
|
Mosquitoes infected with Wolbachia bacteria are less capable of transmitting dengue virus , Chikungunya virus , and Zika virus . We use a mathematical model to quantify the impact of infecting wild Aedes aegypti and Aedes albopictus mosquitoes with wAlbB and wMel strains of Wolbachia in reducing the transmission of these viruses . The model is a system of ordinary differential equations that accounts for reduced fitness of the Wolbachia-infected mosquitoes , reduced transmissibility of an infection , and the behavior changes of infected individuals caused by the infection . We derived an explicit formula for the effective reproduction number for when the host population are partially immune to new infections , as occurs in seasonal outbreaks . We compared the effectiveness of different species of mosquitoes , different strains of Wolbachia , and different diseases . Our model is a general model that can produce outputs for a specific location , once the data for the location are available to parameterize the model . The spatial heterogeneity of the populations must be considered before using this model to help guide policy decisions .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"death",
"rates",
"invertebrates",
"dengue",
"virus",
"medicine",
"and",
"health",
"sciences",
"pathology",
"and",
"laboratory",
"medicine",
"togaviruses",
"chikungunya",
"infection",
"pathogens",
"immunology",
"tropical",
"diseases",
"microbiology",
"animals",
"wolbachia",
"alphaviruses",
"viruses",
"infectious",
"disease",
"immunology",
"clinical",
"medicine",
"chikungunya",
"virus",
"rna",
"viruses",
"neglected",
"tropical",
"diseases",
"population",
"biology",
"insect",
"vectors",
"bacteria",
"infectious",
"diseases",
"medical",
"microbiology",
"microbial",
"pathogens",
"disease",
"vectors",
"insects",
"arthropoda",
"population",
"metrics",
"mosquitoes",
"eukaryota",
"flaviviruses",
"clinical",
"immunology",
"viral",
"pathogens",
"biology",
"and",
"life",
"sciences",
"species",
"interactions",
"viral",
"diseases",
"organisms",
"zika",
"virus"
] |
2018
|
Comparing the effectiveness of different strains of Wolbachia for controlling chikungunya, dengue fever, and zika
|
Recent improvements in technology have made DNA sequencing dramatically faster and more efficient than ever before . The new technologies produce highly accurate sequences , but one drawback is that the most efficient technology produces the shortest read lengths . Short-read sequencing has been applied successfully to resequence the human genome and those of other species but not to whole-genome sequencing of novel organisms . Here we describe the sequencing and assembly of a novel clinical isolate of Pseudomonas aeruginosa , strain PAb1 , using very short read technology . From 8 , 627 , 900 reads , each 33 nucleotides in length , we assembled the genome into one scaffold of 76 ordered contiguous sequences containing 6 , 290 , 005 nucleotides , including one contig spanning 512 , 638 nucleotides , plus an additional 436 unordered contigs containing 416 , 897 nucleotides . Our method includes a novel gene-boosting algorithm that uses amino acid sequences from predicted proteins to build a better assembly . This study demonstrates the feasibility of very short read sequencing for the sequencing of bacterial genomes , particularly those for which a related species has been sequenced previously , and expands the potential application of this new technology to most known prokaryotic species .
We generated 8 , 627 , 900 random shotgun reads from P . aeruginosa PAb1 using Solexa technology . All reads were exactly 33 bp in length . We used four distinct computational steps to assemble the genome of PAb1 . For the initial step , we used the comparative assembly algorithm AMOScmp [21] , which aligns all reads to a reference genome , and then builds contigs based on these alignments . The algorithm gains efficiency by avoiding the costly all-versus-all overlapping step , which is particularly difficult with very short reads due to the high incidence of false overlaps [13] . We modified AMOSCmp by tuning the MUMmer software [22] , which is run within AMOScmp , to look for exact matches to the reference genome of at least 17 bp , allowing at most two mismatches in each read . We found that careful trimming of the reads based on their matches to the reference produced better assemblies than un-trimmed reads . The initial assembly used 7 , 500 , 501 reads , leaving 1 , 127 , 399 as singletons ( Table 1 ) . The PAb1 genome is closer to PA14 ( 99 . 4% identical for 92% of the PAb1 genome ) than to PAO1 ( 99 . 0% identical for 90% of the PAb1 genome ) , and we therefore used PA14 as the primary reference for orienting the contigs . Our second step was a novel enhancement to the comparative assembly strategy , in which we used multiple reference genomes ( Figure 1 ) . We used the complete genomes of both PAO1 [19] and PA14 [20] separately to build multiple comparative assemblies , and found that PA14 produced the better assembly , comprising 2 , 053 contigs containing 6 , 206 , 284 bp . ( We also used the PA7 strain , but its greater evolutionary distance made it less useful . ) The bulk of the sequence was contained in 157 contigs longer than 10 Kbp , which collectively covered 5 , 568 , 616 bp . There were 331 , 364 bp in the PA14 genome that were not covered by the initial assembly , due to divergence between the two strains . However , the gaps in the comparative assembly based on PAO1 occurred in different locations due to differences between the strains . The best assembly based on PAO1 comprised 2797 contigs covering 6 , 043 , 652 bp . We aligned the two assemblies to one another to identify locations where a contig in the PAO1-based assembly might span two or more contigs in the PA14-based assembly ( Figure 1 ) . For each such case , we filled the gap with the sequence from the PAO1 assembly using the Minimus assembler [23] to stitch together the contigs . This algorithm closed 203 gaps , reducing the number of contigs to 1850 , of which all but 305 were <200 bp . The bulk of the genome , 5 , 949 , 162 bp , was contained in just 113 contigs of 10 , 000 bp or longer . Note that the overlapping contigs between the two assemblies did not agree perfectly . In order to produce a clean merged assembly , we re-mapped the reads to the contigs using AMOScmp to create consistent multi-alignments . The third step used a novel algorithm , gene-boosted assembly . For this step , we took the contigs from the previous step and identified protein-coding genes using our annotation pipeline , which is based on Glimmer [24] and Blast [25] . Because amino acid sequences are much more conserved than nucleotide sequences , we were able to use the predicted protein sequences ( primarily but not exclusively from other Pseudomonas species ) to fill gaps even where the DNA sequences diverged . The annotation pipeline identified 5 , 769 proteins in the 305 longest contigs . From the initial annotation , we identified those genes that extended beyond the ends of contigs or that spanned the gaps between contigs . We extracted the amino acid sequences corresponding to these gap positions , with a small buffer sequence included on each side of each gap . Next we used tblastn [25] to align each protein sequence to all the unused reads translated in all 6 frames ( Figure 2 ) . This step identified , for each gap , a small set of reads that would fill in the missing protein sequence , and the tblastn results provided initial locations for a multiple alignment . We then used a new program , ABBA ( Assembly Boosted By Amino acids ) , to assemble the reads together with the flanking contigs and close the gaps . This gene-boosted assembly protocol extended many contigs and closed 185 gaps , ranging in length from 14–1095 bp , reducing the number of long contigs to 120 . As a separate test , we conducted a gene-boosted assembly of PAb1 using only the annotated proteins from PA14—without any reference genomic sequence . For this experiment , we aligned all the translated reads to each protein and used ABBA to assemble each one . For 4 , 572 of the proteins , ABBA produced a single contig that covered the entire reference protein , and another 831 proteins assembled into a few contigs . Thus 5 , 403 out of 5 , 602 ( 96% ) of the PAb1 proteins can be assembled using a pure gene-boosting approach , and additional proteins would likely be assembled if we used a large set of proteins for boosting . This demonstrates that in the absence of a closely related genome sequence , gene-boosted assembly can use protein sequences—which diverge much more slowly than genomic DNA—to assemble most of the genes of a new bacterial strain , although the results will lack global genome structure information . The fourth step of our method identified any remaining DNA sequences that were ( a ) unique to PAb1 and ( b ) outside predicted gene regions . We separately constructed pure de novo assemblies of the 8 . 6 million Solexa reads using SSAKE , Edena , and Velvet . The Velvet assembly was the best of the three , creating 10 , 684 contigs , the longest being 16 , 239 bp ( Table 1 ) . We used MUMmer to align these contigs to the 120 long contigs in our scaffold from the previous step , and identified cases where de novo contigs spanned gaps or extended contigs . This step allowed us to close 46 gaps , reducing the number of contigs in our main scaffold to 74 . After removing Velvet contigs that were already contained in our scaffold , we had 436 unplaced de novo contigs spanning 416 , 897 bp . The longest unplaced contig was 10 , 493 bp .
Our final assembly contains one large scaffold with 76 contigs whose total length is 6 , 290 , 005 bp , with the longest contig at 512 , 638 bp . The 436 unplaced contigs , which should fit into the remaining gaps , represent sequence that is unique to PAb1 . Our annotation shows that most of these contigs contain genes that are homologous to other Pseudomonas species . Several contigs contain bacteriophage genes , pointing to recent phage insertion events in PAb1 . The final assembly thus consists of 512 contigs covering 6 , 706 , 902 bp , with 94% of the bases in a single large scaffold . Approximately 9% of the reads were not used in the assembly ( Table 1 ) ; many of these can be mapped to contigs if we use relaxed matching criteria , indicating that they represent low-quality data . Our annotation of the PAb1 genome identified 5 , 602 protein-coding genes , as compared to 5 , 568 for PAO1 and 5 , 892 for PA14 . All Solexa reads have been deposited in the Short Read Archive at NCBI , and the final genome sequence and annotation have been deposited in GenBank as sccession ABKZ01000000 . We have demonstrated that it is possible to sequence and assemble a bacterial genome from deep sequencing using 33 bp reads . The final assembly has 40 . 3× coverage , with very high agreement among the individual reads at the vast majority of positions in the genome . To measure the accuracy of individual reads , we examined all positions in the assembly with >20× coverage , which yielded 5 . 9 million positions . If we count as errors any bases that disagree with the consensus at those positions , we get an estimate based on internal consistency that the error rate per read is 1 . 04% . Based on this estimate , the expected number of errors for regions of the genome with coverage of >20× is close to zero , except for systematic errors such as difficult-to-sequence regions . This illustrates how the great depth of sequencing possible with short-read technology produces higher quality assemblies—in regions with deep coverage—than would conventional Sanger sequencing at a typical 8× coverage depth . We evaluated the coverage to determine if the Solexa sequences were biased towards any portion of the genome , and found a small bias towards high-GC regions , which comprise most of the genome . In particular , regions with 60–70% GC , which comprised 79% of the genome , had 40× coverage . In contrast , regions with 50–55% GC ( 1 . 5% of the genome ) had 14× coverage , and regions with <50% GC ( 1 . 1% of the genome ) had just 5× coverage . The alignment of P . aeruginosa PAb1 to strain PA14 , which matches at 99 . 4% identity for >90% of the genome , can be used to provide an estimate of the sequencing accuracy . To assess the question of whether differences between our assembly and the PA14 genome represented true differences or sequencing errors , we aligned the two genomes and identified all single nucleotide polymorphisms ( SNPs ) . Out of 5 , 568 , 550 aligned bases from the longer PAb1 contigs , 5 , 537 , 508 agreed with PA14 and can be presumed correct . For each of the remaining 31 , 042 SNPs , we examined all reads that were assembled at that point and assessed whether ( a ) the depth of coverage was adequate , and ( b ) the PAb1 reads agreed on the consensus base . The coverage was 10-fold or greater for 95% of these SNPs . Using the conservative assumption that a SNP might be in error if the inter-read agreement was less than 80% , we found 1157 positions ( out of 5 , 568 , 550 ) that might be sequencing errors . We also found 1104 insertions and deletions ( indels ) in the aligned regions , and our assembled reads were in perfect agreement for 917 of these . If we assume conservatively that the other 187 indels are errors , then considering both SNPs and indels , the accuracy of the assembled genome is greater than 99 . 97% . The assembly is sufficiently complete that we can confidently infer that genes are missing if their expected positions fall in the midst of contigs . Although deeper analysis will be presented in a followup paper , we note that the PAb1 strain is known for its hypermotility on low percentage agar media . Our sequence contains most of the genes required for swimming motility in P . aeruginosa [26] , but is missing part of the pathway used by cyclic-di-GMP , a secondary signaling molecule , that has been implicated in repressing swimming motility [27] , [28] . By searching all of the known P . aeruginosa genes in this pathway [29] , [30] , [31] , we found that three genes encoding diguanylate cylase and phosphodiesterase are missing: PA2771 and PA2818 ( arr ) from the PAO1 strain , and PA14_59790 ( pvrR ) from the PA14 strain [32] , [33] . All three of these genes are located in chromosomal regions previously indicated as hyper-variable based on genomic hybridizations [29] . The altered gene content of PAb1 in the regulatory pathways repressing flagella may contribute to its observed hypermotility . The new algorithm described here make it possible for any scientist to acquire the entire genome of a bacterium at high speed and very low cost . One limitation of our method is that it depends on the existence of related genomes ( for the comparative assembly step ) and protein sequences ( for the gene boosting step ) . However , GenBank already contains the complete genome sequences for >650 microbial genomes , and draft sequences for nearly 1000 more . For many of these species , much larger numbers of related strains and species have yet to be sequenced . Our method opens the door to the use of whole-genome sequencing to study entire collections of bacteria , to rapidly identify genotypes from mutagenized genetic screens , and for other analyses that were previously too costly or technically infeasible . The gene-boosted assembly technique applies equally well to both short and long-read sequencing methods , and should also work for assembling the gene-containing regions of much larger genomes .
Genomic DNA was extracted by SDS lysis , proteinase K digest , and phenol/chloroform extraction . Sequencing was performed by Illumina using the 1G Genome Analyzer , also known as the Solexa sequencer . The 8 . 6 million reads represent 1/4 of the current capacity of a flow cell . For sequencing trimming in step 1 , we mapped all reads to the initial assembly and then trimmed up to three bases from the 3′ end when those bases failed to match a contig . The AMOScmp pipeline for trimming and short read assembly is described at http://cbcb . umd . edu/research/SR-assembly . shtml . Contig merging in step 2 of our algorithm used the merger program from the EMBOSS package [34] . The Edena , Velvet , and ssake assemblers were run with a wide range of parameters in order to optimize them for the data used in this study , with the best results coming from Velvet with a minimum overlap requirement of 24 bases . ( The other methods created more numerous , shorter contigs . ) The ABBA assembler has been added to the free , open-source AMOS assembler package , which also includes the AMOScmp assembler . ABBA can be found at http://amos . sourceforge . net/docs/pipeline/abba . html . AMOS and additional modules developed in this study are freely available from http://cbcb . umd . edu/software , and the MUMmer system is freely available at http://mummer . sourceforge . net .
|
In this paper we demonstrate that a bacterial genome , Pseudomonas aeruginosa , can be decoded using very short DNA sequences , namely , those produced by the newest generation of DNA sequencers such as the Solexa sequencer from Illumina . Our method includes a novel algorithm that uses the protein sequences from other species to assist the assembly of the new genome . This algorithm breaks up the genome into gene-sized chunks that can be put back together relatively easily , even from sequence fragments as short as 30 bases of DNA . We also take advantage of the genomes of related species , using them as reference strains to assist the assembly . By combining these and other techniques , we were able to assemble 94% of the 6 . 7 million bases of P . aeruginosa into just 76 large pieces . The remaining 6% is contained in 436 smaller fragments . We have made all of our software available for free under open-source licenses , and we have deposited the newly assembled genome in the public GenBank database .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] |
[
"genetics",
"and",
"genomics/comparative",
"genomics",
"computational",
"biology/comparative",
"sequence",
"analysis",
"genetics",
"and",
"genomics/genome",
"projects",
"computational",
"biology/genomics",
"genetics",
"and",
"genomics/bioinformatics"
] |
2008
|
Gene-Boosted Assembly of a Novel Bacterial Genome from Very Short Reads
|
The binding of bacteria to human platelets is a likely central mechanism in the pathogenesis of infective endocarditis . We have previously found that platelet binding by Streptococcus mitis SF100 is mediated by surface components encoded by a lysogenic bacteriophage , SM1 . We now demonstrate that SM1-encoded lysin contributes to platelet binding via its direct interaction with fibrinogen . Far Western blotting of platelets revealed that fibrinogen was the major membrane-associated protein bound by lysin . Analysis of lysin binding with purified fibrinogen in vitro confirmed that these proteins could bind directly , and that this interaction was both saturable and inhibitable . Lysin bound both the Aα and Bβ chains of fibrinogen , but not the γ subunit . Binding of lysin to the Bβ chain was further localized to a region within the fibrinogen D fragment . Disruption of the SF100 lysin gene resulted in an 83±3 . 1% reduction ( mean ± SD ) in binding to immobilized fibrinogen by this mutant strain ( PS1006 ) . Preincubation of this isogenic mutant with purified lysin restored fibrinogen binding to wild type levels . When tested in a co-infection model of endocarditis , loss of lysin expression resulted in a significant reduction in virulence , as measured by achievable bacterial densities ( CFU/g ) within vegetations , kidneys , and spleens . These results indicate that bacteriophage-encoded lysin is a multifunctional protein , representing a new class of fibrinogen-binding proteins . Lysin appears to be cell wall-associated through its interaction with choline . Once on the bacterial surface , lysin can bind fibrinogen directly , which appears to be an important interaction for the pathogenesis of endocarditis .
The pathogenesis of infective endocarditis is a complex process , involving numerous host-pathogen interactions [1] , [2] . A key interaction for disease establishment and progression is the binding of microbes to human components , including platelets , fibrinogen , fibrin , and fibronectin [3] , [4] , [5] , [6] , [7] , [8] . Although this binding appears to be a central requirement for virulence , only a limited number of endocarditis-related adhesins has been identified [7] , [8] , [9] . Among the viridans group streptococci , Streptococcus mitis is a leading cause of endovascular infection [10] , [11] , [12] , [13] , [14] . Despite its increasing importance as a human pathogen , relatively little is known about the virulence determinants of this organism , particularly with regard to its interaction with platelets or other host components . Our previous studies identified two surface proteins ( PblA and PblB ) encoded by a lysogenic bacteriophage ( SM1 ) that mediate the binding of S . mitis to human platelets , through their interaction with the membrane ganglioside GD3 [15] , [16] , [17] . Disruption of the genes encoding PblA and PblB results in a significant decrease in platelet binding in vitro , as well as a marked reduction in virulence , as measured by an animal model of endocarditis [16] , [17] . Expression of these proteins on the bacterial surface is dependent upon the activities of phage holin and lysin , which permeabilize the cell envelope , thereby permitting the transport of PblA and PblB to the cell wall , where they attach to phosphocholine ( PC ) residues [16] . Of note , disruption of the gene encoding lysin ( lys ) resulted in a profound reduction in platelet binding , to levels that were significantly lower than those seen with either the parent strain , or a pblA/plbB double knock-out mutant [16] . These findings suggested that lysin mediates platelet binding in part through a mechanism independent of its role in the export of PblA and PblB . For these reasons , we investigated the mechanisms by which lysin mediates binding to platelets , and whether this interaction contributes to the pathogenesis of streptococcal endocarditis . Our studies indicate that phage lysin can be localized on the bacterial surface through its interaction with PC residues . Surface-bound lysin can subsequently bind both free and platelet-associated fibrinogen , through its specific interaction with the Aα and Bβ chains of the protein . Loss of lysin expression is associated with reduced virulence in the setting of endocarditis , indicating that the binding of lysin to fibrinogen is an important factor in the pathogenesis of this infection .
Using the NCBI Conserved Domain Database ( CDD ) search system [18] , bioinformatic analysis of the predicted amino acid sequence of lysinSM1 ( Accession number Q9AF60 ) , revealed that an amidase-5 domain ( Pfam05382; amino acids 4–146 ) is present at the amino terminus , and a putative choline-binding domain is found at the carboxyl terminus ( COG5263; amino acids 128–271; Fig . 1 ) . The N-terminal domain of lysinSM1 ( N-lysinSM1 ) exhibits 75% amino acid identity to the Pal lysin ( accession number O03979 ) of the pneumococcal bacteriophage Dp-1 , and 74% identity to the lysin ( accession number Q8E0W3 ) of the prophage lambdaSa1 of Streptococcus agalactiae [19] , [20] . The C terminus of lysinSM1 ( C-lysinSM1 ) contains a choline-binding domain homologous to that found in the pneumococcal LytA autolytic enzyme ( 62% identity ) , which anchors the protein to PC residues present in LTA or teichoic acids [19] . To assess whether lysinSMl demonstrated its predicted biological activities , we first examined its binding to DEAE-cellulose , a property that is a hallmark of choline-binding proteins [21] . LysinSM1 , N-lysinSM1 , and C-lysinSM1 were expressed individually in Escherichia coli , and lysates from these strains were applied to a DEAE-cellulose column [16] . N-lysinSM1 failed to bind the matrix , with the protein being detected in the wash volumes ( Fig . 2A ) . In contrast , lysinSM1 and C-lysinSM1 were only eluted with ™ buffer containing 2% choline chloride . Thus , lysinSM1 appears to be a choline-binding protein , with this interaction being mediated by the C terminus . We then examined whether purified lysinSM1 bound directly to PC residues of LTA purified from S . pneumoniae HS0001 and S . mitis SF100 . Purified FLAGlysinSM1 was incubated with immobilized LTAs , and binding was assessed by ELISA with anti-FLAG antibody . As shown in Fig . 2B , lysinSM1 bound LTA from S . mitis SF100 and from S . pneumoniae HS0001 , both of which contain PC . Of note , binding levels of lysinSM1 to these LTAs were comparable and concentration-dependent . In contrast , little or no binding to LTA was detected from strain HS0001-EA , which has no PC . C-lysinSM1 also bound LTA from SF100 and HS0001 , whereas N-lysinSM1 did not ( Figure S1 ) . These results confirm that lysinSM1 interacts with the PC residues of LTA , and that binding is mediated by the predicted choline-binding domain within the C terminus . As mentioned above , analysis of the predicted amino terminus of lysinSM1 indicated that it encodes an amidase with g-D-glutaminyl-L-lysin endopeptidase activity [20] . To assess its lytic activity , we tested the bactericidal properties of lysinSM1 in vitro ( Fig . 2C ) . When compared with organisms treated with buffer alone , exposure of S . pneumoniae HS0001 to lysinSM1 resulted in a mean ( ± S . D . ) reduction of 5 . 07±1 . 28 log10 CFU per ml ( P<0 . 05 ) . LysinSM1 was also active against the SM1 host strain SF100 and its isogenic variant , PS1006 , though it only reduced mean titers by 0 . 8±0 . 04 ( P<0 . 05 ) and 1 . 65±0 . 21 log10 CFU per ml ( P<0 . 05 ) , respectively . No bactericidal activity was seen when tested against Staphylococcus aureus , Streptococcus sanguinis , Streptococcus pyogenes , or E . coli . Of note , neither purified N-lysinSM1 nor C-lysinSM1 had bactericidal activity against strains HS0001 or SF100 ( data not shown ) . Thus , lysinSM1 has lytic activity against PC positive strains , such as S . mitis and S . pneumoniae , though the latter species is considerably more sensitive to the enzyme . Moreover , lysinSM1 requires its choline-binding domain , in addition to its predicted amidase domain , for this activity . We have previously observed that disruption of the gene encoding lysinSM1 resulted in a significant reduction in platelet binding by S . mitis [16] . To assess whether lysinSM1 could interact directly with human platelets , we evaluated the binding of FLAGlysinSM1 to immobilized human platelets and to isolated platelet membranes ( Fig . 3A ) . FLAGlysinSM1 was incubated with platelet monolayers or platelet membranes , and bound FLAGlysinSM1 was then detected with anti-FLAG antibody . When tested by this approach , we found that FLAGlysinSM1 strongly interacted with both whole platelets and platelet membranes in a concentration-dependent manner . In contrast , no binding of FLAGlysinSM1was seen to wells coated with only a casein-based blocking reagent ( Western Blocking Reagent; Roche ) . To identify the membrane receptor for lysinSM1 , we assessed by far Western blotting the binding of FLAGlysinSM1 to platelet membranes that had undergone SDS-PAGE and transfer to nitrocellulose ( Fig . 3B ) . Although the platelet membrane extracts contained numerous proteins , ranging in mass from 50 to 250 kDa , FLAGlysinSM1 bound only a small number of proteins . The highest levels of binding were seen with two proteins of MW 65 kDa and 55 kDa , which were similar to the molecular masses of the Aα and Bβ chains of human fibrinogen ( 64 and 56 kDa ) , respectively . To confirm that platelet membrane extracts contained fibrinogen , the preparations were probed with antibodies directed against the three major chains of fibrinogen ( Aα , Bβ and γ ) . As shown Fig . 3B , each subunit of fibrinogen was present in the membrane extracts . To directly confirm that lysinSM1 bound fibrinogen on platelet membranes , we assessed whether lysinSM1 binding to immobilized platelet membranes was inhibited by anti-human fibrinogen IgG . As shown in Fig . 3C , pre-treatment of membranes with 30 or 100 µg/ml of anti-fibrinogen antibodies significantly reduced subsequent lysin binding . These results further indicate that fibrinogen is the principal component on platelet membranes and that lysinSM1 is bound to platelet membranes through it interaction with fibrinogen . Since fibrinogen is a key factor in the pathogenesis of infective endocarditis , and because it is a receptor for some bacterial adhesins [7] , [22] , [23] , [24] , [25] , [26] , we further investigated the interaction of this protein with lysinSM1 . We first assessed the binding of the increasing concentrations of FLAGlysinSM1 to human fibrinogen ( 3 µg/ml ) immobilized in microtiter wells . In control studies , no significant binding of fibrinogen by FLAG-tagged alkaline phosphatase ( FLAGAP ) was detected ( Figure S2 ) . In contrast , FLAGlysinSM1 showed significant binding to immobilized fibrinogen , which increased in direct proportion to the amount of protein applied ( Fig . 4A ) . At concentrations above 125 µg/ml FLAGlysinSM1 , binding reached a plateau , indicating that it was saturated . In addition , the binding of FLAGlysinSM1 to immobilized fibrinogen was effectively blocked by both unlabeled lysinSM1 and fibrinogen ( Fig . 4B ) . Similar levels of lysin binding were seen with rat fibrinogen , the host used for our subsequent virulence assays ( Figure S3 ) . For some bacteria , binding to fibrinogen is dependent on whether the protein is in solution or immobilized on a surface . For example , Group A and G streptococci can bind both soluble and immobilized forms of fibrinogen , whereas several oral streptococci appear to bind only immobilized fibrinogen [27] , [28] , [29] . To assess whether fibrinogen binding by lysinSM1 was phase-dependent , we reversed the binding conditions , such that FLAGlysinSM1 , untagged lysinSM1 , and FLAGAP ( all at 10 µg/ml ) were immobilized in microtiter wells , and probed with the increasing concentration of fibrinogen in solution . Under these conditions , fibrinogen was still found to bind lysinSM1 and FLAGlysinSM1 comparably , whereas no significant binding to FLAGAP was detected ( Fig . 4C ) . As noted above , we found that lysinSM1 bound two proteins associated with platelet membranes that corresponded to the Aα and Bβ chains of fibrinogen . To confirm that lysinSM1 binds specifically to these subunits , we assessed by far Western blotting the interaction of lysinSM1 with purified human fibrinogen ( Fig . 4D ) . When separated by SDS-PAGE under reducing conditions , fibrinogen appeared as three bands , having the expected masses . When transferred to nitrocellulose and probed with FLAGlysinSM1 , binding could be detected to the Aα and Bβ chains only , confirming the results seen with platelet membranes . The fibrinogen molecule is comprised of two subunits , each containing three polypeptide chains ( Aα , Bβ , and γ; Fig . 5A ) . Cleavage of fibrinogen with plasmin produces a series of fragments , most notably the E fragment containing the central part of the molecule , and the D fragment containing the terminal regions . To further identify the domains of fibrinogen bound by lysinSM1 , we examined the interaction of FLAGlysinSM1 to the D and E fragments . When assessed by ELISA , FLAGlysinSM1 showed high levels of binding to immobilized fragment D , which were comparable to those seen with whole fibrinogen ( Fig . 5B ) . In contrast , no significant binding to the E fragment was seen . Purified fibrinogen fragment D contains three subunits , each representing a part of the three major chains ( α chain fragment = 15 kDa , β chain fragment = 44 . 5 kDa , and γ chain fragment = 42 kDa ) ( Fig . 5A ) . To further identify the subdomains of fibrinogen bound by lysinSM1 , purified fragment D was separated under reducing conditions and transferred to a nitrocellulose membrane . When assessed by far Western blotting , binding by FLAGlysinSM1 , was limited to the Bβ chain component of fragment D with no binding detected to the Aα chain ( Fig . 5C ) . These data indicate lysinSM1 binds a region contained within AA 134–461 of the Bβ chain . Of note , lysinSM1 bound the full-length Aα chain ( Fig . 3B ) , but not its D or E fragments ( Fig . 5C ) , suggesting that the lysinSM1 binding to the Aαchain requires the C terminus ( AA 197–610 ) . To assess the impact of lysin expression on bacterial binding to fibrinogen , we compared the adherence of SF100 ( WT ) and PS1006 ( Δlysin ) to fibrinogen immobilized in microtiter wells . As shown in Fig . 6A , SF100 had high levels of binding to immobilized fibrinogen , which increased in proportion to the amount of fibrinogen in the wells . PS1006 showed markedly reduced levels of binding , as compared with the parent strain . For example , when tested with wells coated with 30 µg/ml of fibrinogen , PS1006 had only 18 . 8±4 . 7% ( mean ± SD ) of maximal binding , as compared with 89 . 7±12 . 8% for SF100 ( P<0 . 05 , unpaired t-test ) . Complementation of the lysin mutation in trans restored fibrinogen binding by PS1006 ( Fig . 6B ) , thereby demonstrating that the loss of binding observed with lysin disruption was not due to polar or pleiotropic effects . The above results suggested that the binding to immobilized fibrinogen by SF100 is mediated by lysinSM1 expressed on the bacterial surface . To confirm that lysin was sufficient to mediate fibrinogen binding , we next examined whether exogenous lysinSM1 could attach to the cell wall of PS1006 and restore binding . The PC-negative strain SK598 served as a negative control . Each strain was incubated with purified FLAGlysinSM1 at RT for 30 min . After washing to remove nonspecifically bound protein , cell wall bound FLAGlysinSM1 was extracted with 2% choline , and the amount of FLAGlysinSM1 recovered was assessed by Western blotting . As shown in Fig . 6C , exogenous FLAGlysinSM1 could readily be detected in the cell wall extracts of PS1006 , whereas no binding of FLAGlysinSM1was observed with SK598 . We then assessed whether this interaction was sufficient to enhance the binding of PS1006 to fibrinogen ( Fig . 6D ) . PS1006 was suspended in PBS containing a range of concentrations of purified lysinSM1 and then tested for its binding to immobilized fibrinogen , as described above . As expected , PS1006 incubated in PBS alone showed minimal levels of binding to fibrinogen . This was not due to a loss of PblA and PblB expression , since the pblA/pblB negative strain PS344 had levels of fibrinogen binding that were similar to those of the parent strain . Exposure of PS1006 to FLAGlysinSM1 increased fibrinogen binding in a concentration-dependent manner . Indeed , 10 µg per ml of FLAGlysinSM1 was sufficient to restore PS1006 binding to levels comparable to those seen with SF100 . To assess the impact of lysinSM1 on pathogenesis , we compared the relative virulence of SF100 , PS344 and PS1006 in a rat co-infection model of infective endocarditis [16] , [55] . We first compared SF100 with PS344 to confirm previous results obtained in a rabbit model of infection [16] . As was observed with rabbits , disruption of pblA and pblB was also associated with attenuated virulence in rats , with PS344 having significantly reduced levels of bacteria within all tissues ( Table 1 ) . Disruption of lysinSM1 also produced a significant reduction in virulence . Rats co-infected with SF100 and PS1006 had significantly lower densities of the lysin mutant strain in vegetations ( mean ± SD = 5 . 07±1 . 50 log10 CFU/g ) as compared with the parent strain ( 6 . 91±1 . 35 log10 CFU/g; n = 8 , P = 0 . 009 ) . Densities of PS1006 were also significantly reduced in kidneys ( P = 0 . 008 ) and spleens ( P<0 . 001 ) as compared with SF100 . We then examined the relative impact on virulence of abrogated PblA and PblB expression , versus loss of lysin ( Table 1 ) . In animals co-infected with PS344 and PS1006 , titers of the latter mutant were significantly reduced in all tissues examined , as compared with the former . In particular , the mean densities of PS1006 within vegetations ( 6 . 59±1 . 45 log10 CFU/g ) were significantly lower than those of PS344 ( 8 . 32±0 . 76; n = 8; P = 0 . 008 ) , as were densities within kidneys ( P = 0 . 027 ) and spleens ( P = 0 . 006 ) . We then re-analyzed these data by comparing the ratio of PS344 to PS1006 within tissues , with the CFU of each strain normalized to the number of CFU within the inoculum ( competition index ) ( Figure S4 ) . When assessed by this approach , the levels of the lysinSM1 mutant PS1006 remained significantly reduced in all tissues , as compared with PS344 . Thus , lysinSM1 appears to be a significant virulence determinant in the setting of infective endocarditis . Moreover , its role in pathogenesis is not due solely to any effect it may have on PblA and PblB expression . Instead , it appears to have an impact upon the development of infective endocarditis independent of these other phage-encoded proteins .
The binding of pathogenic bacteria to platelets is thought to play a key role in the pathogenesis of infective endocarditis . This interaction may be important both for the initial attachment of bacteria to the endocardial surface , and for the subsequent formation of vegetations . Numerous endocarditis-associated pathogens have been shown to bind platelets directly in vitro , through a variety of mechanisms [3] , [4] , [7] , [8] , [25] , [30] . The ability to bind platelets in vitro has been linked to virulence for several of the most common endocarditis-associated species , including Staphylococcus aureus , Streptococcus gordonii , and Streptococcus sanguinis [5] , [31] , [32] , [33] . Previous work from our laboratory has shown that platelet binding by S . mitis strain SF100 is mediated in part by two proteins ( PblA and PblB ) encoded by the lysogenic bacteriophage SM1 [16] . The functional localization of these proteins to the cell surface requires the phage lysin ( lysinSM1 ) , which permeabilizes the host organism , thereby permitting the transport of PblA and PblB from the cytoplasm to the bacterial surface , and their subsequent attachment to the cell wall [16] . During the course of these studies , we noted that disruption of the gene encoding lysinSM1 reduced platelet binding in vitro more profoundly than the loss of PblA and PblB localization , indicating that lysin had a role in platelet binding beyond facilitating PblA and PblB transport . It was unknown , however , whether lysin itself could directly mediate binding , or rather , the effects of lysin on bacterial permeability led to the surface expression of other proteins ( either phage or bacterial ) that could enhance platelet binding . Our current results demonstrate that lysin can bind human platelets directly through its interaction with fibrinogen . Purified lysin was found to bind fibrinogen , regardless of whether the proteins were in solution or immobilized . The binding of lysin with fibrinogen also was saturable , consistent with a receptor-ligand interaction . Lysin binding was restricted to the D fragment of the Aα and Aβ chains , further indicating that this is a specific process . This interaction appears to be important for the binding of S . mitis to fibrinogen , since disruption of the gene encoding lysin markedly reduced fibrinogen binding by bacteria in vitro . The addition of exogenous purified lysin to these mutants restored binding to WT levels , confirming that lysin can directly mediate the interaction of S . mitis with fibrinogen . A number of other bacterial proteins have been shown to bind fibrinogen , including the M protein and serum opacity factor of Streptococcus pyogenes , FbsA of Streptococcus agalactiae , SdrG of Staphylococcus epidermidis , and several proteins of Staphylococcus aureus ( clumping factors A and B , fibronectin binding protein A ) [4] , [22] , [25] , [30] , [34] . However , none of these proteins exhibit any primary sequence homology with lysinSM1 . The staphylococcal autolysins Aaa and Aae do resemble lysinSM1 , in that they appear to have both enzymatic and fibrinogen binding activities in vitro [35] , [36] . A search against the SMART and Pfam databases indicates that collectively these proteins belong to the NlpC/P60 superfamily of proteins , containing their catalytic domain that are characteristic of this group of proteins . However , the predicted catalytic activity of lysinSM1 ( amidase 5 ) is different from that autolysins Aaa and Aae . LysinSM1 has no sequence similarity to either the Aaa or Aae protein , and unlike these other proteins , it is a choline-binding protein . Thus , lysin appears to be a multi-functional protein that can mediate S . mitis binding to fibrinogen , in addition to its role in the transit of the PblA and PblB proteins to the cell surface . LysinSM1 was also associated with increased virulence in a rat model of infective endocarditis . When animals were co-infected with the parent strain SF100 and the lysinSM1 mutant PS1006 , densities of the lysin mutant were significantly reduced within vegetations , kidneys , and spleens , as compared with the parent strain . Moreover , the virulence of PS1006 was also attenuated , when compared with its pblA and pblB-deficient isogenic variant , PS344 . These results indicate that , beyond its importance for PblA and PblB expression , lysin contributes to virulence through a mechanism beyond its role in the transport of these bacteriophage-encoded adhesins . It is possible that there are other , unrecognized phage-encoded virulence factors that require lysin for export or localization . However , in view of the ability of lysin to bind fibrinogen directly ( both human and rat ) , and that fibrinogen binding has been associated with virulence for several other adhesins [37] , [38] , [39] , [40] , [41] , it is likely that this interaction of lysin with fibrinogen contributes to the pathogenesis of infective endocarditis by S . mitis . Given that lysin-fibrinogen binding enhances bacterial adherence to platelets in vitro , and that bacterium-platelet binding has been linked to virulence , it is likely that lysin-mediated binding to platelets via fibrinogen is an important pathogenetic interaction . However , it is also possible that lysin mediates streptococcal binding to fibrinogen on other surfaces , such as damaged endothelium . Finally , it is conceivable that lysin contributes to virulence through other , as yet unidentified interactions . In summary , lysin is a novel fibrinogen-binding protein encoded by a lysogenic bacteriophage of S . mitis . In addition to its expected role in cell wall degradation , lysin also appears to be an adhesin mediating the attachment of this organism to human platelets , through its interaction with cell wall PC , fibrinogen , and the platelet membrane receptor for fibrinogen , glycoprotein IIb/IIIa ( Fig . 7 ) . Lysin also appears to contribute significantly to virulence , which could explain the persistence of certain bacteriophages within their host organisms . Although induction of the phage lytic cycle extracts a toll on host viability , in vivo this may be more than offset by the enhanced virulence resulting from lysin expression . Since fibrinogen is also present within gingival crevicular fluid , lysin-fibrinogen binding may also contribute to the colonization of oral surfaces by S . mitis [42] , [43] . Although we do not know the exact prevalence of lysinSM1 homologs in other organisms , recent studies of S . pneumoniae and Enterococcus faecalis indicate that lysogenic bacteriophages encoding homologs of PblA and PblB are often present within these species [44] , [45] . Since lysins are required for the phage life cycle , these findings suggest that homologs of lysinSM1 may also be encoded by such prophages . If so , then lysin binding to fibrinogen could prove to be an important interaction for a range of Gram-positive pathogens .
Blood was obtained from healthy human volunteers , using a protocol approved by the Committee on Human Research at the University of California , San Francisco . All human studies were conducted according to the principles expressed in the Declaration of Helsinki . Written informed consent was obtained from all study participants prior to their participation . All procedures involving rats were approved by the Los Angeles Biomedical Research Institute animal use and care committee , following the National Institutes of Health guidelines for animal housing and care . N terminal Met-FLAG-alkaline phosphatase ( FLAGAP ) and purified rat fibrinogen were purchased from Sigma-Aldrich . Purified human fibrinogen and the fibrinogen fragment D and E ( produced by cleavage of fibrinogen with plasmin ) were obtained from Haematologic Technologies . Rabbit anti-human fibrinogen polyclonal IgG was purchased from Innovative Research . Genomic DNA was isolated from SF100 , using Wizard Genomic DNA purification kits ( Promega ) , according to the manufacturer's instructions . Polymerase chain reaction ( PCR ) was performed with the primers listed in Table S2 . To clone lys gene into E . coli expression vector , PCR products were purified , digested , and ligated into pET28FLAG to express FLAG-tagged versions of full length lysinSM1 ( amino acids [AA] 1–295 ) , the amino terminus of lysinSM1 ( AA 1–158; N-lysinSM1 ) , or the carboxy terminus of lysinSM1 ( AA 141–295; C- lysinSM1 ) . Untagged lysinSM1 , C-lysinSM1 , and His-tagged N-lysinSM1 ( HisN-lysinSM1 ) were cloned into pET22b ( + ) ( Novagen ) . The plasmids were then introduced to E . coli BL21 ( DE3 ) by transformation . LysinSM1 , FLAGlysinSM1 , C-lysinSM1 and FLAGC-lysinSM1 were purified with DEAE-cellulose columns , as described previously [16] . FLAGN-lysinSM1 and HisN-lysinSM1 were purified by either Ni-NTA ( Promega ) or anti-FLAG M2 agarose affinity chromatography ( Sigma-Aldrich ) , according to the manufacturers' instructions . A gene replacement cassette was constructed by cloning the chromosomal regions flanking lys upstream and downstream of the cat gene in pC326 [16] . A 339 bp upstream segment was amplified using primers KO4F and KO4R , and then digested with XhoI and HindIII . A 513 bp downstream segment was amplified with primers KO6F and KO6R , and then digested with EcoRI . The upstream and downstream fragments were cloned sequentially into the corresponding sites of pC326 . The resulting plasmid , pKO-lys , was introduced into SF100 by natural transformation as previously described [17] . In brief , overnight SF100 cultures were diluted 100-fold in fresh THB supplemented with 20% heat-inactivated horse serum , 200 ng/ml competence-stimulating peptide ( CSP; DWRISETIRNLIFPRRK ) , and 1 µg/ml of plasmid . Transformation mixtures were incubated 4 h at 37°C and then plated on blood agar containing 5 µg chloramphenicol per ml . To complement in trans the lys mutation in PS1006 , lys was amplified using primers 3206-XbaI and 5206-EcoRI and then cloned into the streptococcal expression vector pDE123 . This plasmid was derived from pDC123 by replacing the chloramphenicol resistance marker with an erythromycin resistance marker [46] . The resulting plasmid , pDE-lys , was introduced into PS1006 by natural transformation . The bacteria and plasmids used in this study are listed in Table S1 . S . mitis strains were grown in Todd-Hewitt broth ( Difco ) supplemented with 0 . 5% yeast extract ( THY ) . PS344 ( ΔORF47-PblB::pVA891 ) and PS1006 ( ΔlysinSM1 ) are isogenic variants of S . mitis SF100 , which is an endocarditis-associated clinical isolate [16] . All three strains grow comparably well in vitro . S . pneumoniae strains were grown in either a chemically defined medium ( CDM; JRH bioscience ) [47] supplemented with 0 . 1% choline chloride , or THY . S . pneumoniae HS0001 is a nonencapsulated pneumococcal strain derived from the TIGR4 strain by deleting the capsule synthesis locus as described previously [48] . S . pneumoniae HS0001-EA is a PC-negative strain derived from HS0001 as described previously [49] . Escherichia coli DH5α and BL21 ( DE3 ) strains were grown at 37°C under aeration in Luria broth ( LB; Difco ) . Appropriate concentrations of antibiotics were added to the media , if required . Transformed E . coli BL21 ( DE3 ) cells were harvested by centrifugation , washed and suspended in 50 mM Tris-maleate ( ™ ) buffer ( Sigma-Aldrich ) , pH 6 . 3 . Cells were disrupted by treatment with B-PER lysis solution ( Pierce , Rockford , IL ) and the debris was removed by centrifugation at 4 , 000 rpm for 10 min at 4°C . Supernatants were loaded on a 2 ml DEAE-cellulose ( Sigma-Aldrich ) column equilibrated with 50 mM ™ buffer , pH 6 . 3 . The column was washed with at least 3 volumes of 50 mM ™ buffer , pH 6 . 3 , containing 1 . 5 M NaCl and 0 . 1% choline chloride , until no protein was detected in the eluent . The retained proteins were then eluted with 50 mM ™ buffer , pH 6 . 3 , containing 1 . 5 M NaCl and 2% choline chloride . Recombinant protein was dialyzed against PBS and then stored at −70°C . Early log phage ( A600 = 0 . 5 ) bacteria were harvested by centrifugation and suspended in PBS at approximately 108–109 CFU/ml . Bacteria samples were then incubated with or without 30 µg/ml of purified lysinSM1 at 37°C for 30 min . Samples were serially diluted in PBS and plated onto blood agar , to determine the number of surviving bacteria . Platelet membranes were prepared by glycerol lysis and gradient centrifugation , as previously described [50] . In brief , isolated human platelets were lysed in 5 volumes of lysis buffer ( 8 . 5 mM Tris-Cl , 96 . 5 mM NaCl , 85 . 7 mM glucose , 1 mM EDTA , 10 mM EGTA [pH 7 . 4] ) containing Complete Protease Inhibitor Cocktail ( Roche ) . The sample was centrifuged ( 5 , 900× g , 10 min ) to remove unlysed platelets , and the supernatant was applied to a sucrose step gradient ( 10 ml of 33% sucrose on 5 ml of 66% sucrose in buffer ) . After ultracentrifugation ( 90 min , 63 , 000× g , 4°C ) , the membranes were removed , dialyzed against PBS containing 10% glycerol , and stored at −70°C . Samples were separated by electrophoresis through 4–12% NuPAGE Bis-Tris gels ( Invitrogen ) and transferred onto nitrocellulose membranes . The membrane were treated with a casein-based blocking solution ( Western Blocking Reagent; Roche ) at room temperature , and then incubated for 1 h with FLAGlysinSM1 ( 5 µg/ml ) or purified human fibrinogen ( 1 µg/ml ) suspended in PBS-0 . 05% Tween 20 ( PBS-T ) . The membranes were then washed three times for 15 min in PBS-T , and bound probe proteins were detected with mouse anti-FLAG monoclonal antibody ( Sigma-Aldrich ) or rabbit anti-fibrinogen polyclonal IgG antibody . Washed , fixed human platelets or purified platelet membranes were immobilized in 96 well microtiter plates as described previously [51] . To reduce non-specific adherence , the wells were then treated with the casein-based blocking reagent for 1 h at room temperature . The blocking solution was removed by aspiration , and the wells were incubated with 0 to 100 µg of FLAGlysinSM1 in PBS for 1 h , at RT , followed by washing to remove unbound protein . Bound FLAGlysinSM1 was detected by ELISA with anti-FLAG antibody . For some studies , the wells containing platelet membranes were pretreated with 0 to 100 µg/ml of rabbit anti-fibrinogen antibody for 30 min , followed by washing to remove unbound antibody . Binding by FLAGlysinSM1 ( 5 µg/ml ) was then assessed as described above . Rat fibrinogen ( 10 µg/ml ) , human fibrinogen , or human fibrinogen D or E fragments ( all 15 nM in PBS ) , were immobilized in 96-well microtiter dishes by overnight incubation at 4°C . The wells were washed twice with PBS and blocked with 300 µl of casein-based blocking solution for 1 h at room temperature . The plates were washed three times with PBS , and a range of FLAGlysinSM1 concentrations in PBS with Tween 20 ( 0 . 05% ) were added . The plates were then incubated for 2 h at 37°C . Unbound protein was removed by washing with PBS , and plates were incubated with mouse anti-FLAG antibodies for 1 h at 37°C . Binding was assessed by ELISA , using HRP-conjugated rabbit anti-mouse IgG , for 1 h at 37°C . FLAGAP ( 25–100 µg/ml ) served as a control for nonspecific binding . To examine the binding of fibrinogen to immobilized FLAGlysinSM1 , untagged lysinSM1 , or FLAGAP ( 10 µg/ml in PBS ) were immobilized in 96 well microtiter plates , followed by blocking of the wells with the casein blocking solution . The wells were incubated with a range of human fibrinogen for 1 h at room temperature , followed by washing . Bound fibrinogen was detected by ELISA , using anti-human fibrinogen IgG . Cultures of PS1006 and S . mitis SK598 in the early log phage of growth ( A600 = 0 . 5 ) were harvested by centrifugation and suspended in PBS . The bacteria were incubated with purified FLAGlysinSM1 ( 0 to 10 µg/ml ) for 30 min at room temperature . The samples were washed twice with PBS to remove unbound FLAGlysinSM1 and incubated with PBS-2% choline chloride to elute choline-binding proteins from the cell walls , as described previously [21] . Eluted cell wall proteins were harvested by centrifugation and loaded onto SDS-PAGE . Cell wall bound FLAGlysinSM1 was detected by western blotting with anti-FLAG antibody . Overnight cultures of S . mitis SF100 or its isogenic mutants ( PS1006 and PS344 ) were diluted 1∶10 in fresh THY broth , incubated for 1 h at 37°C , and then exposed to UV light ( λ = 312 nm ) for 3 min , to induce the expression of the lysogenic bacteriophage SM1 . The cultures were then incubated at 37°C for an additional 2 h , followed by harvesting by centrifugation . The pellets were suspended in PBS , and adjusted to a concentration of 106 CFU/ml . One hundred microliters of each suspension were added to wells that had been coated overnight with 30 µg/well of fibrinogen in carbonate buffer . The plates were incubated at room temperature for 1 h , and the wells were washed three times with PBS to remove nonadherent bacteria . The wells were then treated with 50 µl of trypsin ( 2 . 5 mg/ml ) for 30 min at 37°C to release the bound bacteria . The number of bound bacteria was determined by plating serial dilutions of the recovered bacteria onto blood agar . LTA was prepared from S . pneumoniae HS0001 and S . mitis strains by organic solvent extraction and octyl-Sepharose chromatography , as previously described [52] . In brief , bacteria were cultured at 37°C for 10 h in CDM with 0 . 1% choline chloride ( Fisher scientific Inc . ) . To purify PC negative LTA , S . pneumoniae HS0001-EA was cultured for 16 h in CDM supplemented with 2% ethanolamine . Pelleted bacteria were suspended in 0 . 05 M sodium acetate ( pH 4 . 0 ) and lysed by sonication . After extraction from the lysate with a chloroform and methanol mixture ( 1∶0 . 9 ) , the LTA was adsorbed onto an octyl-Sepharose CL-4B ( Sigma-Aldrich ) equilibrated in a mixture of 15% n-propanol and 0 . 05 M sodium acetate ( pH 4 . 7 ) . The absorbed LTA was then eluted with 35% n-propanol in 0 . 05 M sodium acetate ( pH 4 . 7 ) . Purified LTA was analyzed by matrix-assisted laser desorption ionization-time of flight ( MALDI-TOF ) mass spectrometry [52] ( Figure S5 ) . In brief , 1 µl of a sample ( 1 µg/ml ) and 1 µl of matrix solution ( 0 . 5 M 2 , 5-dihydroxybenzoic acid and 0 . 1% trifluoroacetic acid in methanol ) were applied to a sample plate . After drying , the sample was analyzed with a mass spectrometer ( Voyager Biospectrometry DE Pro workstation; PerSeptive Biosystems ) . Purified LTA showed three major peaks that corresponded to LTA with five , six , and seven repeating units , respectively . The mass difference between the major peaks was 1299 or 1100 amu , corresponding to an oligosaccharide repeating unit with two PC groups or two phosphoethanolamine groups [52] . In addition , PC expression by strains HS0001 and SF100 was directly assessed by western blotting with anti-PC antibody ( TEPC-15; Sigma-Aldrich ) [53] ( Figure S6 ) . The relative virulence of SF100 and its isogenic variants was compared in a competition model of infective endocarditis , as described previously [16] , [54] . In brief , Sprague-Dawley female rats ( 250 to 300 g each ) were first anesthetized with ketamine ( 35 mg/kg ) and xylazine ( 10 mg/kg ) . A sterile polyethylene catheter was surgically placed across the aortic valve of each animal , such that the tip was positioned in the left ventricle , to induce the formation of sterile vegetations ( nonbacterial thrombotic endocarditis ) . The catheters were left in place throughout the study . Seven days post-catheterization , the animals were infected intravenously with an inoculum of 105 CFU containing a 1∶1 mixture of a ) SF100 and PS344 , b ) SF100 and PS1006 , or c ) PS344 and PS1006 . At 72 hr post-infection , the rats were euthanized with thiopental ( 100 mg IP ) . Animals were included in the final analysis only if the catheters were correctly positioned across the aortic valve at the time of sacrifice , and if macroscopic vegetations were visible . All cardiac vegetations , as well as samples of the kidneys and spleens , were harvested , weighed , homogenized in saline , serially diluted , and plated onto 8% Todd Hewitt agar ( ±2 . 5 µg/ml of chloramphenicol or 5 µg/ml of erythromycin ) for quantitative culture . The plates were cultured for 48 h at 37°C , and bacterial densities were expressed as the log10 CFU per gram of tissue . Differences in means were compared for statistical significance by the paired t-test . The data were also analyzed by calculating a “competition index , ” which was defined as the ratio of the paired strains within tissues for each animal , normalized by the ratio of organisms in the inoculum . The mean of the log10 normalized ratios was tested against the hypothesized ‘no effect’ mean value of 0 , as described previously , using a paired t-test , with P<0 . 05 as the threshold for statistical significance [55] . Data expressed as means ± standard deviations were compared for statistical significance by the paired or unpaired t test , as indicated .
|
The binding of bacteria to human platelets is thought to be a central event in the development of endocarditis ( a life-threatening cardiovascular infection ) . We have previously found that platelet binding by Streptococcus mitis is mediated by surface components encoded by a bacteriophage contained within the host bacterium . We now show that lysin ( an enzyme of bacteriophage origin ) contributes to platelet binding via its direct interaction with fibrinogen on the platelet surface . Lysin bound to purified fibrinogen in vitro , and this interaction specifically involved the Aα and Bβ chains of fibrinogen . Binding of lysin to the Bβ chain was further localized to a region within the fibrinogen D fragment . Disruption of the gene encoding lysin gene resulted in a significant reduction in binding to fibrinogen by S . mitis , as well as a major reduction in virulence , as measured by a rat model of endocarditis . These results indicate that lysin is a multifunctional protein , representing a new class of fibrinogen-binding molecules . Lysin is localized to the bacterial surface via its interaction with cell wall choline , where it then can bind fibrinogen directly . Cell surface lysin apparently also contributes to the development of endovascular infections via its previously unrecognized fibrinogen binding activity .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/bacterial",
"infections",
"microbiology/cellular",
"microbiology",
"and",
"pathogenesis"
] |
2010
|
Bacteriophage Lysin Mediates the Binding of Streptococcus mitis to Human Platelets through Interaction with Fibrinogen
|
MACC1 ( Metastasis Associated in Colon Cancer 1 ) is a key driver and prognostic biomarker for cancer progression and metastasis in a large variety of solid tumor types , particularly colorectal cancer ( CRC ) . However , no MACC1 inhibitors have been identified yet . Therefore , we aimed to target MACC1 expression using a luciferase reporter-based high-throughput screening with the ChemBioNet library of more than 30 , 000 compounds . The small molecules lovastatin and rottlerin emerged as the most potent MACC1 transcriptional inhibitors . They remarkably inhibited MACC1 promoter activity and expression , resulting in reduced cell motility . Lovastatin impaired the binding of the transcription factors c-Jun and Sp1 to the MACC1 promoter , thereby inhibiting MACC1 transcription . Most importantly , in CRC-xenografted mice , lovastatin and rottlerin restricted MACC1 expression and liver metastasis . This is—to the best of our knowledge—the first identification of inhibitors restricting cancer progression and metastasis via the novel target MACC1 . This drug repositioning might be of therapeutic value for CRC patients .
Colorectal cancer ( CRC ) is one of the leading causes of cancer-associated death worldwide . Metastasis of CRC is mainly responsible for the global mortality burden and is directly linked to patient survival . This necessitates the search for molecular biomarkers for the early identification of patients with tumors of elevated metastatic propensity . One such promising biomarker that emerged in the recent past is Metastasis-Associated in Colon Cancer 1 ( MACC1 ) [1 , 2] . MACC1 mRNA expression in primary tumors was shown to be directly correlated with metastasis formation and metastasis-free survival within a 12-y follow-up [1] . Numerous follow-up studies confirmed the prognostic value of MACC1 for CRC metastasis and patient survival [3–9] . MACC1 was shown to induce migration , invasion , and proliferation in cell culture , as well as tumor progression and formation of metastases in xenografted and genetically engineered mouse models [1 , 10 , 11] . Many further studies reported that MACC1 can act as a decisive driver for the transition from adenoma to carcinoma and thus initiates cancer progression and ultimately metastasis [5 , 10 , 12–18] . Apart from its crucial role in CRC progression and metastasis , recent studies indicate the relevance of MACC1 in tumor progression and metastasis of several other solid tumor types [2 , 3 , 12 , 17 , 19–26] . All these studies have speculated about the strong therapeutic potential of targeting MACC1 to restrict CRC progression and metastasis , which can also be applied to other solid cancers . However , so far , no inhibitor of MACC1 expression has been described . Here we report the identification of the first small-molecule MACC1 transcriptional inhibitors using a high-throughput screening ( HTS ) of more than 30 , 000 compounds , which was possible because of our previous identification of the human MACC1 promoter [27] . We identified the statins mevastatin and lovastatin and , additionally , rottlerin as effective inhibitors of MACC1 promoter activity and expression . Statins are originally a widely known and clinically used drug class for reducing cholesterol levels [28] . Rottlerin shows different modes of action but has not been successful in achieving clinical approval [29] . In this study , we particularly investigated the effects of lovastatin on MACC1 expression and MACC1-associated metastasis in order to reposition this known compound as an antimetastatic drug , thereby broadening its therapeutic value in oncology .
HCT116-MACC1p-Luc CRC cells stably expressing the human MACC1 promoter-driven luciferase reporter gene ( Fig 1A ) were used to screen the ChemBioNet library of more than 30 , 000 compounds , which includes the Sigma Library of Pharmacologically Active Compounds ( LOPAC ) , for identification of potential transcriptional MACC1 inhibitors [30] . In the primary screen , using 5 μM of each compound ( the screening parameters are listed in S1 Table ) , we identified 542 compounds that inhibited MACC1 promoter-driven luciferase expression by more than 3 standard deviations from the mean of all samples on a plate ( Z score < −3; Fig 1B ) . These 542 compounds were then subjected to a selectivity counter screen for false positives acting against luciferase itself with HCT116-CMVp-Luc cells , wherein the luciferase gene was driven by the CMV promoter instead of the MACC1 promoter . Four hundred and forty-five compounds inhibited CMVp-driven luciferase expression by more than 75%; these were considered as nonspecific luciferase inhibitors , CMVp inhibitors , or cytotoxic compounds and were excluded . Ninety-seven specific compounds , which included 7 pharmacologically active compounds from the LOPAC of approved drugs and 90 novel biologically annotated compounds , were left for further characterization . These 97 compounds were then tested for MACC1p inhibitory capacity in more detail by luciferase assays using 10 two-fold serial dilutions starting with the highest concentration of 25 μM . On the basis of inhibitory properties ( Hill coefficient and IC50 values ) , solubility , purity , selectivity screen comparison , and information on known biological targets and functions , the top 10 candidates with the most potential were identified ( Fig 1C , S2 Table ) . Among these 10 compounds , mevastatin and rottlerin showed the best potential for MACC1 transcriptional inhibition . In the dose-response assay for measuring MACC1 promoter activity , mevastatin and rottlerin showed a remarkable inhibition of luciferase activity at a concentration of 1 . 6 μM and 0 . 78 μM , respectively ( Fig 1D and 1F ) . We next performed an MTT assay to evaluate the effects of these drugs on cell viability . Mevastatin and rottlerin reduced cell viability by 50% at concentrations higher than 50 and 25 μM , respectively ( Fig 1D and 1F ) . However , in the past mevastatin was evaluated as a less effective HMG-CoA inhibitor in patients and demonstrated an acute toxicity profile in dogs [31] . Because of these controversial findings , mevastatin did not reach routine clinical use . In contrast , lovastatin exerted better efficacy as an HMG-CoA inhibitor and became the first member of the statins receiving Food and Drug Administration ( FDA ) approval [28] . Moreover , mevastatin and lovastatin are structurally closely related compounds that differ only by 1 methyl group . Although lovastatin was not included in the compound library , we decided to work with lovastatin from here on instead of mevastatin . Therefore , we determined whether lovastatin has the same inhibitory effect on MACC1 promoter-driven reporter gene expression as mevastatin , allowing fast translation into clinical trials . We performed a dose-response curve using 10 two-fold serial dilutions of lovastatin as done for mevastatin and analyzed its effect on cell viability and luciferase activity in HCT116-MACC1p-Luc cells . Lovastatin inhibited luciferase activity at 0 . 39 μM and higher concentrations and reduced viability only at 12 . 5 μM and higher concentrations ( Fig 1E ) . Thus , the dose-response assays confirmed that mevastatin , lovastatin , and rottlerin possess the potential to inhibit MACC1 promoter-driven reporter gene expression at noncytotoxic concentrations . To determine the effect of the identified inhibitors on MACC1 expression , HCT116 cells were treated with increasing concentrations of rottlerin , mevastatin , and lovastatin for 24 h . At a concentration of 2 . 5 μM , rottlerin showed more than 60% reduction in the endogenous MACC1 mRNA ( p < 0 . 001 ) and protein level compared to the solvent-treated control ( Fig 2A ) . Similarly , treatment with 5 μM mevastatin significantly restricted the MACC1 mRNA level to 50% of the solvent-treated control ( Fig 3A , p < 0 . 01 ) , whereas treatment with 5 μM lovastatin significantly reduced MACC1 mRNA levels by 62% as compared to the solvent-treated control ( p < 0 . 001 , Fig 3B ) . Consistent with the reduction of MACC1 mRNA levels , the statins caused a decrease in MACC1 protein level at 5 μM and above , as demonstrated by western blotting ( Fig 3A and 3B ) . These results demonstrate that the treatment reduced the MACC1 mRNA level in a concentration-dependent manner for all 3 drugs . Of note , we saw comparable efficiency of mevastatin and lovastatin as MACC1 transcriptional inhibitors . Based on our primary interest of repositioning approved drugs as MACC1 inhibitors , lovastatin became the preferred drug candidate for our further , more detailed analyses . We then analyzed the kinetics underlying the rottlerin- and lovastatin-mediated inhibition of MACC1 expression . We found that both drugs reduced the MACC1 expression after a single drug application . After 12 h of treatment of HCT116 cells with 2 . 5 μM rottlerin , MACC1 mRNA was significantly reduced to less than 50% ( p < 0 . 001 ) as compared to the solvent-treated control and was further reduced to 26% of the solvent-treated cells ( p < 0 . 001 ) at 48 h ( Fig 2B ) . Consistent with the mRNA expression , reduction in the MACC1 protein was also detected 12 h post treatment and remained low until 48 h following a single dose ( Fig 2B ) . For lovastatin , MACC1 mRNA was significantly reduced to less than 50% ( p < 0 . 001 ) after 18 h of drug treatment with 5 μM lovastatin and was further decreased to 16% at 48 h ( p < 0 . 001 ) as compared to the solvent-treated control ( Fig 3C ) . Consistent with the mRNA expression , reduction in the MACC1 protein was also detected at 24 h post lovastatin treatment , and it remained reduced until 48 h following the single drug application ( Fig 3C ) . To further support that rottlerin and lovastatin are transcriptional inhibitors of MACC1 , we hypothesized that ectopic overexpression of MACC1 governed by a promoter other than the human MACC1 promoter should be irresponsive to the inhibitory effects of lovastatin . Therefore , HCT116 cells were transiently transfected to express CMV promoter-driven MACC1 cDNA , leading to increased MACC1 mRNA and protein levels compared to HCT116/vector cells . Treatment of HCT116/vector cells with 2 . 5 μM rottlerin and 5 μM lovastatin ( Figs 2C and 3D ) reduced the MACC1 mRNA levels to more than 50% of the solvent-treated control ( p < 0 . 01 ) , which was similar to the effect observed in wild-type HCT116 cells . In contrast , treatment of HCT116/MACC1 cells with lovastatin did not result in inhibition of MACC1 mRNA . Coherent to the mRNA data , MACC1 protein expression in the HCT116/vector cells was reduced upon drug treatments , but not in drug-treated HCT116/MACC1 cells ( Figs 2C and 3D ) . Next , we analyzed the inhibitory effects of rottlerin and lovastatin on the MACC1 expression in the SW48 , DLD-1 , and SW620 CRC cell lines . Both drugs were capable of restricting MACC1 expression in these 3 human CRC cell lines . Since the effective drug concentrations were cell line dependent , we tested all drug concentrations for effects on cell viability . None of these concentrations including elevated drug concentrations of above 10 μM reduced cell viability within 24 h ( S1 Fig ) . Upon treatment of these CRC cells with rottlerin , MACC1 mRNA levels were reduced to 50% at a concentration of 5 μM in SW48 cells , 2 . 5 μM in DLD-1 cells , and 20 μM in SW620 cells as compared to the solvent-treated control ( p < 0 . 001 , Fig 2D , 2E and 2F ) . For lovastatin , treatments of 2 . 5 μM were sufficient to reduce MACC1 mRNA to 40% in SW48 cells , ( p < 0 . 001 , Fig 3E ) , whereas in DLD-1 cells , 30 μM of lovastatin was required to achieve a 50% decrease in MACC1 mRNA level ( p < 0 . 01 , Fig 3F ) . For SW620 cells , a higher concentration of 50 μM was required to restrict MACC1 expression to 55% ( p < 0 . 001 , Fig 3G ) . However , to identify a potential MACC1 inhibitor with a brighter clinical translational perspective anticipated for the future , we decided to focus on lovastatin because of the availability of pharmacokinetics data , its safety profile , and its global consumption for cholesterol control . Due to the fact that the mechanism of action for rottlerin is still debated and only limited data are available on pharmacology and toxicology , this compound has not yet been in clinical use . Furthermore , rottlerin was never approved by the FDA or other authorities for its use in patients , which in fact would have been one decisive criterion for our intention to reposition this drug as an MACC1 inhibitor . For the potential clinical translation of our findings , we therefore focused on lovastatin as a compound routinely used in the clinic and being more suited for repositioning in cancer therapy . A major phenotype imparted by MACC1 is increased migration of the CRC cells [1] . Thus , we investigated the effect of lovastatin on MACC1-mediated cell migration of HCT116/vector cells and HCT116/MACC1 using the Boyden chamber assay . HCT116/vector cells treated with 5 μM lovastatin for 24 h showed inhibition of cell migration to less than 50% of solvent-treated control cells ( p < 0 . 05; Fig 4A ) . In contrast , HCT116/MACC1 cells with CMV promoter-driven MACC1 expression treated with lovastatin for 24 h showed no statistically significant inhibition of migration compared with the solvent-treated cells . As shown in Fig 4B , 5 μM lovastatin has no significant effect on proliferation/cell number in HCT116 cells at 24 h , suggesting that the effect on migration at this time point is mostly independent of cell proliferation . We further analyzed the effect of lovastatin on directed migration in a wound healing assay . In the absence of lovastatin , HCT116/vector and HCT116/MACC1 cells entirely closed the inserted wound in 48 h ( Fig 4C ) . Wound closure was impaired in lovastatin-treated HCT116/vector cells . In contrast , HCT116/MACC1 cells treated with lovastatin were able to infiltrate the wound and close the gap significantly faster compared to control cells , as shown by the representative figures and the corresponding quantification ( Fig 4D; p < 0 . 05 ) . This was also confirmed in DLD-1 cells ( S2 Fig ) . In summary , treatment with lovastatin restricted cell motility . Ectopic overexpression of MACC1 was able to rescue lovastatin-mediated inhibition of cell motility , suggesting that the effect of lovastatin was specific to MACC1 . In our previous study , we described that c-Jun and Sp1 regulate MACC1 transcription by binding to its core promoter region [27] . Here , we identified that lovastatin inhibits MACC1 transcription . Therefore , we wanted to know if lovastatin influences c-Jun and Sp1 binding to the human MACC1 promoter . This was investigated by electrophoretic mobility shift assay ( EMSA ) , using biotinylated oligonucleotides encompassing the c-Jun or Sp1 binding site of the MACC1 promoter as described earlier [27] . In solvent-treated HCT116 cells , a strong signal was observed because of the binding of c-Jun and Sp1 with their respective biotinylated oligonucleotides , consistent with our previous findings . However , treatment of HCT116 cells with lovastatin interrupted the binding of c-Jun and Sp1 with the MACC1 promoter ( Fig 5A ) . The specificity of the c-Jun/MACC1 promoter complex was verified by the addition of unlabeled oligonucleotides and c-Jun antibody , both leading to the reduction in the signal ( Fig 5A ) . Similar results were found with the chromatin immunoprecipitation ( ChIP ) assay ( Fig 5B and 5D ) . Solvent-treated cell extracts showed 3 . 3-fold and 2-fold higher enrichment of MACC1 promoter sequence after immunoprecipitation with c-Jun and Sp1 antibody , respectively , as compared with lovastatin-treated cell extracts . We further analyzed the expression levels of c-Jun and Sp1in lovastatin-treated cells , showing that drug treatment did not alter total Sp1 expression at mRNA and protein levels ( Fig 5E ) . In contrast , c-Jun expression was found to be elevated at mRNA and protein levels upon lovastatin treatment ( Fig 5C ) . Therefore , it can be deduced that the decrease in c-Jun and Sp1 binding to the MACC1 promoter is not attributable to the decrease in the c-Jun and Sp1 levels , and lovastatin is not an inhibitor of c-Jun or Sp1 expression . These results indicate that the small molecule lovastatin restricts c-Jun/MACC1 and Sp1/MACC1 promoter binding and thereby influences MACC1 gene transcription . The reduction of MACC1-mRNA expression was verified by decreased binding of transcription factor complexes at AP-1/c-Jun-specific oligonucleotides of the MACC1 promoter . We then hypothesized the loss of DNA binding by competitive interaction of the drugs with the DNA binding site of AP-1 . Therefore , we docked the drugs onto a published crystal structure of the leucine zipper of AP-1 ( Fig 6A ) and determined a docking score for each molecule . The docking score for rottlerin was 75 . 7 , and the scores for lovastatin and mevastatin were 50 . 9 and 50 . 7 , respectively . The molecular docking predicts interactions of all drugs with ARG155 , ARG158 , and LYS283 , spanning both arms of the leucine zipper ( Fig 6B ) . Since no cocrystallized ligand of this area other than DNA was available , we used published inhibitors of AP-1 to rate the docking scores and also docked them into the defined binding site . We found 4 substances , published by Chen et al . , that reduced AP-1/DNA binding more than 90% at a concentration of 0 . 1 mg/ml [32] . The docking scores of shimobashiric acid C , salvianolic acid L , Mena987 , and rosmarinic acid were predicted as 96 . 8 , 82 . 2 , 66 . 8 , and 59 . 8 , respectively . In order to analyze the effect of lovastatin on tumor growth and metastasis formation in mice , we first determined the tolerable doses of the drug . We chose an oral application route for a concentration range of 10 mg/kg up to 100 mg/kg lovastatin . Since we observed no toxicities ( as a measure of body weight and general health condition ) ( Fig 7A ) , we finally selected a concentration of 100 mg/kg , which has been described to be safe and tolerable for the animals in a previous study [33] , for further in vivo studies . We next monitored the effect of lovastatin on metastasis formation over time in a mouse xenograft model by noninvasive in vivo bioluminescence imaging . Severe combined immunodeficiency ( SCID ) -beige mice were intrasplenically xenotransplanted with HCT116-CMVp-Luc cells and were randomized in 2 groups of n = 9 animals each . The bioluminescence measurement started at day 6 post intrasplenic transplantation of HCT116-CMVp-Luc cells . Lateral signals ( representing the spleen as the site of the primary tumor ) were observed in solvent- and lovastatin-treated mice and were assigned to the spleen . Ventral signals ( representing the liver as the site of metastasis ) were assigned to the liver , representing metastasis formation . Signals from both lateral and ventral imaging over the period of 26 d were quantified as shown in Fig 7B and 7C . On day 26 , the animals in the solvent-treated control group started to show clear signs of morbidity due to tumor burden , which was not observed in the lovastatin-treated group . Thus , the experiment had to be terminated because of ethical reasons . Representative images indicating spleen and liver signals in vivo and ex vivo on day 26 are shown in Fig 7D and 7F . Quantification of the luminescence signal from the ventral side on day 26 showed a significant inhibition of liver metastasis under lovastatin treatment ( p < 0 . 01 ) , with a slight but not significant decrease in tumor growth in the spleen compared to the solvent-treated group ( Fig 7E and 7G ) . We next analyzed the presence of human satellite DNA in the liver of the control versus the lovastatin-treated mice as a molecular marker for the appearance of metastases ( Fig 7H ) . This analysis revealed that the livers from the lovastatin-treated group carried 40% less satellite DNA as compared to treated animals , supporting our bioluminescence finding from Fig 7C , 7F and 7G . In addition , MACC1 mRNA levels were quantified by quantitative real-time reverse-transcription polymerase chain reaction ( qRT-PCR ) to verify lovastatin-mediated transcriptional inhibition of MACC1 in vivo ( Fig 7I ) . Lovastatin-treated animals showed significantly reduced MACC1 mRNA expression ( p < 0 . 05 ) , confirming that the drug acts as a transcriptional inhibitor of MACC1 and thus inhibits MACC1-induced metastasis formation in vivo . In order to analyze further drug-induced effects , we determined the mRNA expression of genes that can be regulated by lovastatin ( DNMT1 , Col1A1 , and MCM2 ) [34–36] . DNMT1 and MCM2 showed no significant expression regulation upon treatment with lovastatin , whereas Col1A1 was significantly down-regulated , and HMGCR was significantly up-regulated ( S3 Fig ) . As mentioned earlier , rottlerin was among the selected candidates for MACC1 inhibition that emerged among the most promising drugs from the HTS . Due to this fact , we were interested to validate if this drug is able to fulfill its proposed MACC1 inhibitory potential in vivo , which we consider as a decisive criterion for the HTS verification . Therefore , similar to the in vivo lovastatin study , we evaluated the effects of rottlerin as the second most promising drug that emerged from the HTS on MACC1-induced metastasis in mice . A previous study with rottlerin has used 0 . 012% rottlerin in food , corresponding to 25 mg rottlerin per kg bodyweight [37] . Herein , we employed an oral application route for a concentration range of 10 mg/kg up to 100 mg/kg rottlerin to determine tolerable doses . An oral concentration of 100 mg/kg was used for the in vivo studies , which was identified to be safe in the drug tolerability studies ( Fig 8A ) . The bioluminescence measurement started at day 8 post intrasplenic transplantation of HCT116-CMVp-Luc cells . Signals from both lateral and ventral imaging over 24 d were quantified as shown in Fig 8B and 8C , demonstrating that rottlerin-treated animals had restricted primary tumor growth and reduced liver metastasis . Representative images indicating the lateral and ventral signals on day 24 are shown in Fig 8D and 8F . On day 24 , the animals in the solvent-treated control group started to show clear signs of morbidity due to tumor burden , which was not observed in the rottlerin-treated group . Thus , the experiment was terminated . Endpoint quantification of lateral and ventral signals showed that the application of rottlerin reduced tumor growth ( p < 0 . 001 ) and metastasis formation ( p < 0 . 05 ) significantly ( Fig 8E and 8G ) . We next analyzed the presence of human satellite DNA in the livers of the control versus the treated mice ( Fig 8H ) . Our results validated that livers from the solvent-treated group had much more human satellite DNA as compared to the rottlerin-treated animals ( p < 0 . 01 ) , confirming the restricted metastatic ability of rottlerin-treated cells . Finally , MACC1 mRNA levels were quantified ( Fig 8I ) . Rottlerin-treated animals showed significantly reduced MACC1 expression ( p < 0 . 05 ) , confirming that rottlerin acts as a transcriptional inhibitor of MACC1 and thus inhibits MACC1-induced metastasis formation in vivo . We analyzed further rottlerin-induced effects by determining the mRNA expression levels of genes that can be regulated by rottlerin ( CDC20 , mTor , and SKP2 ) [38–40] . No significant expression regulation upon treatment with rottlerin was observed ( S3 Fig ) .
MACC1 has been established by numerous studies as a biomarker for prognosis of metastasis formation , survival , and prediction of therapy response in a broad variety of solid cancer types , such as in cancers of the gastrointestinal tract ( e . g . , CRC and esophageal , gastric , and pancreatic cancer ) and hepatocellular , hepatobiliary , renal , bladder , breast , ovarian , cervical , lung , nasopharyngeal , salivary gland , and tongue cancer , as well as in glioblastomas and osteosarcomas . MACC1 acts as a key driver in tumor progression towards more advanced tumor stages and metastasis formation [2 , 24–26] . Here , we hypothesized the potential of MACC1 for targeted therapy and aimed to target MACC1 for intervention in CRC progression and metastasis formation . This is of particular interest since until now no inhibitors have been known for MACC1 . Therefore , finding effective MACC1 inhibitors will add to the therapeutic possibilities for targeted intervention of tumor progression and metastasis progression . To achieve this , we employed HTS to identify inhibitors for MACC1 expression by using the human MACC1 promoter-driven luciferase reporter system . This HTS revealed mevastatin and rottlerin as the most promising hits for MACC1 transcriptional inhibition , providing the chance to reposition these drugs in cancer therapy . Mevastatin ( isolated from Penicillium citrinum and also known as compactin ) was the first statin found to have a powerful inhibitory effect on HMG-CoA reductase [41–43] . In the present study , we demonstrated a novel target of this statin: MACC1 . However , mevastatin was never approved by the FDA because of its lesser efficacy in patients and considerable toxicity in dogs . In contrast , lovastatin , a mevastatin analogue , was the first FDA-approved cholesterol-lowering drug . This drug has since then been long in clinical use , which makes lovastatin a valuable candidate for repositioning in cancer therapy [31] . From the HTS data , we decided to analyze the effects of mevastatin and lovastatin in more detail , demonstrating a concentration-dependent inhibition of MACC1 expression , subsequently restricting MACC1-induced cell motility in vitro . Lovastatin reduced MACC1 mRNA and protein expression in CRC cells , and the effects were dependent on drug concentration , time of treatment , and the cell line used . To the best of our knowledge , this is the first study demonstrating the effect of lovastatin on MACC1 expression . Consistent with our findings , lovastatin did not affect CMV promoter-driven MACC1 expression . Therefore , the effects we observed are specific for endogenous MACC1 regulated by the human MACC1 promoter . Moreover , our study demonstrates that lovastatin can restrict cell migration , thereby intervening in crucial metastatic capabilities . As statins target MACC1 , which plays a decisive role in cellular motility , the effects of restricted migration could be at least partially mediated by reduced MACC1 levels . The rescue of the lovastatin-mediated effects on migration by ectopic CMV promoter-driven overexpression of MACC1 further strengthens the role of lovastatin in restricting MACC1-induced cell motility . However , the possibility of other lovastatin targets contributing to reduction in the aggressive phenotype still prevails . For instance , statins have already been described in the literature as anticancer agents acting via p38MAPK-p53-survivin signaling cascade or via the bone morphogenetic protein ( BMP ) pathway [44–46] or Rho signaling [47] . To understand further the impact of lovastatin on MACC1 transcriptional inhibition , we analyzed the binding of c-Jun and Sp1 to the human MACC1 promoter . C-Jun and Sp1 have been established in our previous study as crucial transcription factors that bind to the MACC1 promoter and regulate its expression [27] . Analysis of c-Jun and Sp1 binding with the MACC1 promoter revealed that lovastatin disrupted the binding of these transcription factors with the MACC1 promoter . This could be potentially due to several reasons like inactivation of their DNA binding domain , inhibition of accessory proteins required by these transcription factors to bind to the MACC1 promoter , inhibition of phosphorylation of these transcription factors , or reduced localization of these transcription factors in the nucleus , which remains unexplored . However , within the scope of this study , we show that lovastatin interfered with the transcription factor binding to the MACC1 promoter and thereby impairing MACC1 transcription in CRC cells , without inhibiting the expression of these transcription factors . As mentioned above , inhibitors of transcriptional activity can act at many points in this process . To evaluate the mode of action of lovastatin , mevastatin , and rottlerin , which results in decreased binding of AP-1 to its specific binding site in the MACC1 promoter , we focused on a possible perturbation of the DNA-binding leucine zipper of AP-1 , as previously published [48] . By molecular docking of the identified transcriptional inhibitors of MACC1 , we found docking scores similar to substances that were screened to strongly inhibit AP-1/DNA binding activity [32] . Interestingly , the individual docking scores for the latter compounds inversely correlate with their published half maximal inhibitory concentrations ( 1 . 3 μM , 1 . 6 μM , 11 . 9 μM , and 16 . 2 μM , respectively ) [32] , indicating a relationship of docking score to inhibitory function , which can be extended also to the here reported transcriptional inhibitors of MACC1 . Furthermore , we analyzed the role of lovastatin as an inhibitor of MACC1-associated CRC progression and metastasis in mice . Our results demonstrate that lovastatin inhibits MACC1 expression at the site of the primary tumor in the spleen and intervenes with metastasis formation to the liver in the CRC xenografted SCID-beige mouse model . Thus , lovastatin application was effective to restrict cancer progression and metastasis formation in vivo . Recently , inhibition of tumor metastasis and growth by application of statins was also shown for metastatic melanoma via suppression of Rho signaling pathways [47] . Remarkably , in the molecular epidemiology of CRC study , including 1 , 953 patients with CRC and 2 , 015 controls , statin use was associated with a 47% decrease in the relative risk of developing CRC ( odds ratio , 0 . 50 ) [49 , 50] . Very recently , statin use was associated inversely with the risk of CRC in a large cohort of patients with inflammatory bowel disease ( odds ratio , 0 . 42 ) [51] . There have been numerous studies suggesting that statins can prevent CRC and prolong patient survival [47 , 49 , 52] . They may have an impact on the metastatic properties of CRC or may sensitize tumor cells to chemotherapeutic agents [53] . Despite all these studies , statins have failed to show improved outcome in clinical trials for CRC patients [54 , 55] . However , since almost 50% of CRC patients develop metachronous metastases , patient stratification based on the prognostic biomarker MACC1 might offer new options for subsequent therapy [56] . Thus , targeting MACC1 with drugs such as lovastatin might be meaningful as a prevention therapy to reduce the risk of metastasis development . Since statins are quite well tolerated by patients , they are promising drug-repositioning candidates for long-term treatment , with potential for the prevention/reduction of drug-mediated tumor progression and metastasis . Meanwhile , several other HMG-CoA reductase inhibitors of the statin family like simvastatin , pravastatin , fluvastatin , atorvastatin , cerivastatin , and rosuvastatin came into the focus [57] . Further studies with the new-generation statins are of great interest to find the most potent statin to restrict CRC progression via MACC1 expression inhibition . In the present study , we solely focused on lovastatin as an attractive candidate for drug repositioning in CRC therapy . We are certainly aware of the fact that lovastatin does not act exclusively via inhibiting MACC1 transcription . However , we demonstrated that treating different CRC cells with lovastatin led to significant reduction of MACC1 expression in concert with a reduction of various biological , MACC1-driven functions—most importantly , restricted metastasis formation . However , genes reported as lovastatin targets such as DNMT1 and MCM2 were not significantly regulated by lovastatin , whereas Col1A1 was significantly down-regulated . By contrast , HMGCR was up-regulated by lovastatin [58–60] . Further , since statins can be applied for years ( even decades with tolerable side effects ) , a long-term treatment might offer new possibilities for CRC patients . Thus , we provide a conclusive line of evidence that statins can be effectively repositioned as inhibitors of MACC1 , providing a novel therapy for effective metastasis prevention/inhibition in CRC with a promising future in clinics . In addition to lovastatin , HTS led to the identification of rottlerin as another potential candidate to inhibit MACC1 transcription . As proof of concept of HTS-based MACC1 inhibitor identification , we tested rottlerin in vitro and in vivo . We confirmed the ability of this drug for reduction of MACC1 promoter activity and expression in cell culture and metastasis restriction in xenografted mice . Unlike lovastatin , rottlerin treatment also affected primary tumor growth significantly in vivo . Although we demonstrated here that rottlerin is a MACC1 transcription inhibitor , rottlerin was shown to possess a wide range of other medicinal potential , including antitumor , antioxidant , antiamyloid , and antibacterial abilities , mitochondrial uncoupling , mTOR inhibition , and anti-inflammatory activities involving a plethora of cellular targets [61] . However , genes such as CDC20 , SKP2 , and mTOR were not found to be significantly modulated by rottlerin . Further , studies have shown that rottlerin has good systemic distribution and bioavailability and thus possesses a good potential for being an anticancer drug [29 , 62] . We confirmed here the good tolerability in vivo . Our data provide evidence for broadened use of rottlerin as an antimetastatic drug acting via another novel target , MACC1 , strengthening its future as a chemotherapeutic drug . Taken together , our study uncovers the first small-molecule inhibitors of MACC1-induced cancer progression and metastasis formation in vitro and in vivo , thereby suggesting their strong therapeutic relevance . This drug repurposing might benefit patients who are at high risk for shorter survival caused by MACC1-induced metastasis .
All experiments were performed in accordance with the United Kingdom Co-ordinated Committee on Cancer Research ( UKCCCR ) guidelines and approved by the responsible local authorities ( State Office of Health and Social Affairs , Berlin , Germany ) , REG0289/13 . Mice were anesthetized with isoflurane gas or Ketamin/Xylanzine . Animals were killed by cervical dislocation under anesthesia . Human CRC cell lines HCT116 , DLD-1 , SW620 , and SW48 , all originally from the American Type Culture Collection , were grown in DMEM or RPMI 1640 medium ( Thermo Fisher Scientific , Waltham , Massachusetts ) supplemented with 10% fetal bovine serum ( Thermo Fisher Scientific ) . All cells were maintained at 37°C in a humidified incubator with 5% CO2 . All cells tested negative for mycoplasma , verified regularly using the MycoAlert Mycoplasma detection kit ( Lonza , Basel , Switzerland ) . Authentication of the cell lines was performed by short tandem repeat ( STR ) genotyping at the Leibniz-Institute DSMZ ( Braunschweig , Germany ) . STR genotypes were consistent with published genotypes for these cell lines . The plasmid pGL4 . 17 ( Promega , Fitchburg , Wisconsin ) carrying the human MACC1 promoter sequence ( −18 to −992 bp upstream of the transcription start site ) upstream of the luciferase reporter gene has been described in our previous study [27] . HCT116 cells were transfected with this construct and selected with neomycin ( Thermo Fisher Scientific ) to generate HCT116-MACC1p-Luc cells . Stable expression of the transgene was controlled regularly by Steady Glow Luciferase Assay System ( Promega ) according to the manufacturer’s instructions . For ectopic CMV promoter-driven overexpression of MACC1 , the pcDNA3 . 1/MACC1 plasmid was used [63] . HCT116 cells were transfected with this construct to generate HCT116/MACC1 cells or with the empty pcDNA3 . 1 vector to obtain control HCT116/vector cells . Additionally , a CMV promoter-driven luciferase reporter HCT116 cell line ( HCT116-CMVp-Luc ) was used as described previously [64] . All transfections were performed with TransIT-2020 ( Mirus , Madison , Wisconsin ) according to the manufacturer’s instructions . Four thousand HCT116 cells stably expressing the MACC1 promoter-driven luciferase gene ( HCT116-MACC1p-Luc ) were seeded into each well of a white 384-well plate ( Corning , Corning , New York ) using an automatic pipetting system ( Tecan AG , Männedorf , Switzerland ) . For the HTS , a compound library consisting of 30 , 000 compounds from ChemBioNet , which also included 1 , 280 compounds of the LOPAC ( Sigma-Aldrich , St . Louis , Missouri ) , was used . The ChemBioNet collection of commercially available compounds has been provided by the Leibniz-Institute for Molecular Pharmacology ( FMP ) , in cooperation with the Max-Delbrück-Center for Molecular Medicine , the Helmholtz-Center for Infection Research , and the University of Konstanz . The design and selection of compounds is based on a maximum common substructure analysis of the World Drug Index ( WDI ) [30] . The collection is extended by the donations of academic chemists and natural product collection of about 20 , 000 compounds ( Analyticon Discovery , Potsdam , Germany ) . The HTS was carried out for 24 h at a concentration of 5 μM per compound . The luciferase signal was measured using a microplate reader ( Tecan ) . In parallel , a selectivity screen to eliminate general luciferase inhibitors was carried out using HCT116-CMVp-Luc cells . Compounds showing best selectivity and efficacy of MACC1 promoter inhibition were further used for a concentration-response screen at a concentration range of 0 . 025 μM to 25 μM . All measurements were made in triplicate . The parameters used in the screening are described in S1 Table . The results were calculated as percent luciferase activity compared to the respective controls . Mevastatin , lovastatin , and rottlerin were obtained from Santa Cruz Biotechnology ( Dallas , Texas ) and stored at −20°C . All drugs were solubilized in dimethyl sulfoxide ( DMSO ) for in vitro applications . The stock solution of 10 mM was prepared fresh every 2 wk and stored in small aliquots at −20°C to avoid repeated freeze thawing . To exclude adverse effects caused by DMSO , control cells were always treated with an equal amount of the solvent . In vivo , lovastatin hydroxyl acid ( sodium salt; Biomol , Hamburg , Germany ) and rottlerin were administered daily orally as a suspension in 10% Kolliphor EL ( Sigma-Aldrich ) and 0 . 9% NaCl using a gavage tube . Control mice were treated with the appropriate volume of solvent solution ( 10% Kolliphor EL , 0 . 9% NaCl ) . The in vivo experiments were terminated when the animals in the control group showed signs of increased suffering due to tumor/metastasis burden and liver damage like swollen abdomen ( ascites formation ) , reduced activity , and reduced food uptake ( ethical/humane endpoint ) ( S4 Fig ) . For expression analyses , 3x105 cells were seeded in a 6-well plate , and after drug treatment , total RNA was isolated using the Universal RNA Purification Kit ( Roboklon , Berlin , Germany ) according to manufacturer’s instructions . RNA was quantified ( Nanodrop , Peqlab , Erlangen , Germany ) , and 50 ng of RNA was reverse transcribed with random hexamers in a reaction mix ( 10 mM MgCl2 , 1x RT-buffer , 250 μM pooled dNTPs , 1 U/μl RNAse inhibitor , and 2 . 5 U/μl Moloney Murine Leukemia Virus reverse transcriptase; all from Thermo Fisher Scientific ) at 42°C for 15 min , 99°C for 5 min , with subsequent cooling at 5°C for 5 min . The cDNA was amplified by quantitative polymerase chain reaction ( qPCR ) using SYBR Green dye chemistry and the LightCycler 480 ( Roche Diagnostics , Mannheim , Germany ) under the following PCR conditions: 95°C for 2 min followed by 45 cycles of 95°C for 7 s , 60°C for 10 s , and 72°C for 20 s using primers for MACC1 and G6PD as described previously [1] . The primers are specific for the respective human gene ( S5 Fig ) . The same protocol for qPCR has been employed for RNA from shock-frozen tumor and liver tissue samples from animals . Human satellite DNA in the liver sections of the control and treated mice was determined as previously described [65] . Data analysis was performed with the LightCycler 480 Software release 1 . 5 . 0 SP3 ( Roche Diagnostics ) . Mean values were calculated from duplicate qRT-PCR reactions . Each mean value of the expressed gene was normalized to the respective mean amount of the G6PD cDNA . For total protein extraction , 3x105 cells were plated in 6-well plates . After drug treatment , the cells were lysed with RIPA buffer ( 50 mM Tris–HCl; pH 7 . 5 , 150 mM NaCl , and 1% Nonidet P-40 , supplemented with complete protease inhibitor tablets; Roche Diagnostics ) for 30 min on ice . Protein concentration was quantified with Bicinchoninic Acid Protein Assay Reagent ( Thermo Fisher Scientific ) , according to the manufacturer’s instructions . Lysates of equal protein concentration were separated with sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) and transferred to Hybond C Extra nitrocellulose membranes ( GE Healthcare , Munich , Germany ) . Membranes were blocked for 1 h at room temperature with 5% nonfat dry milk in TBST buffer ( 10 mM Tris-HCl; pH 8 , 0 . 1% Tween 20 , and 150 mM NaCl ) . Membranes were then incubated overnight at 4°C with MACC1 antibody ( Sigma-Aldrich , dilution 1:1000 ) or β-actin antibody ( Sigma-Aldrich , dilution 1:10 , 000 ) , followed by incubation for 1 h at room temperature with HRP-conjugated anti-rabbit IgG ( Promega , dilution 1:10 , 000 ) or anti-mouse IgG ( Thermo Fisher Scientific , dilution 1:10 , 000 ) . Antibody-protein complexes were visualized with WesternBright ECL HRP substrate ( Advansta , Menlo Park , California ) and subsequent exposure to CL-Xposure Films ( Thermo Fisher Scientific ) . Immunoblotting for β-actin served as the protein loading control . HCT116 cells were first serum starved overnight . Then , 3x105 serum starved cells in 300 μl of drug containing DMEM with 2% FBS were seeded into presoaked transwell chambers with a pore size of 8 μm ( Corning ) . The control cells were treated with solvent . Six hundred and fifty μl of fresh medium with 10% FBS and drug was added to the bottom chamber . The cells that had migrated to the lower chamber were stained with DAPI , and 4 random pictures per transwell were taken under a fluorescent microscope ( Axio Observer . Z1 , Zeiss , Jena , Germany ) . The migrated cells were counted manually from those pictures . Results are expressed as the percent number of migrated cells compared to controls . The wound healing assay was used to analyze directed cell migration . On day 0 , 5x104 cells were seeded into cell culture inserts ( ibidi , Martinsried , Germany ) to create a wound . After an attachment time of 24 h , the culture inserts were gently removed , and a wound of about 500 μm width was inflicted . Subsequently , medium containing the drug or solvent was added . The progress of wound closure was monitored daily , and microphotographs of 10x and 40x magnification were taken with the Leica DM IL light microscope ( Leica Microsystems , Heerbrugg , Switzerland ) from day 0 up to day 2 . Results were quantified using ImageJ 1 . 48v ( NIH , Bethesda , Maryland ) and the MRI wound healing tool ( available online ) as relative residual wound size compared to starting day 0 . Each wound healing assay was performed in duplicate . For determination of cell viability and proliferation , 4x103 cells were plated into 96-well plates and were allowed to accommodate for 24 h before treatment was started . Cells were treated daily for 4 d with inhibitor or solvent . For determination of viable cells , 3- ( 4 , 5-dimethylthiazol-2-yl ) -2 , 5-diphenyltetrazolium bromide ( MTT; Sigma-Aldrich ) was added to a final concentration of 0 . 5 mg/ml and incubated for 3 h at 37°C in a humidified incubator . MTT was reduced to purple formazan crystals by the mitochondria of living cells , and the decrease in metabolized MTT represented decreased cell viability and number . Formazan crystals were dissolved in 150 μl of DMSO , and the absorption was measured at 560 nm in the multiwell reader ( Tecan infinite 200 PRO , Tecan ) . Each cell proliferation experiment was performed in triplicate . Results are expressed as percent viable cells compared to solvent-treated controls . A ChIP assay was performed using EZ-Magna ChIP kit ( Merck , Darmstadt , Germany ) as per the manufacturer’s instruction . Cells ( 2x106 ) were plated in 10-cm dishes . Twenty-four hours after drug treatment , the cells were cross-linked with 1% formaldehyde for 10 min at room temperature , lysed in the lysis buffer provided in the kit , and sonicated for 25 pulses at 40% output to release chromatin . Cell lysates were then centrifuged at 10 , 000 rpm for 10 min , and supernatant was collected in a new tube . One percent of this solution was stored at 4°C until the elution step and served as an input control . The protein-DNA complexes were precipitated on addition of polyclonal antibodies for c-Jun or Sp1 ( Cell signaling , Danvers , Massachusetts ) to the chromatin solution and incubated overnight at 4°C . Magnetic beads were then added and incubated for another 2 h at 4°C . Nonbound protein was removed by washing twice with the Wash Buffers provided in the kit . The protein-DNA complex was eluted from the beads with the elution buffer , followed by centrifugation at 3 , 000 rpm for 1 min . Cross-linking of protein and DNA was reversed at 68°C overnight , and residual protein was digested by proteinase K at 55°C for 2 h . DNA was purified by column purification . The extracted DNA was subjected to quantitative PCR as described above with the MACC1 promoter primers described before [27] . EMSA was performed using the LightShift Chemiluminescent EMSA Kit ( Thermo Fisher Scientific ) as per the manufacturer’s instruction . Briefly , 2x106 cells were seeded in a 10-cm culture dish and incubated for 24 h for cell adherence . Twenty-four hours after drug or solvent treatment , nuclear extracts were prepared using NE-PER nuclear and cytoplasmic extraction reagent ( Thermo Fisher Scientific ) as per the manufacturer’s protocol . As described earlier , 5′-labeled biotin oligonucleotides for the putative binding sites for c-Jun and Sp1 in the human MACC1 promoter were used [27] . In a total volume of 20 μl , 5 μl of nuclear extracted protein was incubated for 30 min at room temperature along with 0 . 05% w/v poly dI·dC , 0 . 5 mM Tris , 0 . 05 mM EDTA , 2 . 5% v/v glycerol , 0 . 2% v/v NP-40 , 5 mM MgCl2 , and double-stranded biotinylated oligonucleotides containing the respective transcription factor binding site as present in the MACC1 promoter . For the super shift assay , 5 μg c-Jun or Sp1 antibody was added before the addition of the corresponding oligonucleotide and incubated for 30 min on ice , whereas 100-fold molar excess of unlabeled oligonucleotides was used in the competition experiments . Electrophoretic separation of the protein-oligonucleotide complexes was performed by precast Novex 6% TBE gels ( Thermo Fisher Scientific ) in TBE buffer ( 45 mM Tris , 45 mM boric acid , 1 mM EDTA , pH 8 . 3 ) for 60 min at 100 V . Capillary transfer of the protein-oligonucleotide complexes to the Hybond-N nylon membrane ( GE Healthcare ) was performed in 20x SSC buffer ( 3 M NaCl , 300 mM Na3C6H5O7 , pH 7 ) overnight . Transferred DNA was cross-linked to the membrane at 250 mJ/cm2 for 1 min in the FL-20-M FluoLinkCrosslinker ( Bachofer , Reutlingen , Germany ) . Visualization of biotin-labeled DNA was performed with the LightShift Chemiluminescent EMSA Kit ( Thermo Fisher Scientific ) according to the manufacturer’s instructions . Searching in the protein database ( PDB ) [66] for the transcription factor AP-1 results in 4 crystal structures and 1 NMR structure . To evaluate which structure might be most suitable for docking studies , a superposition of these 5 PDB entries was performed using PyMOL , an open-source and widely used biomolecular visualization program [67] . Based on the resulting superpositions , we decided to use the PDB structure 1S9K for further evaluation . To prepare the small molecules for docking , Discovery studio 4 . 1 was used [68] . This process comprises adding hydrogens , normalizing the ionization state , generating possible tautomers , fixing valencies , and generating three-dimensional coordinates . Additionally , a minimization step was applied to generate low-energy conformers , by applying the Smart minimizer . Docking studies were carried out by using GOLD suite 5 . 2 [69] with the Goldscore scoring function , where the integrated wizard was used to set up and run the docking . The first step comprises the preparation of the protein . Therefore , hydrogens were added , water and possible side chain rotamers were removed , and the cocrystallized DNA was excluded . We focused on a possible inhibition of the AP-1/DNA interaction to identify any drug binding site and defined a radius of 12 angstrom around the AP-1/DNA interacting atoms to cover the complete binding area . Additional options , like protein and ligand flexibility , were kept in default configuration . All experiments were performed in accordance with the UKCCCR guidelines and approved by the responsible local authorities ( State Office of Health and Social Affairs , Berlin , Germany ) . HCT116-CMVp-Luc cells ( 3x106 cells/animal ) were intrasplenically transplanted into 6-wk-old female SCID-beige mice ( Charles River , Wilmington , Massachusetts ) . SCID-beige mice were randomly assigned 24 h after cell transplantation to 2 groups of 9 animals each . Mice were then treated orally with daily doses of either solvent ( 10% Kolliphor in 0 . 9% NaCl ) or 100 mg/kg body weight of lovastatin hydroxyl acid or rottlerin for up to 4 wk . Tumor growth and metastasis formation were monitored by bioluminescence imaging using the NightOWL LB 981 imaging system ( Berthold Technologies , Bad Wildbad , Germany ) . For bioluminescence imaging , mice were anesthetized with isoflurane gas and received intraperitoneally 150 mg/kg D-luciferin ( Biosynth , Staad , Switzerland ) . Tumor growth and metastasis formation were imaged and quantified by WinLight ( Berthold Technologies ) and ImageJ 1 . 48v . The experimental endpoint was defined by ethical guidelines of animal care ( S4 Fig ) . After the animals were killed , the spleen ( the tumor implantation site ) and the liver ( the metastasis target organ ) were removed and shock frozen in liquid nitrogen , and cryosections were performed for isolation of genomic DNA and total RNA ( DNA/RNA/Protein extraction kit , Roboklon ) for further analyses . All calculations and statistical analyses were performed with GraphPad Prism version 5 . 01 . Comparison of the 2 groups was done by an unpaired t test . Comparison of a control versus multiple respective treated groups was performed by one-way analysis of variance ( ANOVA ) Dunnett’s multiple comparison test . All significance tests were 2-sided , and p-values less than 0 . 05 were defined as statistically significant .
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Cancer is still one of the leading causes of death in the Western world , and metastasis—the spread of cancer to distant sites—represents the most critical attribute for therapy failure . In colorectal cancer , up to one-third of patients have already developed metastasis at the time of diagnosis , and about half of newly diagnosed patients will develop metastasis during the course of the disease . MACC1 was first described as a key driver of metastasis formation in colorectal cancer , and its importance was later confirmed for other solid tumor entities . Stratification of patients with high MACC1 expression identifies patients at high risk of developing metastasis . Here we present a mechanism of targeting MACC1 as a potential therapy option for these high-risk patients . We identify the small molecules lovastatin and rottlerin as transcriptional inhibitors of MACC1 . We describe the mechanism by which these molecules inhibit MACC1 expression and show that MACC1 inhibition leads to a reduced migratory phenotype in vitro and limits metastatic spread in preclinical mouse models . We propose repositioning of these 2 known drug molecules to reduce MACC1-driven metastasis formation in high-risk patients even before metastatic spread is clinically evident .
|
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2017
|
Statin and rottlerin small-molecule inhibitors restrict colon cancer progression and metastasis via MACC1
|
An explanatory computational model is developed of the contiguous areas of retinal capillary loss which play a large role in diabetic maculapathy and diabetic retinal neovascularization . Strictly random leukocyte mediated capillary occlusion cannot explain the occurrence of large contiguous areas of retinal ischemia . Therefore occlusion of an individual capillary must increase the probability of occlusion of surrounding capillaries . A retinal perifoveal vascular sector as well as a peripheral retinal capillary network and a deleted hexagonal capillary network are modelled using Compucell3D . The perifoveal modelling produces a pattern of spreading capillary loss with associated macular edema . In the peripheral network , spreading ischemia results from the progressive loss of the ladder capillaries which connect peripheral arterioles and venules . System blood flow was elevated in the macular model before a later reduction in flow in cases with progression of capillary occlusions . Simulations differing only in initial vascular network structures but with identical dynamics for oxygen , growth factors and vascular occlusions , replicate key clinical observations of ischemia and macular edema in the posterior pole and ischemia in the retinal periphery . The simulation results also seem consistent with quantitative data on macular blood flow and qualitative data on venous oxygenation . One computational model applied to distinct capillary networks in different retinal regions yielded results comparable to clinical observations in those regions .
VEGF is a factor with a long history . First identified as a vascular permeability factor [30 , 31] , it has become clear over time that it has other important roles as a factor in angiogenesis [32] , endothelial cell proliferation [33] , and also as a neuroretinal protective factor [34 , 35] . While we do model retinal edema [36] the important property of VEGF for this model is its role a mediator of elevated ICAM-1 on retinal endothelial cells . In our model of progressive capillary occlusion , VEGF is the locally secreted molecule which diffuses and increases the likelihood of nearby capillary occlusion . As this pro-occlusive property is not as well-known and even possibly denied by some , we provide below the background supporting our choice of VEGF as a substance responsible for the adverse cycle of capillary occlusion . This does not mean VEGF is by any means the only cytokine involved or that there is not an intervening cascade of events that generate the chronic inflammatory state that is diabetic retinopathy . Leukostasis is mediated by the diabetic activation of circulating leukocytes co-existing with marked upregulation of adhesion molecules such as ICAM-1 on the retinal vascular endothelium [37] . These changes increase the likelihood of leukocyte adhesion to the retinal capillary endothelium and therefore the probability of capillary closure . The model does not detail the local , undoubtedly complex , phenomena such as the cumulative leukocyte mediated endothelial capillary damage resulting in endothelial replicative exhaustion culminating in capillary occlusion; they are treated as black boxes at this time . The model treats elevation of one substance for simplicity though likely the relative amounts of two substances , such as the balance of VEGF and pigment epithelium derived factor ( PEDF ) , is what is often physiologically important [38] . PEDF itself has complex neurotrophic , neuroprotective , and anti-angiogenic , anti-exudative and anti-inflammatory properties [39 , 40] . High glucose decreases expression of PEDF in retinal Mueller cells as it simultaneously elevates VEGF expression . Additionally vitreous levels of PEDF are significantly lower in patients with diabetic macular edema or proliferative diabetic retinopathy than in non-diabetic patients or diabetic patients without retinopathy whereas in each situation VEGF is elevated . The model simplifies this duality by treating the physiological import of an imbalance as simply the concentration of VEGF . Certain steps in the progressive ischemic process must be met by a diffusible substance and ideally we need to have anatomical and physiological support for each of the steps in the model if we are to model the substance as VEGF . The local adverse positive feedback model could stand on its own dealing only with the problem of diabetic ischemia as a geographic phenomenon but it is more constructive to have model elements that correspond as closely as possibly to biological elements . We now construct a simple biological model based on the observation that this substance is required to have a number of physiological properties which first create the permissive diabetic state of recurrent capillary endothelial cell loss by activated leukocytes , leads to permanent capillary occlusions from local endothelial depletion , and which in turn produces geographic propagation of capillary occlusions . This progression requires a substance , modelled as VEGF , and the retinal tissue to have the following characteristics:
The protocol for AOSLO imaging used to provide retinal vascular images used in this study was approved by the Indiana University Institutional Review Board and adheres to the tenets set forth in the Declaration of Helsinki and the Health Insurance Portability and Accountability Act regulations . Written informed consent was obtained from all subjects . To capture the events of progressive capillary occlusion we implemented a quantitative model of the anatomical features mentioned above in Compucell3D [98] . As shown in Fig 2 , beginning with an AOSLO scan of the perivascular fovea , a full vascular model from an arteriole to a venule with the linking capillaries is included with oxygen advection , oxygen diffusion , and oxygen consumption . This paper develops a conceptually simple model of the diabetic retina treating Mueller cells as the sole retinal source of VEGF and assumes a slight elevation of VEGF production by Mueller cells in a diabetic retina higher than that in the normal retina [99] . Physiologically VEGF is a necessary neurotrophic factor in the retina and is normally present at low levels [100–102] . In the model VEGF is produced by Mueller cells locally in variable amounts based on oxygen saturation . VEGF diffuses from the Mueller cells and is consumed by cells including endothelial cells but is not transported away by advection . The model vessels have endothelial cells which respond to local VEGF levels by an increased probability of occlusion with elevation of local VEGF and also by leaking if local VEGF exceeds a threshold level . The model is cycled many times and if a capillary occlusion occurs , all flow rates , steady state oxygen tension and VEGF levels are recalculated . The model’s treatment of occlusion is an irreversible decrease of capillary diameter to zero . An important assumption is that the vascular supply to each area of retina is critical in that occlusion of a capillary will result in ischemia of an area of physiologically dependent retina with a resultant elevation of VEGF synthesis by the locally ischemic Mueller cells . We do not know that this has been proven but the constraints imposed by evolution on the visual apparatus make this assumption reasonable . To quote Chan et al . 2012 [102] “It is likely that retinal capillary networks are morphometrically adapted in order that the balance between cellular nutrition and optical clarity can be achieved . ” Note , however , that with the variations of capillary spacing seen anatomically , all areas of retina would not have equal dependence on a single supplying capillary . In a network based on actual capillary anatomy different areas of retina could be more or less critical as a result of variation in local capillary density . There would thus be greater or lesser propagation of capillary closure by the adverse feedback mechanism . Small capillary diameter adjustments can also occur , e . g . slightly increasing diameter with increased flow after each capillary occlusion . Maps at various model times are made of capillary network structure , flow , oxygen tensions , VEGF , and retinal edema . These are the output measures as well as summary graphs of the system such as total flow and average distance from an intact capillary . Model capillary occlusions are always probabilistic based on local VEGF levels and the calculated flows of the capillary segments . Capillary networks of several types were utilized including physiologically unlikely hexagonal capillary network with introduced deletions , physiologically realistic peripheral retinal ‘ladder’ capillaries [103] and an actual perifoveal arteriovenous sector capillary map obtained from adaptive optics scanning laser ophthalmoscopy ( AOSLO ) imaging of a subject . The hexagonal map was used to explore the dependence of capillary occlusion progression on amount of tissue dependent on capillaries by varying the scale of the hexagons . Both the macula and the peripheral retina are clinically important , with the macular area being the location of ischemia as well as macular edema affecting visual acuity , and the periphery being the major source of the ischemia and resultant VEGF production which results in retinal neovascularization . Though it is not clear if it is physiologically appropriate to utilize the same fundamental model parameters for the macula and periphery given the distinct peripheral retinal and vascular architecture [103 , 104] we altered only the capillary diameters and network structures . In the main text we address primarily a sector of the perifoveal capillary network from AOSLO imaging ( CASE 1 ) and filled the open space between vessel segments with cells of anatomically reasonable sizes ( S4 Table ) . Capillary diameters were estimated based on the AOSLO image . Model inputs such as terminal hydrostatic pressure and arteriolar blood oxygen tension were estimated from published results ( S4 Table , S15 Fig ) . Vascular flows , oxygen and VEGF fluxes were calculated and resulting tissue oxygen tension and VEGF levels were determined in the model . A large number ( 362 ) of replicate runs were made of the subject’s capillary network in order to assess the vulnerability of distinct capillaries given the probabilistic nature of the model of individual capillary occlusion . S1 Text details mathematical descriptions , parameter selection and influence and boundary and initial conditions of the model . S2 Text briefly treats a run of the model in the macular area with a different initial capillary occlusion ( CASE 2 ) . S3 Text treats a hexagonal network with some deleted edges , and S4 Text treats a peripheral schematic ladder capillary network modelled on that of the peripheral human retina . The peripheral ladder capillary network seen in the peripheral retina has significant implications about the development of the peripheral ischemic wedge-like sectors seen clinically between arterioles and venules whereas the hexagonal model was informative about the dependence of capillary occlusion propagation on distance between capillaries . Many models have been constructed to study problems at the interface of vasculature in various tissues: skeletal muscle [105 , 106] , brain [107 , 108] , vascular tumor [109 , 110] and retina [111] . Shirinifard et al . employed a 3D multi-cell model to successfully recapitulate the three patterns of progression of age-related macular degeneration and suggested that defects in adhesion were the dominant contributor to initiation and development of choroidal neovascularization [111] . Cringle et al . divided retina into multiple layers and used a mathematical model to calculate the oxygen tension in each layer in terms of oxygen consumption rate in that layer and the oxygen level in choroidal capillaries [112 , 113] . McDougall et al . studied angiogenesis during normal retinal development using a hybrid discrete-continuum mathematical model and computationally simulated the structure of a retinal vascular plexus that agreed with the whole-mount retinal vasculatures at different stages of development [114] . Our model deals with a different pathophysiological issue: progression of ischemia and edema in diabetic retinopathy based on a local VEGF-dependent mechanism of propagation of capillary occlusions . Unlike this study , Gandica et al . [115] developed a computational model of retinal ischemia studying the effect of critical sizes and densities of localized blockages of retinal vasculature on the emergence of diabetic retinopathy . In their model , various sizes of local blockages of vessels , assumedly caused by destabilizing proteins such as Angiopoietin-2 , were randomly distributed in the region of interest and areas of derived hypoxia were examined regarded as an indicator of potential phenotypes of diabetic retinopathy . An important conclusion in their study is that local blockages with smaller size than characteristic irrigation length , if their densities exceed a critical threshold , likely result in large hypoxic areas because of a cooperating effect . A limitation of the model , as the authors also noted , is the simplified consideration of oxygen transport . To ensure that we respect the specific geometry of the retinal capillary network , we use networks from actual subject imaging or from peripheral retinal capillary networks in the literature and were therefore not created for these modelling purposes . Also the oxygen diffusion coefficient was taken from the literature . In this study , we explore the effect of focal capillary occlusion on decreasing local oxygenation of retinal cells , resultant elevation in VEGF , and the consequences in terms of propagation of capillary occlusions and formation of edema using a computational model . The anatomy of this capillary network was determined from a normal patient using AOSLO ( Fig 2 ) . This network is an arteriovenous sector with the capillaries connecting the arteriole and venule , the foveal avascular zone on one edge and retinal tissue on the other borders . We computationally reconstruct the network and initialize the simulation with boundary blood pressures and arterial and FAZ oxygen tension ( Fig 2 ) . The major entering arterial node and the exiting venous node are assigned with blood pressures Pbart and Pbven respectively . These pressures would not be expected to depend on the diabetic state and remain fixed . Other boundary nodes are assigned with blood pressures of intermediate values ( S15 Fig , also see Boundary conditions and initial state of simulation in S1 Text for details ) . The FAZ region is treated as an oxygen source , supposedly supplied by choroidal capillaries . The entering arterial node and the FAZ region are assigned with oxygen tension PO2art and PO2faz though the exiting venous oxygen tension is model dependent . Other boundary nodes with incoming blood flow are assigned with oxygen tensions of smaller values ( S15 Fig ) . Hypoxia-induced elevated secretion of VEGF in Mueller cells is known as an occurrence in diabetic retinopathy [115–117] . FAZ region is treated as a sink for VEGF . We modelled the oxygenation and local VEGF levels within this retinal sector following a focal capillary obstruction . Within the sector of capillary network modeled , the arterial side receives oxygen-rich blood , while from the venous terminus carries away blood with lower oxygen tension . Oxygen diffuses into tissue space from capillaries , where it is consumed and metabolized by retinal cells . Hypoxia of local retinal tissue is induced by a local capillary segment occlusion , and production of local VEGF , dependent on the level of hypoxia is upregulated in ischemic Mueller cells . VEGF released by Mueller cells diffuses to other nearby patent capillary segments , which probabilistically derive more occlusions based on an underlying and not visibly modelled upregulation of ICAM and increased probability of leukostasis . The schematic of oxygen and VEGF fluxes is shown in Fig 3 . The described computational model consists of four generalized model cell types: capillary block ( CAP ) , fluid portion ( FP ) , Mueller cell ( MC ) and other retinal cell ( OT ) . Along with these four generalized cell types in the model is another model object called the conveyor-belt block , CB , which is an object associated with the capillary block and introduced for modeling of oxygen advection . In addition to five model objects , two chemical fields exist in the model: oxygen and VEGF . Modeled processes include advection of blood carrying oxygen , diffusion and metabolism of oxygen , and synthesis , diffusion and decay of VEGF . As detailed in S1 Text and summarized in S1 Table , model objects have the following properties and are representative of various retinal cells: To model oxygen advection , we discretize each capillary segment into a one-dimensional sequence of equally-sized CBs and simulate oxygen advection using a “conveying” action , which moves a volume of oxygen in a given CB to its next downstream connected CB ( Fig 4 ) . The size of a CB is proportional to both flow velocity and the time step for advection . In the case of merging at a junction , total oxygen volumes in last CBs of the predecessor capillary segment are conveyed to the first CB of the successor capillary segment ( Fig 4 ) . In the case of branching at a junction , conservation of blood flow is enforced to appropriately distribute the oxygen volume in the last CB of the parent capillary segment to the first CB of the daughter capillary segments ( Fig 4 ) . Mathematical descriptions were detailed as equations ( 9 ) - ( 11 ) in S1 Text . The benefit of the conveyor-belt model of oxygen advection is the flexibility of adjusting the number of CBs in a CAP without interference with oxygen diffusion . When occlusion occurs , flow velocities change on the capillary network and accordingly the size and number of CB on a CAP also change . This alters the discretization for oxygen advection , but the module of oxygen diffusion remains unaffected . A simple rule is followed to associate a CB with CAP: a CB is associated with a CAP if the CB’s center is enclosed by the CAP’s volume . Then , the following sequence of processes is used to link modules of advection and diffusion: ( 1 ) oxygen advection in CBs on each capillary segment at time step t0; ( 2 ) conversion of oxygen volume from CB-level to CAP-level just before diffusion at time step t0; ( 3 ) oxygen diffusion involving CAPs and their surrounding objects at time step t0; ( 4 ) conversion of oxygen volume from CAP-level to CB-level just before advection at time step ( t0 + Δtf ) ( Fig 5 ) . ( More details on the CB model of oxygen advection are in S1 Text ) . To model diffusion of a chemical field , we assume that each generalized cell has a uniform intra-cellular chemical concentration and that diffusion occurs at the interface between neighboring cell pairs . Metabolism of oxygen and synthesis and decay of VEGF are modeled as an intra-cellular process ( Fig 3 ) . As for diffusion , the rate of exchange of oxygen or VEGF between generalized cells is proportional to inter-cellular gradient of concentration and inter-cellular contact surface area . Metabolism of oxygen obeys Michaelis-Menton kinetics , which assumes variability of oxygen consumption given different intracellular oxygen tension . Synthesis of VEGF in hypoxic MC is dependent on intra-cellular oxygen tension and VEGF level . Decay of VEGF is modeled using first-order kinetics . FAZ region is treated as both an oxygen source and a VEGF sink . ( Details on oxygen and VEGF fluxes in S1 Text ) Our simulation involves three distinct intervals of time: the time step of integration for oxygen and VEGF flux , Δtf; the time interval to check edema formation , Δte; and the time interval to check for occlusion , Δto . The Δtf is chosen so that the differential equations of fluxes are properly integrated . In contrast , Δte and Δto are selected so that possible edema formation and capillary occlusion take place at a significantly slower pace ( months to years ) , as compared with fast establishment ( seconds ) of the oxygen and VEGF steady state following a newly derived occlusion . With Δtf = 0 . 002s , Δte = 7 days , Δto = 28 days , a model workflow is shown in Fig 6 . The time for oxygen and VEGF steady state is basically mandated by physics whereas the other longer times for edema and capillary occlusion are chosen to allow the model to progress in rough accordance to the progression of clinical disease .
It is important to maintain perspective regarding the model . While we initially present results in terms of an example run of the model , CASE 1 , as explained below , the model was run many times to explore the impact of the implemented stochastic events . The configuration of cells and vessels has been initialized for a sector near the FAZ with dimensions of 510μm × 600μm × 50μm , as determined from a patient ASOLO image . The sector during initialization is viewed in 3D with CAPs and MCs visualized ( Fig 7A ) . Completely initialized configuration shows that MCs and OTs are uniformly patterned between vessels from a 2D view ( Fig 7A ) . Under normal conditions , the blood flow is sourced from the arteriolar entrance , flows through the capillary network and exits via the venule . Because the model concentrates on a small arteriole-venule sector , side streams reflect capillaries connecting neighboring peri-foveal networks ( Fig 7B ) . Capillaries near the FAZ carried a relatively small blood flow , and therefore had a higher probability of occlusion based on the assumed occlusion mechanism . Cells near capillaries had abundant oxygen supply , while more distantly situated cells received less , but still sufficient , oxygen to support normal activities without ischemia ( Fig 7C ) . In the initial state VEGF production was assumed to be in the basal diabetic physiological range when retinal tissue was adequately oxygenated ( Fig 7D ) . This corresponds to a slight elevation of VEGF above the basal non-diabetic state; an elevation sufficient to induce the presence of a low level of ICAMs allowing diabetes induced leukostasis . Once a first occlusion was initiated , the network topology changed reflecting the loss of that capillary and the steady state of oxygen tension and VEGF level were reestablished accordingly ( Figs 8–10 ) . In week 0 , a capillary was occluded ( Fig 8A ) and consequently tissue surrounding it became poorly oxygenated ( Fig 9A ) . Within the model , the date of first capillary occlusion is always week 0 . This is not the date of the initiation of diabetes . Certain Mueller cells become ischemic from this capillary occlusion and these hypoxic Mueller cells produce and release VEGF , which then develops local concentration peaks ( Fig 10A ) . Adjacent capillaries respond to the elevated concentration of VEGF , which increased their risk of occlusion via the ICAM mediated leukostasis mechanism not addressed separately in the model . Due to limited diffusion length of VEGF , distant capillaries are insensitive to such localized change . In week 72 , secondary occlusions took place and the flow network became increasingly impaired ( Fig 8B ) . Consequentially , more Mueller cells had an insufficient oxygen supply and produced increased levels of VEGF ( Figs 9B and 10B ) . At this point , the capillary damage appeared well bounded and confined in one arteriolar-venular sector . Notably , several cells in a neighboring area became hypoxic and produced elevated VEGF , possibly because their nearest vessel lost an important upstream branch , which carried significant oxygen supply before closure . However , there were still barriers composed of healthy cells and capillaries between the adjacent sectors . There then followed a series of capillary occlusions with minor enhancement in total volume inflow rate , until the damage in week 124 resulted in drop of inflow rate the first time since onset of initial injury ( see below ) . Concomitant with the drop in total flow , the terminal venule between the two sectors was compromised ( Fig 8C top of image ) and a larger fraction of tissue was now hypoxic ( Fig 9C ) . In week 152 , capillaries near the FAZ and the terminal venule were no longer patent ( Fig 8D ) , the FAZ is considerably enlarged , and roughly one third of the tissue was hypoxic and had an elevated VEGF environment ( Figs 9D and 10D ) . We note that Sakata et al . 2006 [118] using a fluorescein angiography technique to measure perifoveal capillary blood velocity were able to show a significant negative correlation between capillary blood flow velocity and the size of the foveal avascular zone in diabetics without edema . In the model , capillaries bordering the avascular zone show slowed flow consistent with Sakata et al . results [118] . Based on simple assumptions on the mechanism of edema formation ( detailed in Edema Formation section in S1 Text ) , our model showed local retinal thickening ( Fig 11 ) . A significant volume of fluid was observed 3 years post onset of initial capillary occlusion ( Fig 11D ) . Extravascular fluid was responsible for the increase in retinal thickness . Moreover , the spot where fluid was present correlated with the boundary of the ischemic region . The current study is limited to qualitative illustration of how retinal thickening can be caused by abnormal VEGF synthesis by Mueller cells . This is the canonical function of VEGF producing leakage from capillaries . In the model edema is only a function of threshold VEGF levels and not a measure of local Starling type relationships . It is reflective within the model of loci of active leakage at sites of intact , non-occluded capillaries which also have elevated VEGF above a particular threshold . Edema within the model is a prediction of expected locations of either retinal thickening or of retinal cystic structures as seen clinically on ocular coherence tomography . The model does not address the actual range of cysts since these can often be present in areas of retinal ischemia lacking active leakage by fluorescein angiography [12] and thus can represent processes other than active leakage such as cellular necrosis or impaired retinal pigment epithelial pumping . The model does leave cysts present in areas in which capillaries had leaked but then subsequently become occluded similar to what occurs clinically . Following the onset of capillary closure , almost every additional occlusion caused average oxygen tension within cells to drop ( Fig 12A ) . The fraction of hypoxic Mueller cells went up nearly linearly from week 72 to week 152 ( Fig 12B ) . Distinct from the monotonic change in average oxygen tension and hypoxic fraction , the total volume inflow rate was non-monotonic , with continuous increases before a sharp decrease in week 124 and one more in week 152 ( Fig 12C ) . Early stages of increased inflow rate might be attributed to physiological response to loss of a selected group of blood flow pathways . Because oxygen tension is assumed to be constant within inlet capillary blocks , as would be physiologically expected , a higher volume inflow rate gives more oxygen carried into the system within a given period of time . This might suggest that at early stages of the disease with few capillary closures , the system would compensate for the oxygen insufficiency by increasing the blood flow . In contrast , at later stages of disease when many capillaries connecting the arteriole to the venule were occluded , total flow declined and occlusions seemed to occur more frequently . To better map the model to clinically observed symptoms , our model used the scaled minimal cell-to-vessel distance dmin / aMC as a metric to quantify disease progression spatially , where aMC is the typical size of a Mueller cell ( Fig 12D ) . This is basically the number of Mueller cell diameters to a patent , or unoccluded , vessel . The dmin / aMC increased monotonically with each additional capillary closure . Interestingly , the capillary occlusion that triggered a rapid drop of the total volume inflow at week 124 had a mild effect on dmin / aMC . This implied that topological location of a capillary segment was influential to the system blood flow supply , which might be neglected in a spatially-based metric . Thus , a flow-based model may be helpful in understanding the critical point at which the disease starts to evolve in a different way i . e . toward a decline in total inflow . The distribution of oxygen tension within all cells exhibited an essentially unimodal shape under the normal condition where most cells had oxygen tensions of 10 to 25 mmHg , a small portion of cells located near vessels had higher levels ranging from 35 to 40 mmHg ( Fig 13 ) and no cells had an oxygen tension less than 4 mmHg O2 , i . e . no cells were ischemic . Capillary occlusions induced by elevation of VEGF gradually altered the distribution . An increasing number of cells turned hypoxic . The broad peak of cells at moderate levels of oxygen decreased and broadened with more cells both at lower oxygen levels and more cells from about 25–30 mmHg . This suggests that while the size of the hypoxic region in this tissue section was growing larger more cells were exposed to high oxygenation producing a bimodal oxygenation distribution . This model’s results are important both in terms of the images produced which bear a striking resemblance to those seen clinically and also as summarized in graphs showing changes occurring over time in a single run of the model for a specific initial capillary closure ( Figs 8–13 ) . Are these images and graphs consistent with what is known clinically about diabetic retinopathy ? The pattern of capillary loss near the FAZ with expansion over time is very similar to what is seen in diabetic patients . The pattern of mixed ischemia and edema in the perifoveal area is also that usually seen clinically . The curve in Fig 12C is the most interesting in that flow rises from baseline levels for a period of time by as much as 13 percent and then declines . Clearly in end stage diabetic retinopathy with the entire capillary network occluded , the flow will go down . It is less clear that earlier stages in loss of the capillary network will result in increased total flow . This occurs because the model has some dilation of capillaries as a consequence of the adaptation module which would increase flows and also partially due to changes in network structure . The literature on blood flow in diabetes has been inconsistent due to measurements on diabetics at different stages of disease with a number of different technologies imaging flow in different locations [119] . The data from the Retinal Function Imager ( RFI ) measures flow velocities in small perifoveal vessels and seems most comparable to the vessel sizes in the model . This data is consistent with the model in that it shows an increased retinal blood flow velocity in diabetic patients without clinically seen morphological changes [119] . This would be similar to patients in the first year or two of the simulation ( approximately 100 weeks ) . The percent increase in blood flow over controls was about 15% in [119] , quantitatively similar to the model’s results . Physiologically this is possibly secondary to increased vasodilator mechanisms due to tissue hypoxia [120] and increased nitric oxide synthase [121] and possibly network changes which could have occurred even though the patients did not have clinically visible changes . The model replicates this effect though it does not explicitly utilize any analogous mechanisms . This pattern of increased macular blood flow accompanied by edema ( Fig 11 ) is consistent with the regional distribution of diabetic lesions emphasized by [28] . Burgansky-Eliash 2010 has RFI data on patients with non-proliferative diabetic retinopathy [122] which show decreased blood flow at this stage of clinical retinopathy comparable to the blood flow decrease seen in the later weeks of this simulation . There is also clinical data on venous oxygen saturation in diabetes [123] showing that venous oxygen saturation in diabetes is elevated over that seen in normals . This model did not specifically treat venous oxygen levels but as blood flows were rising with a constant input oxygen saturation occurring simultaneously with a rise in hypoxic retinal cells , retinal oxygen extraction must be lower resulting in elevated venous oxygen saturation . The oxygen map shows this qualitatively as an expanded reddish tissue area ( top right corner near “V” Fig 9C vs 9A ) of elevated oxygen saturation around the venule . Hammer et al . ( 2009 ) interpret this elevation in venous oxygen levels to be due to a shortened arterio-venous passage time resulting in reduced oxygen extraction [123] . We performed 362 replications of the macular capillary sector simulation on Indiana University’s supercomputer BigRed II to pursue the consequences of different initial occlusion sites and explored the evolution of progression states in a flow-oxygen phase diagram ( Fig 14 ) . The probabilistic aspect of the capillary occlusions means that repeated runs of the model will not produce identical patterns of capillary loss but similarity of replications will be strongly influenced by network structure . In the flow-oxygen phase diagram , the normal condition ( circles in dark blue ) were clustered in a confined range , which showed that all simulations had similar equilibrium oxygen tension and total inflow rates initially as expected ( Fig 14A ) . Circles gradually became scattered , because different simulations randomly picked different occlusion sites resulting in different disease progression trajectories . At 156 weeks , most simulations landed not far from the initial oxygen-flow states , which corresponded to situations without derived occlusions . On the contrary , some simulations showed distant end-point states situated mainly in low oxygen territory , which represented exacerbating progressive capillary occlusions . Of all such simulations , temporal trajectories were visualized ( Fig 14B ) if the simulations showed less than 75% total inflow rate or oxygen tension in year three . Most such simulations followed a clockwise trajectory temporally , starting from equilibrium state , transiting via low-oxygen and high-flow zone and ending in the low-oxygen and low-flow territory of the phase diagram , which indicated a severely damaged end-point of the capillary network . The rest seemed to pursue a temporal pattern of evolution but still remained in a transition stage . These graphs show the results of typical runs of the model . This might illustrate a general picture of how retinopathy progresses in terms of system oxygenation and total blood supply . Note that clinically many diabetics do not develop clinically significant retinopathy whereas a minority has significant propagation of capillary closure . This model would indicate that this variability of progression could have a significant element of probability , ‘bad luck’ , in terms of which capillary was initially an occluded , in addition to other aspects of diabetic control and genetic/epigenetic factor [124–126] . It is now possible to gather time sequence data on the macular capillary network structure of diabetics through the utilization of AOSLO and in particular to do so in the two eyes of single patients , which possess different network anatomies but presumably identical environments in terms of glucose , blood pressure , and levels of systemic leukocyte activation . These data will allow comparisons of patient capillary occlusions and edema over time with sequentially constructed model based probability occlusion maps . This ought to allow refinement of model parameters or rejection of the model . We further summarized the vulnerability of the capillary network given a certain initial occlusion site ( Fig 15 ) . Among all capillary segments carrying relatively slow blood flow , initial occlusion of two capillaries near the FAZ seemed to be most influential in triggering derived occlusions , while occlusions of others had a less significant impact . Both cases showed a spatially relevant patency distribution , with capillaries closer to the initial occlusion site bearing a higher frequency of occlusion . Not uncommonly , capillaries near the terminal FAZ venule and arteriole were also candidates of occlusion . Closure of these capillaries was likely to propagate injury to neighboring foveal arteriolar-venular sectors . These runs show similar results and show that certain portions of this subject’s capillary network are vulnerable to occlusion whereas others seem to be more resilient . Those more resilient areas tended to possess more densely situated capillaries and therefore the area of ischemia produced by a capillary occlusion is small and consequentially so is the resultant increase in local VEGF production and the probability of propagation . Occlusion or survival of a capillary is highly influenced by the local capillary network structure . This phenomenon seen in these results may be the result of more dense capillary networks further from the fovea where the visual impediment consequent to blood vessel opacity is less significant perhaps allowing more closely spaced capillaries . This pattern of loss of perifoveal capillaries , clinically called enlargement of the FAZ , is a commonly seen clinical pattern of macular ischemia development [11] . Experimental data of a number of types can improve and validate the model . Arteriolar and capillary blood flow velocity data is needed to calibrate the network flow module and adjust the structural adaptation module . There are currently AOSLO based [127 , 128] and ocular coherence tomography ( OCT ) angiography techniques [129] that will provide valuable inputs to future diabetic retinopathy modelling but no published techniques for measuring capillary blood velocities are sufficiently mature for routine use . Improved vascular imaging with capillary structures determined over the several retinal capillary layers in the macula would help extend the model beyond its current limitations . With regard to retinal edema , thickness projections can be validated and refined against OCT macular thickness maps and hydrostatic as well as oncotic pressures can be incorporated into the model . Refinements of the relationship of local retinal edema and capillary loss with visual functioning are also on the horizon [130] and can be assessed over time . More detailed structural modeling can be done of the cystic structure of the usual diabetic macular edema as can be determined by OCT . In the periphery the model predicts a gradual enlargement of the sorts of capillary free dark areas commonly seen on fluorescein angiography with occasional development of new small areas of capillary loss that also gradually expand and are blocked , at least temporarily by the oxygenated areas surrounding larger retinal vessels . Sequential fluorescein angiography , especially wide field angiography , would be validating in this area and allow refinement of the occlusion probability functions used in the model .
Why does diabetic retinopathy progress to extensive areas of ischemia whereas certain other ischemic retinal vascular conditions do not progress ? An example would be the arteriolar occlusions seen from particulates in IV drug users . The distinction between diabetic retinopathy and arteriolar occlusions caused by particulates is in the nature of the systemic inflammatory state in diabetes . This is likely the explanation for the non-progressive areas of capillary loss seen in certain retinal vascular conditions such as talc retinopathy in the IV drug user [138] in distinction to the enlarging areas of capillary occlusion in diabetic retinopathy . Diabetics have both a systemic inflammatory condition causing induction of cell adhesion molecules on leukocytes as well as induction of cell adhesion molecules throughout the retinal vasculature . The arteriolar occlusions seen in the IV drug user are local and likely do , through the creation of local ischemia , elevated local VEGF and induce ICAM receptors on local endothelial cells but do so without alterations in leukocyte cell receptors as the systemic inflammatory state is lacking . Therefore there is only local non-propagating retinal ischemia in the IV drug user and in animal embolic arteriolar occlusion models of diabetic retinopathy [139] . The absence of progressive capillary occlusion in either talc retinopathy or embolic models supports a ‘two-hit’ situation in diabetes , with induction of appropriate receptors on both the retinal endothelial cells and on the circulating leukocytes . Similar reasoning can be applied to the sharply geographically constrained ischemic damage produced by branch retinal vein occlusion . The degree to which generalizations can be made to other organ systems is unclear but the presence of a positive feedback between the loss of a capillary and the likelihood of adjacent capillary loss may be less applicable to those organs which lack the constraint of a minimally sufficient , i . e . critical , vascular supply , imposed on the eye by evolution . This may partially explain the relative vulnerability of the eye in diabetes to the propagation of capillary occlusions and to the development of diabetic retinopathy . A model provides a framework within which to analyze and interpret data . Currently , there are no appropriate models for either the progression of peripheral ischemia in diabetics or for diabetic macular disease . This model provides a structure within which to analyze and compare diabetic retinal vascular disease and some framework even if it proves incorrect or inadequate is required to move the understanding of this area forward in an era of refined imaging techniques able to provide inputs at the level required for capillary network modelling . This model , may , in some future instantiation , after considerable refinement and validation , allow improved treatment , with personalized prognosis , from imaging of a diabetic patient’s capillary network and with subsequent modelling allow a prediction regarding risk for vision impairment . Those at especially elevated risk may be candidates for earlier intervention either from anti-VEGF agents or from an alternative approach to photocoagulation . It seems reasonable that this sort of model could influence the course of patient therapy possibly in the not distant future . The current model is clearly limited relative to actual retinal vascular anatomy and physiology . The model was based on the advection and diffusion of the simplest known limiting factor , oxygen , rather than dealing with , say , removal of lactate or carbon dioxide . The model treats only one cytokine , a single VEGF isoform without consideration of other larger VEGF isoforms , PEDF , PDGF , erythropoietin , angiopoetin-1 , angiopoetin-2 or angiopoetin-like 4 , all of which likely play at least some role in vascular changes in diabetic retinopathy [117 , 140–142] . In this case the level of therapeutic efficacy of the anti-VEGF injectable agents such as ranibizumab or aflibercept supports VEGF being a major [12 , 100 , 143] if not the only important factor , supporting its relevancy and use in the model . This is in addition to all the evidence cited above ( see Support for model’s physiological assumptions ) supporting in choice of VEGF as the factor released from Mueller cells and ultimately responsible for capillary occlusion through elevation of ICAM and resultant leukostasis mediated capillary occlusion . Movement of VEGF is a concern as there are a number of VEGF isoforms which have different molecular weights and also different structural domains which bind to tissue matrix [143] . Distribution of VEGF may depend on different states of the vitreous gel: attached , detached , syneretic , or absent ( post-vitrectomy ) , as analogously , oxygen levels are dependent on intraocular location prior to , but not post , vitrectomy which presumably allows free advection [144] . We model only intra-retinal levels of VEGF , not vitreal levels , and there is little evidence specifically on these intraretinal levels and likely little relationship between these and the intra-vitreal levels seen late in the disease . It would seem that the current model is most applicable to the situation of non-proliferative disease with an attached intact vitreous resulting in minimal VEGF advection via fluid flow within the posterior chamber of the eye . This sort of elevated advecting VEGF would introduce another source of VEGF influence on local retinal areas not treated in the model . The details of the complex mechanism of permanent capillary occlusion are unknown but it is likely that multiple intercellular adhesion events occur locally with brief capillary occlusions but also with endothelial cell damage and loss and that over time a local as well as a replacement endothelial cell population from the bone marrow are exhausted [145] . This seems to be another aspect of the impaired physiology of the diabetic . The model assumes a one-time irreversible occlusion event which we interpret as the local coup de grace for that capillary segment following a number of prior endothelial damaging leukocyte adhesion events . In the model occlusion probability was assigned a formula related to local VEGF levels as well as vessel size and flow . This is a sensible approximation to a complicated recurrent local adhesion/occlusion event but has no specific supporting data from the literature . There are also limitations in the model’s approximation to the capillary anatomy in the macula . The model is three dimensional but the capillary bed treated is only two dimensional in the sense that it is a single lamina thought of as the retinal ganglion cell layer capillary network . It is a single capillary layer but only for about 60 microns from the FAZ . There are currently technological difficulties with resolution of the several capillary layers present further from the FAZ and in this area the model is based only on the inner capillary network imaged by AOSLO . The macular thickness increases over the clivus and thus the amount of tissue dependent on the capillary bed is changing with distance from the FAZ . A number of clinical signs of diabetic retinopathy were not modelled such as microaneurysms , intra-retinal microvascular abnormalities , cotton wool spots , or dot/blot hemorrhages . These signs can reflect local ischemia and locally elevated VEGF but we feel they are not etiologically related to the topic of progression of capillary occlusions . The word ‘periphery’ is used loosely in ophthalmology . A model limitation regarding the retinal periphery is that distinct and varying retinal vascular anatomy is seen from the most posterior retinal periphery , that near the arcades ( Fig 1 ) , to that anterior to the eye’s equator and especially that most anterior retina near the ora serrata ( S8 Fig ) . We have modelled the extreme periphery ( anatomically a single capillary layer ) and made statements about ‘peripheral retina’ in general , much of which posterior to the equator has 2 capillary layers . We have implemented a quantitative model of the impact of diabetes on progressive capillary occlusion in retinal capillary networks producing a number of qualitative results very similar to the clinical picture in diabetic retinopathy . A full vascular model from a retinal arteriole to a venule with the linking capillaries is included with oxygen advection , oxygen diffusion , and oxygen consumption . This model requires only the capillary network anatomy , arteriolar and venular pressures , and a number of physical parameters such as a diffusion constant for VEGF and for oxygen . The model produces capillary occlusion on a stochastic basis dependent on local VEGF levels and flow where the local VEGF level is seen physiologically as elevating ICAMs , increasing leukocyte adhesion and ultimately resulting in the capillary occlusion . This results in a local adverse feedback cycle often producing progressive capillary occlusions and enlarging contiguous areas of retinal ischemia . With these simple properties if the model is implemented using a capillary network for a perifoveal area it shows regions of ischemia and macular edema similar to what is seen clinically in the macula including enlargement of the foveal avascular zone . If implemented on a vascular pattern similar to that seen in peripheral retina , model damage proceeds more in line with what is seen clinically in the periphery developing large ischemic areas without edema . This model seems to show that the type and nature of retinal damage depends largely on the pre-existing capillary network morphology , suggesting that it may , after further refinement and validation , have value not only by providing a model through which to augment our understanding of diabetic retinopathy but even potentially , after sufficient clinical validation , for prognostic evaluations and timing of treatment in individual patients .
|
Diabetes is a disease of elevated blood sugar which damages the body’s blood vessels , especially in the eye . Current understanding is that diabetics block one capillary at a time basically because white blood cells become ‘sticky’ in diabetes . This begins a process which results in blockage of a vessel and starves a retinal area of oxygen . This process is believed to randomly block vessels but patients actually have large areas with no intact vessels . We developed a computer model of this process which shows why diabetics have areas in which all capillaries are occluded rather than blocked randomly . Areas develop because the factors released from the retina around one blocked vessel increase the chance that nearby capillaries also become blocked . This understanding may increase our ability to intervene in the process to prevent these large ischemic areas from developing and thereby prevent blindness from diabetic retinopathy .
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2016
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Progression of Diabetic Capillary Occlusion: A Model
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Direct reciprocity , or repeated interaction , is a main mechanism to sustain cooperation under social dilemmas involving two individuals . For larger groups and networks , which are probably more relevant to understanding and engineering our society , experiments employing repeated multiplayer social dilemma games have suggested that humans often show conditional cooperation behavior and its moody variant . Mechanisms underlying these behaviors largely remain unclear . Here we provide a proximate account for this behavior by showing that individuals adopting a type of reinforcement learning , called aspiration learning , phenomenologically behave as conditional cooperator . By definition , individuals are satisfied if and only if the obtained payoff is larger than a fixed aspiration level . They reinforce actions that have resulted in satisfactory outcomes and anti-reinforce those yielding unsatisfactory outcomes . The results obtained in the present study are general in that they explain extant experimental results obtained for both so-called moody and non-moody conditional cooperation , prisoner’s dilemma and public goods games , and well-mixed groups and networks . Different from the previous theory , individuals are assumed to have no access to information about what other individuals are doing such that they cannot explicitly use conditional cooperation rules . In this sense , myopic aspiration learning in which the unconditional propensity of cooperation is modulated in every discrete time step explains conditional behavior of humans . Aspiration learners showing ( moody ) conditional cooperation obeyed a noisy GRIM-like strategy . This is different from the Pavlov , a reinforcement learning strategy promoting mutual cooperation in two-player situations .
We place a player obeying the reinforcement learning rule on each node of the square lattice with 10 × 10 nodes with periodic boundary conditions . However , the following results do not require particular network structure ( Fig A in S1 Text ) . Each player is involved in the two-player PDG against each of the four neighbors on the network . The game is also interpreted as a PGG played in the group composed of the player and all neighbors submitting binary decisions [40] . The game is repeated over tmax rounds . We set tmax = 25 unless otherwise stated . Each player selects either to cooperate ( C ) or defect ( D ) in each round ( Fig 1A ) . The submitted action ( i . e . , C or D ) is used consistently against all the neighbors . In other words , a player is not allowed to cooperate with one neighbor and defect against another neighbor in the same round . If both players in a pair cooperate , both players gain payoff R = 3 . If both defect , both gain P = 1 . If a player cooperates and the other player defects , the defector exploits the cooperator such that the cooperator and defector gain S = 0 and T = 5 , respectively . Each player is assumed to update the intended probability to cooperate , pt , according to the Bush-Mosteller ( BM ) model of reinforcement learning [27–29 , 32 , 39] as follows: p t = p t - 1 + ( 1 - p t - 1 ) s t - 1 ( a t - 1 = C , s t - 1 ≥ 0 ) , p t - 1 + p t - 1 s t - 1 ( a t - 1 = C , s t - 1 < 0 ) , p t - 1 - p t - 1 s t - 1 ( a t - 1 = D , s t - 1 ≥ 0 ) , p t - 1 - ( 1 - p t - 1 ) s t - 1 ( a t - 1 = D , s t - 1 < 0 ) , ( 1 ) where at−1 is the action in the ( t− 1 ) th round , and st−1 is the stimulus that drives learning ( −1 < st−1 < 1 ) . The current action is reinforced and suppressed if st−1 > 0 and st−1 < 0 , respectively . For example , the first line on the right-hand side of Eq ( 1 ) states that the player increases the probability to cooperate if it has cooperated and been satisfied in the previous round . The multiplicative factor ( 1 − pt−1 ) is imposed to respect the constraint pt < 1 . The stimulus is defined by s t - 1 = tanh β ( r t - 1 - A ) , ( 2 ) where rt−1 is the payoff to the player in round t − 1 , averaged over the four neighboring players , A is the aspiration level , and β ( > 0 ) controls the sensitivity of st−1 to rt−1 − A [39] . The player is satisfied and dissatisfied if rt−1 − A > 0 ( i . e . , st−1 > 0 ) and rt−1 − A < 0 ( i . e . , st−1 < 0 ) , respectively ( Fig 1B ) . The so-called Pavlov strategy corresponds to β = ∞ and P < A < R [4 , 5] ( Fig 1C ) . The so-called GRIM strategy , which starts with cooperation and turns into permanent defection ( if without noise ) once the player is defected [2 , 41] , corresponds to β = ∞ and S < A < R [38] . When β < ∞ , which we assume , the behavior realized by the BM model is not an exact conditional strategy such as Pavlov or GRIM , but an approximate one . Unlike some previous studies in which A adaptively changes over time [32 , 37–39] , we assume that A is fixed . In each round , each player is assumed to misimplement the decision with probability ϵ [5 , 6 , 39] . Therefore , the actual probability to cooperate in round t is given by p ˜ t ≡ p t ( 1 - ϵ ) + ( 1 - p t ) ϵ . We set ϵ = 0 . 2 and the initial probability of cooperation p1 = 0 . 5 unless otherwise stated .
For A = 0 . 5 and A = 1 . 5 , the realized probability of cooperation , p ˜ t , averaged over the players and simulations is shown in Fig 2A up to 100 rounds . Due to a relatively large initial probability of cooperation , p1 = 0 . 5 , p ˜ t drops within the first ≈20 rounds and stays at the same level afterwards for both A values . This pattern is roughly consistent with behavioral results obtained in laboratory experiments [13–16 , 42] . For a range of the two main parameters , the sensitivity of the stimulus to the reward ( i . e . , β ) and the aspiration level setting the satisfaction threshold for players ( i . e . , A ) , p ˜ t averaged over the first 25 rounds is shown in Fig 2B . The figure indicates that cooperation is frequent when β is large , which is consistent with the previous results [39] , and when A is less than ≈1 . The probability of cooperation is also relatively large when A is larger than ≈2 . In this situation , defection leads to an unsatisfactory outcome unless at least two out of the four neighbors cooperate ( Fig 1B ) . Because this does not happen often , a player would frequently switch between defection and cooperation , leading to p ˜ t ≈ 0 . 4 . The results shown in Fig 2B were largely unchanged when we varied tmax and ϵ ( Fig B in S1 Text ) . The probability of cooperation , p ˜ t , is plotted against the fraction of cooperating neighbors in the previous round , denoted by fC , for A = 0 . 5 and two values of β in Fig 3A and 3B . The results not conditioned on the action of the player in the previous round are shown by the circles . The player is more likely to cooperate when more neighbors cooperate , consistent with CC patterns reported in experiments with the PDG on the square lattice [42] . CC is particularly pronounced at a large value of β ( Fig 3B as compared to Fig 3A ) . The relationship between p ˜ t and fC conditioned on the last action of the focal player , denoted by at−1 , is shown by the triangles and squares . We observe clear MCC patterns , particularly for a large β . In other words , players that have previously cooperated ( i . e . , at−1 = C ) show CC , whereas the probability of cooperation stays constant or mildly decreases as fC increases when the player has previously defected ( i . e . , at−1 = D ) . These MCC patterns are consistent with the extant experimental results [13–16] . In the experiments , MCC has also been observed for different population structure such as the scale-free network [16] and a dynamically changing network [14] . We carried out numerical simulations on the regular random graph ( i . e . , random graph in which all nodes have the same degree , or the number of neighbors ) with degree four and the well-mixed group of five players in which each player had four partners . The results remained qualitatively the same as those for the square lattice , suggesting robustness of the present numerical results with respect to the network structure ( Fig A in S1 Text ) . Spatial or network reciprocity is not needed for the present model to show MCC patterns . A different aspiration level , A , produces different patterns . CC and MCC patterns are lost when we set A = 2 ( Fig 3C ) , with which the dependence of p ˜ t on fC is small , and p ˜ t when no neighbor has cooperated in the previous round ( i . e . , fC = 0 ) is larger for at−1 = D ( squares in Fig 3C ) than for at−1 = C ( triangles ) . The latter pattern in particular contradicts the previous behavioral results [13–16] . CC and MCC patterns are mostly lost for A = −1 as well ( Fig 3D ) . With A = −1 , the BM player is satisfied by any outcome such that any action is reinforced except for the action implementation error . Therefore , the behavior is insensitive to the reward , or to fC . To assess the robustness of the results , we scanned a region in the β − A parameter space . For each combination of β and A values , we performed linear least-square fits to the relationship between the mean p ˜ t and fC , estimating p ˜ t ≈ α 1 f C + α 2 ( Fig 4A ) . CC is supported if the obtained slope α1 is positive when unconditioned on at−1 ( circles in Fig 3 ) . MCC is supported if α1 is positive when at−1 = C ( triangles in Fig 3 ) and negative or close to zero when at−1 = D ( squares in Fig 3 ) . Intercept α2 is equal to the value of p ˜ t when no neighbor has cooperated in the previous round . The behavioral results suggest that α2 is larger when conditioned on at−1 = C than on at−1 = D [13–16] . Fig 4B indicates that the slope α1 unconditioned on at−1 is positive , producing CC , when A ≤ 1 and β is larger than ≈0 . 25 . However , α1 is less positive when A is extremely small , i . e . , smaller than ≈0 . When conditioned on at−1 = C , α1 is positive , consistent with the MCC patterns , except when β is larger than ≈0 . 5 and A is smaller than ≈0 ( Fig 4C ) . When conditioned on at−1 = D , α1 is close to zero when A ≤ 1 and substantially negative when A ≥ 1 ( Fig 4D ) . The difference in the value of α2 , the intercept of the linear fit , between the cases at−1 = C and at−1 = D is shown in Fig 4E . The figure indicates that this value is non-negative , consistent with the experimental results , only when A < 1 . To conclude , CC and MCC patterns consistent with the behavioral results are produced when 0 < A < 1 and β is not too small . We also confirmed that a different implementation of the BM model [32] produced CC and MCC patterns when A < 1 ( Fig C in S1 Text ) . The BM model with P < A < R , i . e . , 1 < A < 3 , corresponds to the Pavlov strategy , which is a strong competitor and facilitator of cooperation in the repeated PDG [4 , 5] . Our results do not indicate that the Pavlov strategy explains CC and MCC patterns . In fact , the BM model with S < A < P ( i . e . , 0 < A < 1 ) , which is a noisy GRIM-like reinforcement learning , robustly produces CC and MCC patterns . It should be noted that , a noisy GRIM strategy without reinforcement learning components does not produce CC and MCC patterns ( Fig D in S1 Text ) . This result suggests an active role of reinforcement learning rather than merely conditional strategies such as the noisy GRIM . CC behavior has been commonly observed for humans engaged in the repeated PGG in which participants make a graded amount of contribution [9–11 , 43–45] . It should be noted that the player’s action is binary in the PDG . In accordance with the setting of previous experiments [10] , we consider the following repeated PGG in this section . We assume that four players form a group and repeatedly play the game . In each round , each player receives one monetary unit and determines the amount of contribution to a common pool , denoted by at ∈ [0 , 1] . The sum of the contribution over the four players is multiplied by 1 . 6 and equally redistributed to them . Therefore , the payoff to a player is equal to 1 - a t + 0 . 4 ( a t + ∑ j = 1 3 a ˜ j , t ) , where a ˜ j , t is the contribution by the jth other group member in round t . The Nash equilibrium is given by no contribution by anybody , i . e . , a t = a ˜ j , t = 0 ( 1 ≤ j ≤ 3 ) . We simulated the repeated PGG in which players implemented a variant of the BM model ( see Materials and Methods ) . Crucially , we introduced a threshold contribution value X above which the action was regarded to be cooperative . In other words , an amount of contribution at ≥ X and at < X are defined to be cooperation and defection , respectively . Binarization of the action is necessary for determining the behavior to be reinforced and that to be anti-reinforced . In Fig 5 , the contribution by a player , at , averaged over the players , rounds , and simulations is plotted against the average contribution by the other group members , which is again denoted by fC ( 0 ≤ fC ≤ 1 ) . We observe CC behavior for this parameter set when X = 0 . 3 and 0 . 4 ( circles in Fig 5A and 5B , respectively ) . CC patterns are weak for X = 0 . 5 ( Fig 5C ) . The average contribution by a player as a function of fC and the action of the focal player in the previous round is shown by the triangles and squares in Fig 5A–5C . We find MCC patterns . CC and MCC shown in Fig 5 are robustly observed if β is larger than ≈0 . 2 , A ≤ 1 , and 0 . 1 ≤ X ≤ 0 . 4 ( Fig 5D–5G and Fig E in S1 Text ) . Directional learning is a reinforcement learning rule often applied to behavioral data in the PGG [46 , 47] and the PDG [48] . By definition , a directional learner keeps increasing ( decreasing ) the contribution if an increase ( decrease ) in the contribution in the previous round has yielded a large reward . In a broad parameter region , we did not find CC or MCC behavior with players obeying the directional learning rule ( Fig F in S1 Text ) . The present BM model is simpler and more accurate in explaining the experimental results in terms of CC and MCC patterns than directional learning is . So far , we have assumed that all players are aspiration learners . Empirically , strategies depend on individuals in the repeated PDG [13 , 15 , 16] and PGG [9 , 10 , 18] . In particular , a substantial portion of participants in the repeated PGG , varying between 2 . 5% and 33% depending on experiments , is free rider , i . e . , unconditional defector [9 , 43 , 49 , 50] . Therefore , we performed simulations when BM players and unconditional defectors were mixed . We found that the CC and MCC patterns measured for the learning players did not considerably alter in both PDG and PGG when up to half the players were assumed to be unconditional defectors ( Fig G in S1 Text ) .
We have provided compelling numerical evidence that the BM model , a relatively simple aspiration-based reinforcement learning model that has been employed in various decision making tasks [27–29 , 31–39] , explains CC and MCC patterns . On one hand , aspiration learning has offered a proximate mechanism for cooperation [28 , 29 , 31 , 32 , 37–39] . On the other hand , conditional cooperation in the repeated PGG [9–11 , 43–45] and its moody variant in the repeated PDG on networks [13–16] have been consistently observed . Here we provided a connection between aspiration learning and conditional cooperation . Our choice of the parameter values including the number of rounds , the size of the group or neighborhood , and the payoff values , supports the comparison of the present numerical data with the results of behavioral experiments . We are not the first to provide this link . Cimini and Sánchez have shown that MCC emerges from a BM model [25] . The current results significantly depart from theirs and are fundamentally new as follows . First , MCC is built in into their model in the sense that every outcome except for a population of unconditional defectors implies MCC patterns . In their model , the linear relationship pt = α1 fC + α2 after the focal player’s cooperation , where pt is the probability of cooperation and fC is the fraction of cooperation in the neighborhood in the previous round , adaptively changes according to the BM model dynamics . In fact , α1 and α2 are simultaneously updated under a constraint and take a common value after a transient ( S1 Text ) , consistent with their numerical results ( Fig 2 in [25] ) . This relationship yields pt = α1 ( fC + 1 ) , implying MCC whenever α1 > 0 . When α1 = 0 , we obtain pt = 0 , i . e . , unconditional defection . In contrast , players in our model directly adapt the unconditional probability of cooperation without knowing fC such that there is no room for players to explicitly learn the MCC rule . Therefore , our approach is inherently bottom-up . Second , our model is cognitively less taxing than the Cimini-Sánchez model . In their model , a player refers to fC and updates the action rule based on its own actions in the last two rounds . Depending on the action that the player has submitted in the second last round , the parameters in one of the two subrules ( ( p , r ) or q in [25] ) are updated . In contrast , as already mentioned , players do not refer to fC in our model . They only refer to their own reward and action in the previous round . A player simply increases or decreases the unconditional probability of cooperation in the next round depending on the amount of satisfaction , as assumed in the previous experimental [28] and theoretical [29 , 32 , 37–39] studies applying aspiration-based reinforcement learning models to social dilemma games . In Ref . [25] , the Pavlov rather than GRIM rule produced MCC patterns . Our results were the opposite . With Pavlov , CC behavior is lost in our simulations ( Figs 4B and 5D ) . In addition , a Pavlov player cooperates more often after it has defected than cooperated in the last round ( Figs 4E and 5G ) , qualitatively contradicting the experimental results . This inconsistency with Pavlov persists even if we use the Macy-Flache reinforcement learning model as in [25] ( Fig C in S1 Text ) . MCC is intuitively associated with GRIM , not Pavlov , for the following reason . Consider the two-person PDG for simplicity and a player obeying MCC . The player and has obtained payoff R ( by mutual cooperation; fC = 1 ) , the player would cooperate in the next round . If the same MCC player has obtained payoff S ( by the player’s unilateral cooperation; fC = 0 ) , the player would defect in the next round . If the player has obtained payoff P or T ( by the player’s defection , i . e . , at−1 = D ) , the player would next submit at ( = C or D ) independently of the previously obtained payoff ( i . e . , P or T ) . If at = C , the player has flipped the action because at−1 = D . This MCC behavior is not realizable by the aspiration learning because it requires S , P , T < A < R , which contradicts the payoff of the PDG , i . e . , S < P < R < T . If at = D , the player has not flipped the action . This MCC behavior is realizable by a value of A verifying S < A < R , P , T , which is the GRIM . The GRIM is not exploited by an unconditional defector . In contrast , the Pavlov is exploited by an unconditional defector every other round because Pavlov players flip between cooperation and defection . In experiments , a substantial fraction of participants unconditionally defects [9 , 43 , 49 , 50] . The parameters of the aspiration learning may have evolved such that humans behave like noisy GRIM to protect themselves against exploitation by unconditional defectors . It should be noted that the mere GRIM strategy , corresponding to β = ∞ and S < A < P in our model , does not produce MCC patterns ( Fig D in S1 Text ) . Therefore , an involvement of reinforcement learning seems to be crucial in explaining the behavioral results , at least within the framework of the present model . Our numerical results indicated MCC in the PGG . Past laboratory experiments using the PGG focused on CC , not MCC , to the best of our knowledge . As pointed out in previous literature [16] , examining the possibility of MCC patterns in the repeated PGG with experimental data warrants future research . Conversely , applying the BM model and examining the relevance of noisy GRIM in the existing and new experimental data may be fruitful exercises . The results were insensitive to the population structure ( Fig A in S1 Text ) . This is in a stark contrast with a range of results in evolutionary games on networks , which generally say that the population structure is a major determinant of evolutionary game dynamics , in particular , the frequency of cooperation [51–53] . The discrepancy suggests that , under social dilemma games in laboratory experiments , humans may behave differently from the assumptions of evolutionary dynamics . In fact , regular lattices [54] and scale-free networks [16] do not enhance cooperation in behavioral experiments , which is contrary to the prediction of the evolutionary game theory . In addition , human strategy updating can considerably deviate from those corresponding to major evolutionary rules [42] . Aspiration learning provides an attractive alternative to evolutionary rules in approximating human behavior in social dilemma situations and beyond .
Unlike in the PDG , the action is continuous in the PGG such that the behavior to be reinforced or anti-reinforced is not obvious . Therefore , we modify the BM model for the PDG in the following two aspects . First , we define pt as the expected contribution that the player makes in round t . We draw the actual contribution at from the truncated Gaussian distribution whose mean and standard deviation are equal to pt and 0 . 2 , respectively . If at falls outside the interval [0 , 1] , we discard it and redraw at until it falls within [0 , 1] . Second , we introduce a threshold contribution value X , distinct from A , used for regarding the action to be either cooperative or defective . We update pt as follows: p t = p t - 1 + ( 1 - p t - 1 ) s t - 1 ( a t - 1 ≥ X and s t - 1 ≥ 0 ) , p t - 1 + p t - 1 s t - 1 ( a t - 1 ≥ X and s t - 1 < 0 ) , p t - 1 - p t - 1 s t - 1 ( a t - 1 < X and s t - 1 ≥ 0 ) , p t - 1 - ( 1 - p t - 1 ) s t - 1 ( a t - 1 < X and s t - 1 < 0 ) . ( 3 ) For example , the first line on the right-hand side of Eq ( 3 ) states that , if the player has made a large contribution ( hence regarded to be C ) and it has been rewarding , the player will increase the expected contribution in the next round . The stimulus , st−1 , is defined by Eq ( 2 ) . In the numerical simulations , we draw the initial condition , p1 , from the uniform density on [0 , 1] , independently for different players .
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Laboratory experiments using human participants have shown that , in groups or contact networks , humans often behave as conditional cooperator or its moody variant . Although conditional cooperation in dyadic interaction is well understood , mechanisms underlying these behaviors in group or networks beyond a pair of individuals largely remain unclear . In this study , we show that players adopting a type of reinforcement learning exhibit these conditional cooperation behaviors . The results are general in the sense that the model explains experimental results to date obtained in various situations . It explains moody conditional cooperation , which is a recently discovered behavioral trait of humans , in addition to traditional conditional cooperation . It also explains experimental results obtained with both the prisoner’s dilemma and public goods games and with different population structure . Crucially , our model assumes that individuals do not have access to information about what other individuals are doing such that they cannot explicitly condition their behavior on how many others have previously cooperated . Thus , our results provide a proximate and unified understanding of these experimentally observed patterns .
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2016
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Reinforcement Learning Explains Conditional Cooperation and Its Moody Cousin
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Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty , reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes . As a result , these models try to predict the dynamics of systems with tens or even hundreds of free parameters . At this level of uncertainty , model analysis should emphasize statistics of systems-level properties , rather than the detailed structure of solutions or boundaries separating different dynamic regimes . Based on the combination of random parameter search and continuation algorithms , we developed a methodology for the statistical analysis of mechanistic signaling models . In applying it to the well-studied MAPK cascade model , we discovered a large region of oscillations and explained their emergence from single-stage bistability . The surprising abundance of strongly nonlinear ( oscillatory and bistable ) input/output maps revealed by our analysis may be one of the reasons why the MAPK cascade in vivo is embedded in more complex regulatory structures . We argue that this type of analysis should accompany nonlinear multiparameter studies of stationary as well as transient features in network dynamics .
Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty [1–7] , reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes . As a result , these models try to predict the dynamics of systems with tens or even hundreds of free parameters [8–10] . At this level of uncertainty , model analysis should emphasize statistics of systems-level properties , rather than the detailed structure of solutions or boundaries separating different dynamic regimes [11–18] . Chemical network theory and monotone systems approaches can characterize dynamics of biochemical networks based only on their structure , independently of a particular choice of parameters [19–21] . Under certain conditions , these methods can rule out whole classes of behaviors , such as bistability or oscillations , but they do not provide information about the relative prevalence of coexisting dynamic patterns . At the other extreme of model analysis techniques are continuation algorithms , which track steady states or limit cycles as a function of just one or two model parameters at a time [9 , 22] . While the information provided by continuation methods is only local , they can be efficiently combined with random parameter sampling algorithms , enabling the statistical exploration of systems-level properties , such as stability and robustness [23 , 24] . Here , we use this approach to characterize the statistics of steady-state input/output maps in the model of the Mitogen Activated Protein Kinase ( MAPK ) cascade , a network present in all eukaryotic cells and one of the most extensively modeled signaling systems [25] . The first model of the MAPK cascade was developed by Huang and Ferrell , and used as a basis for connecting the structure of the cascade and its dynamics ( Figure 1A ) . Based on mass-action kinetics , the model described the dynamics of 22 species participating in ten reactions [26] . Each of the 37 model parameters , which have been either estimated or extracted from cellular and biochemical experiments , was specified within a reasonably broad interval . Huang and Ferrell hypothesized that the three-tiered structure of the MAPK cascade controls its steady-state input–output behavior . Based on simulations with hundreds of randomly generated parameter sets , they found that the input–output map is ultrasensitive . Importantly , this prediction was supported by biochemical experiments in Xenopus oocyte extracts [26] . In a later sequence of papers , Ferrell and co-workers demonstrated that ultrasensitivity can lead to bistability in positive feedback networks , in which the activated MAPK positively regulates the input to the cascade [27–29] . Recently , however , Kholodenko and co-workers have established that bistability is possible at the level of a single stage of the MAPK cascade [30] . Specifically , when the same phosphatase ( e . g . , MAPK'Pase ) dephosphorylates both the monophosphorylated and double-phosphorylated forms of the substrate ( e . g . , MAPK ) , the double-phosphorylated form competitively inhibits the second dephosphorylation . In combination with the conservation of the total amount of substrate , this generates an equivalent of a direct positive feedback and can lead to bistability [30 , 31] . The extent to which this single-stage phenomenon influences the dynamics of the entire MAPK cascade has been unclear . Here , we demonstrate that a significant fraction of the multidimensional parameter space in the Huang-Ferrell model exhibits bistability and oscillations . Furthermore , our computational results strongly suggest that single-stage bistability is a necessary condition for the oscillatory behavior at the cascade level .
We used a combination of parameter sampling and continuation algorithms to characterize the statistics of input–output ( I/O ) maps in the Ferrell-Huang model [26] . Just as in the original publication , the I/O map describes the system response , taken to be the fraction of MAPK in the double-phosphorylated state , as a function of a distinguished model parameter , the input to the first stage of the cascade ( Figure 1A ) . Specifically , the 36-dimensional vector of the remaining model parameters was repeatedly generated by Monte Carlo sampling from the hypercube defined by Huang and Ferrell ( Table S1 ) . For each of the generated parameter sets , a pseudoarclength-continuation algorithm was used to compute the steady-state I/O map [32] . This approach can both locate steady states and characterize their stability as a function of the input to the cascade . We developed a classification procedure for assigning the I/O maps to one of the three categories: “single-valued , ” “oscillatory , ” and “hysteretic” ( Figure 1B; see Protocol S1 for details of the sampling , continuation , numerical stability analysis , and classification protocols ) . The summary of the classification results , based on 20 , 000 parameter sets , is presented in Figure 2 . We found that ∼80% of the generated models led to single-valued I/O maps ( Figure 2A ) . Surprisingly , the rest of the generated models corresponded to strongly nonlinear I/O maps . Specifically , ∼10% of models had I/O maps with regions of oscillations ( Figure 2B ) , while ∼10% of models were bistable ( Figure 2C; see Table S2 for examples ) . While the existence of bistable I/O maps could have been expected on the basis of the single-stage results by Kholodenko et al . , our results provide the first evidence of oscillatory behavior in the MAPK cascade in the absence of explicit negative feedback [30 , 33] . The large sample size in our calculations ensured tight confidence intervals for these estimates of the frequencies of the three different classes of I/O diagrams ( see also Figure S2 ) . All of the bistable I/O maps had their left-most turning point for positive values of the input . Thus , we did not observe bistability at zero values of the input; such diagrams were proposed to mediate irreversible cell-fate transitions in Xenopus oocyte maturation [29] . Based on the results of our sampling/continuation approach , we characterized the statistical properties of the I/O maps . By fitting the single-valued I/O maps to Hill functions , we found that , with high probability , they are ultrasensitive , i . e . , are characterized by high Hill constants ( nH > 1 ) , Figure S1 ) . In particular , with probability ∼74% , single-valued I/O map is characterized by a Hill coefficient greater than 2: P ( nH > 2 ) ≈ 0 . 74 . Focusing on the hysteretic and oscillatory maps , we established that they involve concentration ranges that can be adequately described by a deterministic approach , i . e . , they are characterized by reasonably large molecular copy numbers for all of the model components ( assuming the volume of an oocyte cell is ∼1 μL , a concentration even as low as 10−9 μM still corresponds to approximately 600 molecules ) . The oscillatory solutions in the model were of the relaxation type , their amplitudes spanned the entire dynamic range of the outputs ( from unphosphorylated to fully phosphorylated MAPK , Figure S3E ) , and their periods were quite long ( typically ½ hour , Figure S4 ) . See Figure S3 for a summary of the statistical properties of oscillatory and bistable regimes . The upper and lower boundaries of the suggested range for each of the parameters in the original Huang-Ferrell paper were given by one-fifth and five times the mean parameter value , respectively [26] . Using our sampling/continuation approach , we found that oscillatory and bistable I/O maps occur for much smaller ranges of parametric uncertainty ( Figure 3 ) . Thus , the existence of deterministic oscillations and bistability is a robust property of the Huang-Ferrell model . In the next set of computational studies , we explored the origin of oscillatory and bistable regimes . To simplify the notation , we label the different stages of the full MAPK cascade , i . e . , the activation of MAPKKK , double-phosphorylation of MAPKK , and MAPK , with the numbers 1 , 2 , and 3 , respectively , and use terms like “system 2” , “system 2+3” or “system 1+2+3” to indicate different reaction networks consisting of a single stage , two consecutive stages , or all stages of the full MAPK cascade , respectively . As a first step towards the analysis of the full model , we used our sampling/continuation approach to characterize the statistics of I/O maps in all possible single-stage and two-stage subsets of the full model ( Table 1 ) . As expected on the basis of previous analytical and computational results [30 , 34–36] , we observed that the first stage is always monostable , while the second and third stages , each of which is formed by two consecutive double phosphorylation–dephosphorylation cycles , supports bistability . While bistability exists already at a single-stage level , our results strongly suggest that the emergence of oscillations requires at least two stages , one of which should be based on double phosphorylation ( Table 1 ) . Based on this , we hypothesized that the existence of single-stage bistability is a necessary condition for oscillations in multistage networks . To test this hypothesis , we checked whether multistage networks with oscillatory I/O maps contain bistable single stages as their building blocks . Remarkably , for all possible multistage networks , i . e . , system 1+2+3 , 1+2 , 2+3 , we observed that oscillatory behavior requires at least one bistable single-stage module , e . g . , stage 2 or 3 being bistable for the 1+2+3 system ( Table 2 ) . Note that there are no qualitative differences between the two-stage and three-stage cascade networks , with respect to their ability to support bistability and oscillations . Interestingly , this correlation between single-stage and multistage dynamics does not necessarily hold for bistable I/O maps ( Table 2 ) : multistage bistability can emerge from coupling of monostable stages . We subsequently analyzed the connection between multistage limit cycles and single-stage bistability . As expected from the established correlation between single-stage bistability and multistage oscillations , we found that , in all cases , multistage limit cycles are “built” around hysteresis loops of bistable single stages ( Figure 4B shows an example of such a correlation ) . This might explain the predominantly relaxation character of the oscillations in the MAPK cascade ( see above ) ; this strongly suggests the relation between the modularity of the network structure and modularity of network dynamics . By analyzing the rates of individual reactions along the limit cycle , we established that multistage oscillations rely on the backwards coupling between a bistable stage and the preceding stage in the cascade ( e . g . , Figure 4A ) . Specifically , when the bistable stage is in the “off” state ( point “a” in Figure 4B ) , the kinase which carries out both of the phosphorylations within this stage is complexed with its substrates . As a consequence , it is protected from dephosphorylation by the phosphatase in the preceding stage , and the total concentration of the kinase gradually increases ( r1 > r2 in Figure 4C ) . However , when the bistable stage switches to the “on” state ( point “b” in Figure 4B ) , at a high total concentration of the kinase , this kinase runs out of substrates and itself becomes a substrate for the upstream phosphatase . As a result , the total concentration of this kinase decreases ( r1 < r2 in Figure 4C ) . At low levels of kinase activity , the substrates of this kinase within the bistable stage quickly become dephosphorylated , and , eventually , the stage quickly undergoes the transition back to the “off” state . We have established that this simple sequence of events accounts for oscillations in all observed multistage systems within the MAPK cascade ( Table 1 ) . Thus , the oscillatory solutions , which were identified on the basis of a brute force computational approach , turned out to have a transparent mechanistic origin . Finally , we assessed the possibility of synthesizing the multistage oscillations from individual components . For this , we estimated the probability that a single , randomly generated bistable stage would lead to oscillations when embedded within the MAPK cascade ( Table 3 ) . The results of this analysis strongly suggest that single-stage bistability is a necessary but not a sufficient condition for multistage oscillations . The same results also show that single-stage bistability is also not sufficient for generating the bistable multistage I/O maps . At the same time , the odds of observing cascade-level oscillations are greatly increased ( more than 3-fold ) by the presence of single-stage bistability ( based on the data in Table 3 ) .
Based on the combination of random parameter search and continuation algorithms , we developed a methodology for the statistical analysis of mechanistic signaling models . In applying it to the well-studied MAPK cascade model , we discovered a large region of oscillations and explained their emergence from single-stage bistability . At this time , it is unclear whether such oscillations and bistability exist within the isolated MAPK cascade . However , our results suggest that oscillations and bistability do not necessarily imply the presence of explicit feedback loops . The surprising abundance of strongly nonlinear ( oscillatory and bistable ) input/output maps revealed by our analysis may be one of the reasons why the MAPK cascade in vivo is embedded in more complex regulatory structures [9] . Numerous feedbacks targeting the MAPK circuit may either enhance the nonlinear behavior , e . g . , by extending the range of inputs supporting bistability and oscillations , or eliminate it altogether , converting the switch-like behavior into a graded I/O response . In addition to feedbacks , synthesis and degradation of pathway components or their nucleocytoplasmic shuttling can affect the MAPK cascade dynamics [37–40] . The effects of these processes on the cascade dynamics can be systematically explored within our continuation/sampling approach . Our objective has been to characterize the relative abundance of qualitatively different types of I/O maps . The rapid convergence of these estimates is an intrinsic feature of the Monte Carlo integration algorithms , which have been used in computational statistical physics for more than half a century . Hence , these kinds of approaches to statistical exploration of network dynamics will be effective whenever the outcomes of computations can be assigned to a finite number of classes . In our case , the outcomes of continuation runs were classified as “single-valued , ” “oscillatory , ” and “hysteretic” ( see Protocol S1 ) . In a different context , it may be important to characterize the statistics of transients induced by changes in the network inputs [41–43] . Given an appropriate classifier for transient solution features , one can identify the regions of the parameter space that lead to either adapting or sustained responses [40 , 42 , 44] . Recent single-cell measurements of protein levels show that they are characterized by high levels of variability . For example , measurements with GFP-labeled proteins in yeast and mammalian cells reported coefficients of variation around 20% [45 , 46] . Within this context , one can ask how robustly it is possible to guarantee a given type of network function . A computational approach to addressing this question can rely on the combination of a simple probability model for protein levels with a deterministic continuation algorithm . In this way , one can estimate the probability that a given I/O map will change its class , e . g . , become oscillatory instead of hysteretic , when the model parameters are sampled from the multivariable distribution localized in parameter space . Figure 5A presents an illustrative example of this type of calculation . Here we took the single-valued I/O map and perturbed it by sampling the parameters from the multivariable normal distribution , with means equal to the base values of parameters in the Huang-Ferrell model and coefficients of variation equal to 0 . 2 . For this particular choice of the base model parameters and probability model , the I/O map remains single-valued ( see Table 4 ) , i . e . , the classification of the I/O map as single-valued is robust . This is not , however , true in general , since in other regions of the parameter space one can easily find single-valued I/O maps that become either oscillatory or hysteretic upon localized variations of model parameters ( unpublished data ) . Given the fact that these types of calculations are quite inexpensive at this time , we argue that this type of analysis should accompany multiparameter nonlinear studies of network dynamics . Another motivation for a more detailed analysis of the distribution of different types of I/O maps in the multidimensional parameter space is provided by problems related to the evolutionary dynamics of signaling networks [47 , 48] . Mutations in the genes which encode components of signaling networks can affect both the protein levels and the rate-constants for protein/protein interactions . One can think that mutations in the regulatory sequence may translate into protein abundance , while mutations in the coding sequence may affect the protein activity and , hence , the rate constants in the model [43] . Depending on their location within the gene sequence , these changes can lead to either small or large shifts in the space of model parameters . Given a model of a mutational process and a biochemical and biophysical understanding of the connection between the gene sequence and protein abundance , one can systematically explore the connection between the dynamics of the genotype and network dynamics . For example , one can ask how easily a given mutational process can lead to a qualitative change of the I/O map . As an example , we computed the class change probabilities of the three different I/O maps in the Huang-Ferrell model upon simulated gene deletions and duplications ( Figure 5B , Table 4 ) . A similar type of approach may prove useful for interpreting the population level data on sequence variations in genes within the MAPK and other signaling pathways [49] .
The mathematical model of the MAPK cascade , described in Text S1 , can be reduced to an equivalent Ordinary Differential Equation ( ODE ) system ( Text S2 ) . The procedure of Monte-Carlo sampling , pseudoarclength continuation , and categorization of the steady-state I/O maps for the reduced ODE system is described in Protocol S1 . Numerical integration , used in obtaining initial guesses for steady states and for approximating oscillatory solutions , was performed using the stiff solver ODE15S in MATLAB , a commercial software package available at http://www . mathworks . com/ . Numerical computations of steady-state solutions and stability/bifurcation analysis were performed in MATLAB code . The statistical frequencies in Figures 2 and 3 and Tables 1–4 are reported with 95% confidence intervals .
|
Molecular studies of cell communication systems lead to models with multiple free parameters . Analysis of dynamical behavior of these models presents considerable challenge . We have developed a computational approach for the efficient exploration of dynamic behavior in such models and applied this method to the model of the Mitogen Activated Protein Kinase cascade , a signaling network conserved in all eukaryotes . Previous analysis of this model suggested that it works as a reversible switch . We have shown that it can also function as an irreversible switch and as a clock .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cell",
"biology",
"1",
"computational",
"biology"
] |
2007
|
Bistability and Oscillations in the Huang-Ferrell Model of MAPK Signaling
|
Canine mammary tumours ( CMT ) are the most common neoplasia in unspayed female dogs . CMTs are suitable naturally occurring models for human breast cancer and share many characteristics , indicating that the genetic causes could also be shared . We have performed a genome-wide association study ( GWAS ) in English Springer Spaniel dogs and identified a genome-wide significant locus on chromosome 11 ( praw = 5 . 6x10-7 , pperm = 0 . 019 ) . The most associated haplotype spans a 446 kb region overlapping the CDK5RAP2 gene . The CDK5RAP2 protein has a function in cell cycle regulation and could potentially have an impact on response to chemotherapy treatment . Two additional loci , both on chromosome 27 , were nominally associated ( praw = 1 . 97x10-5 and praw = 8 . 30x10-6 ) . The three loci explain 28 . 1±10 . 0% of the phenotypic variation seen in the cohort , whereas the top ten associated regions account for 38 . 2±10 . 8% of the risk . Furthermore , the ten GWAS loci and regions with reduced genetic variability are significantly enriched for snoRNAs and tumour-associated antigen genes , suggesting a role for these genes in CMT development . We have identified several candidate genes associated with canine mammary tumours , including CDK5RAP2 . Our findings enable further comparative studies to investigate the genes and pathways in human breast cancer patients .
Breast cancer is a devastating disease causing a majority of cancer-related deaths in women worldwide [1] . Sub-categorisation of patients based on receptor status ( oestrogen ( ER ) , progesterone ( PR ) and HER2 ) has enabled improved targeted treatments . However , treatment could be further improved , especially for the triple negative patients , which account for 12–24% of the patients , and for which no efficient therapy exists at present [2] . There is therefore an urgent need to identify predisposing genes and prognostic tools to improve early detection and enhanced treatment options in breast cancer . One approach is to attempt to identify genes influencing susceptibility to breast cancer , which also has the potential to reveal novel targets for drug development and assist in the implementation of strategies towards personalised medicine . Breast cancer susceptibility is generally believed to be conferred by a large number of loci , each contributing with a small effect to breast cancer risk [3] . So far only a small fraction of human breast cancer cases can be explained by a single gene mutation and the prevalence of clearly hereditary breast cancer is about 5–10% of all breast cancers , leaving a large majority of cases with a more complex aetiology [4 , 5] . Several genes predisposing to breast cancer have been identified , including BRCA1 and BRCA2 , which explain about 20% of the familial breast cancer cases [6] . A large number of association studies have been performed in search of breast cancer susceptibility genes , including pooled strategies and meta-analyses , and many genes conferring a moderately increased risk have been identified [7–10] . However , a large proportion of the inherited risk factors remain unknown . The dog is a unique model for human disease , sharing many both complex and monogenic diseases , a similar gene set and largely the same environment as humans . In addition , the canine population structure makes trait mapping much easier than in humans . Several recent studies have proven the effectiveness of gene discovery in dog breeds for both monogenic [11–14] and complex traits including cancer [15–19] . Canine mammary tumours ( CMT ) are the most common neoplasia in intact female dogs and constitute about half of all tumours [20 , 21] . As in women , dogs develop mammary tumours with increasing age , rarely before 5 years of age and with a median age of occurrence of 10–11 years . However , the English Springer Spaniel ( ESS ) has been shown to have a median age of onset at 7 years of age in the Swedish dog population and 32% of the female dogs are affected at ten years of age in this high-risk breed [20] . This early onset mimics that of familial breast cancer in humans and indicates that inherited risk factors influence CMT development . CMTs also show a high degree of similarity to human breast tumours regarding epidemiological , clinical , morphological and prognostic features [22–24] . CMT is considered a heterogeneous disease with a complex background , resembling that of human breast cancer , but very little is known about the inherited genetic risk factors influencing CMT . We have previously shown that the BRCA1 , BRCA2 and ESR1 genes are associated with CMT in Swedish ESS [25 , 26] . The associations imply similarities in predisposing genetic risk factors between human and canine mammary tumours , but explain only a minor proportion of the elevated risk for CMT in the ESS breed . In this study , we have conducted a genome-wide association study ( GWAS ) to identify genetic risk factors associated with mammary tumour predisposition in the ESS breed in addition to BRCA1/2 and ESR1 [25 , 26] . We have identified three candidate regions containing plausible cancer susceptibility genes and pathways . The top associated region is located on canine chromosome 11 and reveals a complex genetic architecture with an abundance of risk haplotypes indicating involvement of the centrosomal cell cycle regulator CDK5 regulatory subunit-associated protein 2 ( CDK5RAP2 ) in tumour development .
A cohort of Swedish ESS dogs was genotyped for genome-wide association analysis for CMT . A total of 332 individuals ( 188 cases , 144 controls ) and 130 , 238 SNPs remained in the analysis after quality control filtering . The English Springer Spaniels display an inbreeding coefficient of 0 . 03±0 . 05 . The ESS cohort showed substantial stratification , mainly due to an outlier group visible in the MDS plot ( S1 Fig ) . The outlier group could potentially be due to genetic mix-in from other breeds . A standard case-control chi-square test resulted in a genomic inflation λ = 2 . 34 , clearly indicating a stratified dataset . The inflation was controlled by removal of an outlier group of 33 individuals , and by mixed model analysis with PCA covariates to correct for residual stratification and cryptic relatedness in the remaining 180 cases and 119 controls ( λ = 1 . 00 , Fig 1A ) . Several loci showed association with CMT , indicating multiple risk factors in the ESS breed ( Fig 1B , Table 1 ) . Genome-wide significant association was detected on canine chromosome 11 ( SNP BICF2G630310626 , chr11:73 , 290 , 522 , praw = 5 . 6x10-7 , pperm = 0 . 019 ) . Allele frequencies of this top SNP was also studied investigated in the Swedish outlier group ( n = 33 ) , a UK cohort ( n = 40 ) and a Norwegian cohort ( n = 15 ) to investigate a potential overlap in association signal in these minor cohorts . The association with CMT in the original Swedish ESS was however only replicated in the Swedish outlier group , which could indicate an enrichment of this risk variant in the Swedish population ( S2 Fig ) . In addition to the top SNP , seven SNPs located in three genomic regions have p-values deviating from the expected in the QQ-plot ( nominal significance threshold at -log p>4 . 0 , Fig 1A ) . Three SNPs are located on canine chromosome 11 , supporting the genome-wide significant locus , and four SNPs are positioned in two loci on chromosome 27 . The nominally associated SNPs are listed in Table 1 . No SNPs were excluded due to HWE inconsistencies . Linkage disequilibrium clumping was used to define the associated regions for further analysis , using both association and LD values to restrict the regions , Table 2 . Several of the identified regions overlap with variants associated with different forms of cancer in humans [27] . However , none of the regions contain known genes or GWAS sites for human breast cancer [27] . 91% of the cases carry at least one risk allele at the three top loci ( S3A Fig ) . The chromosome 11 peak confers a substantial risk ( OR = 2 . 76 , 95% CI 1 . 72–5 . 57 ) and accounts for 11 . 0±7 . 2% of the phenotypic variance , whereas the three associated regions together explain 28 . 1±10 . 0% of the phenotypic variance ( S3B Fig ) . Interestingly , the proportion increases to 34 . 8±11 . 0% for the top 5 regions and 38 . 2±10 . 8% for the top 10 regions , despite the lack of genome-wide significant association . The associated and potentially-associated regions were re-sequenced in 7 ESS dogs selected for optimal variance . The re-sequencing resulted in a coverage of 159x±33x and 90±3% of the target covered by 20x or more . On average 24 , 500 SNPs and 13 , 100 short indels were detected in each dog across the 12 Mb sequenced . Nine non-synonymous SNPs were discovered within the top region on chromosome 11 , three of these were previously known canine SNPs . No SNPs with predicted deleterious effects were identified within the two nominally associated regions on chromosome 27 . The identified SNPs were evaluated for their potential biological function and whether they complied with risk and protective haplotypes in the sequenced dogs . Fifty-four candidate SNPs were selected for genotyping in the ESS cohort . Several larger structural variants were also detected in the top candidate regions , with the majority overlapping repetitive elements or flanking gaps in the genome assembly , indicating alignment difficulties . This was especially evident in the region on chromosome 27:0 . 7Mb , where two deletions , four duplications and one inversion ranging from 200 bp to 43 kb were detected . The chromosome 11 candidate locus ( Fig 2A and 2C ) shows a dispersed minor allele frequency pattern , with no signs of reduced variability due to selective pressure in the region ( Fig 2B ) . Haplotype and LD analysis was performed for the top candidate region ( chr11:76 . 1–76 . 8Mb , Fig 2D ) using a merged dataset including genotypes from the canine SNP chip combined with candidate SNPs identified by sequencing . This dataset was imputed to allow haplotype , LD and association comparisons between markers . The 700 kb region on chromosome 11 displayed a complex genetic architecture with a multitude of haplotypes , which persisted when taking potential genotype or imputation errors into account . When investigating only SNPs with signs of association ( p<0 . 001 , 15 SNPs ) , 51 different haplotypes were identified of which 17 were private , indicating an unusually high genotypic diversity in the candidate region . Based on data from Auton et al [28] , there are four recombination hotspots within the region and the recombination hotspot density is significantly higher in this region compared to the rest of chromosome 11 ( p = 0 . 017 ) , which could be an explanation for the increased diversity in the region . The phylogenetic relationship between the haplotypes was investigated and the haplotypes can be clustered into three groups with 29 , 5 and 17 haplotypes in each group ( Fig 3A ) . The haplotype frequencies are 0 . 59 , 0 . 16 and 0 . 25 for haplotype group 1 , 2 and 3 , respectively . Haplotypes belonging to group 3 confer a higher risk for CMT than group 1 ( p = 5 . 9x10-5 , OR = 2 . 3 , Fig 3B ) . No significant difference could be established between haplotype group 2 and either group 1 or 3 . The top locus on chromosome 11 could be further defined in the combined GWAS and fine-mapping dataset by markers in high LD ( r2>0 . 6 ) with the top SNP , Fig 2D , restricting the candidate region to approximately 446 kb ( 73 . 278–76 . 723Mb ) . This region spans the CDK5RAP2 ( CDK5 Regulatory Subunit Associated Protein 2 ) and parts of the MEGF9 ( Multiple Epidermal Growth Factor-Like Domains Protein 9 ) gene , both with previous connections to cancer [29 , 30] . There could potentially also be a microRNA and a lincRNA gene in the region since the human MIR147A and LINC01613 overlap gaps in the dog genome assembly ( CanFam 2 . 0 and CanFam 3 . 1 ) . Three putative non-synonymous SNPs in CDK5RAP2 and one SNP in the 3’UTR of MEGF9 were included in the analysis , but the chr11:73 , 290 , 522 top SNP identified in the GWAS remained the most significantly associated after comparisons with potential candidates from re-sequencing , but with a slightly higher p-value after imputation ( p = 1 . 66x10-6 ) , Fig 2D ) . This SNP is located in a small gene desert downstream of CDK5RAP2 . The region is evolutionary conserved , indicating potential functional importance . The base is evolutionary conserved in 95% of the vertebrates and all mammals evaluated ( UCSC genome browser , 100 vertebrates ) . The SNP is predicted to significantly alter the transcription factor binding abilities for the photoreceptor cell-specific nuclear receptor ( PNR/NR2E3 , p = 5 . 3x10-5 from TOMTOM [31] ) , which is specific for the protective allele . PNR/NR2E3 is an orphan nuclear hormone receptor previously reported to have a regulatory role in breast cancer [32 , 33] . Interestingly , two other SNPs in the candidate region show high association and LD with each other ( r2 = 0 . 94 ) but relatively low LD ( r2<0 . 4 ) with the top SNP , indicating a possibility of two independent genetic risk factors in the area . One of these SNPs produces a non-synonymous change in CDK5RAP2 ( at chr11:73 , 692 , 993 bp , grey in Fig 2D ) . The SNP at chr11:73 , 692 , 993 creates a proline to alanine transition , but the amino acid is not well conserved evolutionary and the change is predicted to be benign ( score 0 . 156 ) when analysed with PolyPhen [34] . It displays strong association to CMT ( p = 1 . 3x10-5 ) , but is in moderate LD with the top SNP at chr11:73 , 290 , 522 bp ( r2 = 0 . 38 ) , and could thus be an alternative genetic risk factor in the region . Analysing the dataset with the chr11:73 , 290 , 522 top SNP genotypes as covariates does however remove the association signal in the entire chromosome 11 region ( p>0 . 02 ) , indicating that the associated SNPs are not independent . The entire proximal 13 . 5 Mb of chromosome 27 shows elevated levels of association , with nominally associated peaks at 0 . 7 and 7 . 7 Mb , Fig 4A . An associated region of this size could indicate selection at this site , but the allele frequencies vary and do not suggest decreased genetic variation in the area , Fig 4B . The two loci appear independent with low LD ( r2 = 0 . 03 ) between the top SNPs , Fig 4A . Fine-mapping with additional SNPs did not result in new association signals or restrict the size of either region ( Fig 4C and 4D ) . The 0 . 7 Mb region contains several large gaps and is poorly annotated in both the CanFam 2 . 0 and CanFam 3 . 1 genome assemblies , but the corresponding human region includes 17 genes . Several larger structural variations ( SVs ) were detected when re-sequencing this region in seven dogs , either reflecting an unstable genomic region or , alternatively , could be indicative of errors in design and sequence alignment due to the incomplete dog genome assembly in this area . After resequencing , genotyping and imputation , the SNP BICF2P1040993 ( chr27:735 , 281 bp ) showed the strongest levels of association in the region ( p = 6 . 8x10-6 ) . It is located 418 bp upstream of the lacritin gene ( LACRT , annotated from human hg19 ) , which encodes a glycoprotein involved in tear secretion [35] . LACRT expression has also been detected in breast tissue ( normal breast tissue , breast cancer tissue and breast cancer cell lines ) [36] . After fine-mapping of the 7 . 7 Mb candidate region , the strongest association is seen for two SNPs located 23 kb apart ( BICF2P815910 , chr27:7 , 683 , 337 and BICF2P365456 , chr27:7 , 706 , 463 ) . Based on gene annotation in human , this region includes the 5’ part of the amino acid transporter SLC38A4 , which is known to be imprinted [37] . The SNP with the lowest p-value in this area , BICF2P365456 , chr27:7 , 706 , 463 , is located intronic of the SLC38A4 gene based on human genome gene annotations ( Fig 4D ) . The ten most associated GWAS regions contain excellent candidate genes previously connected to cancer , several of which are novel in breast cancer . We used a PubMed text-based pathway analysis tool ( GRAIL ) to evaluate gene relationships linking the top ten GWAS loci [38] . Highly significant connections were found for six of the ten regions ( pGRAIL≤4 . 6x10-6 , S1 Table ) , which all contain small nucleolar RNA ( snoRNA ) genes . The snoRNAs are involved in post-transcriptional modification of mainly ribosomal RNA and small nuclear RNA . Emerging evidence connect several snoRNAs to cancer [39] . In addition to the associated regions , 117 regions with reduced genetic variability ( RGVs ) were identified in the ESS cohort ( MAF<0 . 01 over >250 kb ) , S2 Table . The RGVs cover 2 . 1% of the genome , and 47 of the RGVs ( representing 19 . 5% of the X chromosome and 1 . 0% of the genome ) are located on the X chromosome . When allowing for more variation ( MAF<0 . 05 ) , RGV regions cover 2 . 2% of the autosomes and 25 . 4% of the X chromosome . This is consistent with a lower recombination rate leading to reduced genetic variation on the X chromosome . There is also a bias towards the X chromosome due to a lower marker density ( average distance 22 . 1 kb compared to 13 . 0 kb for the autosomes ) . The syntenic human regions were extracted for the 117 regions , of which 99 contain genes and could be evaluated for pathway enrichments . Using GRAIL , 29 RGV regions were significantly connected ( pGRAIL<0 . 05 ) , mainly through genes with connections to cancer ( 14 of the 29 regions ) . Of these , ten can be classified as tumour antigen genes , including PAGE2B ( prostate-associated P antigen family , member 2B , pGRAIL = 3 . 3x10-9 ) , SAGE1 ( sarcoma antigen 1 , pGRAIL = 5 . 8x10-6 ) , XAGE5 ( X Antigen Family , Member 5 , pGRAIL = 8 . 2x10-4 ) , DUSP21 ( Dual Specificity Phosphatase 21 , cancer/testis antigen , pGRAIL = 4 . 5x10-3 ) , CT55 ( CXorf48 , cancer/testis antigen 55 , pGRAIL = 3 . 8x10-2 ) and five melanoma-associated antigens ( MAGEA11 , MAGED2 , MAGED4 , MAGED9 and MUM1L1 ) ( S2 Table ) . The tumour antigen gene products can act as antigens in tumour tissue due to somatic mutations or aberrant expression , which can lead to an immune response . Any altered protein could act as a tumour associated antigen , but according to the T cell-defined tumour antigen peptide database [40] there is an overrepresentation of antigen genes on the X chromosome ( 22 . 9% of the unique gene entries 2013 are on X , average distance 4 . 7 Mb compared to 26 . 9 Mb in the remaining genome ) , which could potentially cause a bias towards enrichment in the RGV regions . Interestingly , when combining the GWAS top ten associated regions together with the RGVs , 41 of the 109 regions ( excluding regions without genes ) are connected ( pGRAIL<0 . 05 , S3 Table ) , including both snoRNAs and tumour associated antigens in both datasets .
We have performed the first genome-wide study to identify the underlying cause of CMT , which is a spontaneously occurring tumour with many similarities to human breast cancer . We have identified significant CMT association in a region overlapping the CDK5RAP2 gene . This study further demonstrated the value of CMT as a comparative model for breast cancer for future genetic and clinical studies .
All blood and buccal swab samples were collected from English springer spaniel pet dogs with owner’s consent according to the ethically approved protocols of the participating institutions . All blood and buccal swab samples were collected from English springer spaniel pet dogs with owner’s consent according to the ethically approved protocols of the participating institutions . A total of 216 CMT cases and 175 controls were collected . Of these , 336 ESS samples were collected in Sweden ( 190 cases and 146 controls ) , 40 in the United Kingdom ( 18 cases and 22 controls ) and 15 in Norway ( 8 cases and 7 controls ) . Swedish ESS blood samples were collected by veterinarians in different veterinary animal hospitals and veterinary clinics throughout Sweden between the years 2005 and 2010 and information was collected regarding possible risk factors for the development of mammary tumours for most dogs ( signalment , age of onset , sex , spaying , lactation , use of contraceptives , diet , pregnancy , disease status , and family cancer history ) as well as pathology reports and/or other clinical diagnostic information . The average age of diagnosis was 10 . 8 years , ranging from 5 to 17 years of age . The age of diagnosis is based on the age at time of surgery , which often occurs several years after initial detection of lumps in the mammary glands . 23% of the cases were spayed . Control dogs were over 8 years old and with a confirmed absence of CMT based on palpation of the mammary gland performed by a veterinarian . They were also unaffected by any other form of cancer . 25% of the controls were spayed , with an average age of 6 . 0 years at time of spaying . When samples were available from siblings only one dog was included to reduce the degree of relatedness in the study cohort . Genomic DNA was extracted from whole blood or buccal swabs using the QIAamp DNA Blood Midi Kit ( Qiagen , Hilden , Germany ) , QIAamp DNA Mini Kit ( Qiagen ) , or salt extraction [63] . 196 of the samples were subsequently whole-genome amplified ( GenomePlex Whole Genome Amplification ( WGA ) Kit , Sigma ) due to low DNA amounts . Associated risk allele status for BRCA1 , BRCA2 and ESR1 was available for 278 , 281 and 178 of the Swedish ESS dogs , respectively [25 , 26] . The proportion of dogs carrying at least one risk allele was 98 . 2% ( BRCA1 ) , 85 . 8% ( BRCA2 ) and 94 . 4% ( ESR1 ) . All designs and data analyses were made using the CanFam 2 . 0 genome build , and the results lifted over to CanFam 3 . 1 . All positions are in CanFam 3 . 1 unless otherwise specified . Gene annotations were extracted from ENSEMBL [64] and by lift-over from the human genome hg18 and hg19 using UCSC genome lift-over tool [65] . The Illumina 170K canine HD SNP array was used for the genotyping of approximately 174 , 000 SNPs with a mean genomic interval of 13 kb [66] . The Swedish cohort of 332 samples was used for GWA analysis . Data quality control was performed using the software package PLINK [67] , removing SNPs and individuals with a call rate below 90% and SNPs with a minor allele frequency below 1% . A total of 96 SNPs were removed due to platform genotyping inconsistencies . Population stratification was estimated and visualised in multidimensional scaling plots ( MDS ) using PLINK ( S1 Fig ) to detect outliers and subgroups in the dataset after removing SNPs in high linkage disequilibrium ( LD ) ( r2>0 . 95 ) . The GCTA software was used to estimate the inbreeding coefficient [68] . Regions associated with CMT were detected by case-control genome-wide association analysis . The EMMAX software [69] was used to calculate association p-values corrected for stratification and cryptic relatedness using mixed model statistics . The two primary eigenvectors calculated by the GCTA software [68] were used as covariates in the analysis to adjust for stratification . The LD-pruned SNP set was used for the estimations of MDS , eigenvectors in GCTA and relationship matrix in EMMAX , whereas the full QC filtered SNP set was used for association testing . Quantile-quantile ( QQ ) -plots were created in R [70] to assess possible genomic inflation and to establish suggestive significance levels . Permutation testing was performed in GenABEL [71] using mixed model statistics , two eigenvector covariates calculated by GCTA and 10 , 000 permutations to establish empirical genome-wide corrected p values . Genome-wide significance is considered for pperm ≤ 0 . 05 . Minor allele frequencies were calculated for each cohort ( cases and controls ) using PLINK [67] . Odds ratios ( ORs ) and 95% confidence intervals were also calculated from allele frequencies in PLINK [67] . The allele frequencies in domestic animal populations do not always comply with Hardy-Weinberg equilibrium ( HWE ) due to the non-random mating , but the top SNPs were tested for HWE to exclude SNPs in extreme HW disequilibrium ( p≤0 . 0001 ) , in order to detect possible genotyping errors . A restricted maximum likelihood ( REML ) analysis implemented in the GCTA software [68] was used to estimate how much of the phenotypic variance the associated SNPs account for . The two primary eigenvectors were used as covariates , and the prevalence set to 0 . 36 [20] . The top ten GWAS regions were defined using LD-based clumping in PLINK [67] , where ± 5 Mb of the top SNP positions were searched for associated SNPs ( p<0 . 1 ) in LD ( r2>0 . 2 ) with the top SNP in each region . The regions analysed are listed in Table 1 . The ESS cohort exhibit regions with reduced genetic variability ( RGVs ) , which are fixed or close to fixed for certain alleles in the breed . These regions could contain risk variants contributing to the high incidence of CMT and are undetected in association studies . Regions with MAF<0 . 01 for >250 kb in the entire cohort without outliers ( 180 cases and 119 controls ) were selected for further analysis . A less strict cut-off , MAF<0 . 05 for >250 kb , was also used to enable comparisons to other studies . The top ten GWAS and all RGV regions were evaluated separately and together for pathway enrichment using the GRAIL software [38] , which use published scientific abstracts to evaluate connectivity between genomic regions . 50 kb were added to the flanks of the GWAS and RGV regions and coordinates were translated to human genome 18 using UCSC liftover [65] . Gene size correction and PubMed Text ( Aug2012 ) were applied in GRAIL . We performed mutational screening of the 14 most associated regions in order to identify disease-causing variants . A homozygous region on chromosome 30 was also included in the sequencing . The regions were targeted by either hybrid selection ( NimbleGen Sequence Capture arrays , Roche NimbleGen ) followed by re-sequencing using next generation sequencing ( Illumina Genome Analyzer II , Illumina ) , or by PCR of exons and conserved elements and Sanger sequencing . A total of 12 Mb was targeted and sequence capture was performed using an in-house modified protocol [72] . DNA samples from seven ESS dogs ( 3 cases , 4 controls ) , selected to carry haplotypes that captured as much genetic variation as possible , were sequenced . Targeted next generation sequencing was used to evaluate the top regions chr11:73 . 1–73 . 8Mb and chr27:0 . 48–0 . 76Mb whereas Sanger sequencing of selected regions was applied to the chr27:7 . 6–7 . 72Mb region . Several software packages were used for sequence data analysis to identify SNPs , indels and copy number variants in the sequenced regions . The BWA package [73] was used for read alignment to the dog reference genome [74] , the GATK pipeline for local realignment and quality score recalibration [75] , Picard for removal of read clones and to extract statistics ( http://picard . sourceforge . net ) , Samtools for SNP and small indel variant calling and filtering [76] , SnpEff to annotate variants [77] , the DELLY software suite for detection of structural variants [78] , IGV for visualisation of sequences [79] and SeqScoring [80] for evaluation of conservation using data from the 29 mammals project [81] . CodonCode Aligner ( CodonCode ) was used to evaluate Sanger sequences . Additional genotyping was performed for 61 SNPs using iPLEX Gold Mass ARRAY ( Sequenom ) . Fifty-one of the SNPs were selected from the sequencing data as candidate variants for CMT and eleven were top SNPs from the GWAS included for genotype confirmation . Pyrosequencing ( Qiagen , Hilden , Germany ) was also used for genotyping of two additional candidate SNPs in the CDK5RAP2 gene [82] and one SNP was genotyped using PCR amplification followed by restriction enzyme cleavage and gel electrophoresis . The SNPs included in the candidate SNP genotyping are listed in S4 Table . The Illumina 170K canine HD SNP array dataset was merged with the iPLEX Gold Mass ARRAY and Pyrosequencing SNP data using PLINK [67] . Imputation of missing genotypes was performed with the BEAGLE software [83] before evaluating LD and haplotype structure in the candidate regions . Imputed SNP calls with <90% probability were filtered out , and quality control filtering and association analysis was performed on the imputed dataset using PLINK and EMMAX as described previously in the genome-wide association mapping section . An additional GWAS analysis was also performed with the top SNP ( Chr11:73 , 290 , 522 ) genotypes as covariates to investigate this SNP’s impact on the remaining loci . Pair-wise r2–based LD between markers was used to evaluate the size of candidate regions and whether the associated loci were independent . The r2 calculations were performed using the Haploview [84] and PLINK software packages [67] on the expanded and imputed dataset . The candidate locus on chromosome 11 was restricted by SNPs with a pairwise r2 ≥ 0 . 6 with the top SNPs . Haplotype analysis was performed using PHASE v2 . 1 . 1 [85] to identify haplotypes in the candidate regions . The SeaView software package was used to construct maximum-parsimony phylogenetic trees with bootstrap resampling ( 1000 permutations ) [86] . The designation of clusters was based on branch length . Chi-square statistics were used to evaluate differences between haplotype groups . The associated SNPs within the detected 446 kb region were evaluated with the transcription factor binding motif tool TOMTOM [31] ( JASPAR and UniProbe motif databases , p<0 . 001 ) . The PolyPhen-2 software was used to evaluate the effect of non-synonymous SNPs [34] . Recombination hotspot data was obtained from Auton et al [28] . Student’s t-test was applied to evaluate recombination hotspot density .
|
Dogs provide an excellent model system for several human diseases , including cancer . Heavy breeding for certain behavioural or phenotypic traits has created genetic isolates–breeds–characterised by low levels of genetic variation and a limited number of genetic disease variants within each breed . Cancer is the most common cause of death in dogs today , and canine mammary tumours ( CMT ) are the most prevalent tumour type in unspayed female dogs . These tumours are very similar to human breast cancer and could therefore be used as a naturally occurring model for the human disease . We have investigated genetic variants associated with CMT in English Springer Spaniels pointing to a gene involved in cell cycle regulation ( CDK5RAP2 ) . The CDK5RAP2 could therefore have a key role in the development of mammary tumours and we suggest that further studies should be performed in both dogs and women to investigate CDK5RAP2 and its possible effect on disease and treatment response .
|
[
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"Introduction",
"Results",
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"and",
"Methods"
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"life",
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"genomics",
"evolutionary",
"biology",
"amniotes",
"computational",
"biology",
"organisms",
"chromosomes",
"human",
"genetics"
] |
2016
|
Genome-Wide Analysis Identifies Germ-Line Risk Factors Associated with Canine Mammary Tumours
|
Paramutation is a well-studied epigenetic phenomenon in which trans communication between two different alleles leads to meiotically heritable transcriptional silencing of one of the alleles . Paramutation at the b1 locus involves RNA-mediated transcriptional silencing and requires specific tandem repeats that generate siRNAs . This study addressed three important questions: 1 ) are the tandem repeats sufficient for paramutation , 2 ) do they need to be in an allelic position to mediate paramutation , and 3 ) is there an association between the ability to mediate paramutation and repeat DNA methylation levels ? Paramutation was achieved using multiple transgenes containing the b1 tandem repeats , including events with tandem repeats of only one half of the repeat unit ( 413 bp ) , demonstrating that these sequences are sufficient for paramutation and an allelic position is not required for the repeats to communicate . Furthermore , the transgenic tandem repeats increased the expression of a reporter gene in maize , demonstrating the repeats contain transcriptional regulatory sequences . Transgene-mediated paramutation required the mediator of paramutation1 gene , which is necessary for endogenous paramutation , suggesting endogenous and transgene-mediated paramutation both require an RNA-mediated transcriptional silencing pathway . While all tested repeat transgenes produced small interfering RNAs ( siRNAs ) , not all transgenes induced paramutation suggesting that , as with endogenous alleles , siRNA production is not sufficient for paramutation . The repeat transgene-induced silencing was less efficiently transmitted than silencing induced by the repeats of endogenous b1 alleles , which is always 100% efficient . The variability in the strength of the repeat transgene-induced silencing enabled testing whether the extent of DNA methylation within the repeats correlated with differences in efficiency of paramutation . Transgene-induced paramutation does not require extensive DNA methylation within the transgene . However , increased DNA methylation within the endogenous b1 repeats after transgene-induced paramutation was associated with stronger silencing of the endogenous allele .
Paramutation is a trans-interaction between specific alleles or transgenes that leads to a meiotically heritable change in the expression of one of the participating alleles or transgenes . Originally described for the maize ( Zea mays L . ) r1 ( red1 ) [1] and b1 ( booster1 ) [2] genes , paramutation has since been reported for several other genes in plants ( see e . g . [3]–[9] ) . Paramutation-like interactions have also been described in other species , including Drosophila [10] , mammals and humans ( for review see [11] ) . Paramutation at the b1 locus provides a powerful system for dissecting the underlying mechanism of paramutation ( reviewed in [12] ) . The b1 gene encodes a transcription factor that activates the purple anthocyanin biosynthesis pathway . Alterations of b1 expression lead to a visual change in plant pigmentation , and the amount of pigment is a read-out of the b1 transcription level [3] . The two b1 alleles that participate in paramutation are B-I ( B-Intense ) and B'; B-I is highly expressed and specifies dark purple pigmentation of the husk , sheath and tassel of the maize plant , while B' is expressed at a much lower level and specifies light streaky pigmentation in the same plant tissues as B-I [3] , [13] . The high expressing B-I allele is unstable and can spontaneously change to B' at variable frequencies ( can be up to 10%; [13] ) . In contrast , B' is very stable and does not change to B-I in wild-type genetic backgrounds [13] , [14] . Paramutation occurs when B' and B-I alleles are combined in one nucleus by crossing . The “paramutagenic” B' allele turns the “paramutable” B-I allele into B' at a 100% frequency . The new B' allele ( B-I in the previous generation ) is as heritable and paramutagenic as the original B' allele [13] . Alleles that do not participate in paramutation are referred to as neutral [14] . Genetic screens in maize have uncovered a number of genes required for paramutation ( reviewed in [12] , [15] , [16] ) . All but one gene [17] identified to date share homology with genes involved in the RNA-directed transcriptional silencing pathway in Arabidopsis [18] , strongly indicating a requirement of this pathway for paramutation . A necessary step towards further dissecting the mechanism of paramutation is knowledge of the key sequences mediating paramutation , the subject of this work . Previous fine structure recombination studies between B' or B-I and neutral b1 alleles revealed that paramutation requires a region spanning ∼6 kb located ∼100 kb upstream of the b1 transcription start site [19] , [20] . This region was also required for high b1 expression . In B' and B-I , this region contains seven tandem repeats of an 853-bp sequence that is unique to this location within the maize genome . Notably , an allelic series in which alleles differed only by the number of repeats revealed that multiple repeats are required for paramutation . Alleles with seven and five repeats were fully paramutagenic , alleles with three repeats had reduced paramutagenicity , and alleles with a single repeat were neutral to paramutation [19] . The B' and B-I alleles are epialleles as they have identical DNA sequences [20] . Consistent with epigenetic regulatory mechanisms defining the B' and B-I states , the hepta-repeats have distinct chromatin structures in B' and B-I [19] , [21] . The epigenetic mark that correlates best with paramutation ability is DNA methylation . The B' repeats have extensive DNA methylation , while the B-I repeats have low levels of DNA methylation [21] . There are differences between the alleles in histone modifications and the extent of chromosomal looping between the repeats and the b1 promoter , but these differences correlate mainly with tissue-specific expression , not the heritable silencing associated with paramutation [21] , [22] . The b1 tandem repeats are transcribed [23] and generate siRNAs [24] , yet repeat siRNAs are produced even from alleles that do not participate in paramutation , suggesting b1 siRNAs are not sufficient for paramutation in the tissues analyzed [24] . However , when the repeat sequence is expressed as a hairpin RNA from a transgene , which generates much higher levels of siRNAs than the endogenous alleles , heritable silencing and paramutation can be reconstructed [24] . This contrasts with two other examples of siRNAs generated from hairpin RNA producing transgenes in maize . These siRNAs effectively silenced homologous promoters , yet that silencing was not heritable [24] . Similar studies using hairpin RNAs to silence promoters in Arabidopsis did not report on heritability ( e . g . [25] ) . We hypothesize that the tandem repeats of the B-I and B' epialleles have special properties , which confer the ability to establish and heritably transmit the silenced paramutagenic state of B' . In this study , we test this hypothesis by asking whether the tandem repeats themselves are sufficient to send and respond to trans-acting paramutation signals , using a series of transgenes containing b1 tandem repeats . Our results are consistent with the above hypothesis . While paramutation was effectively reconstituted , the repeat transgene-induced silencing of B-I was less frequent and showed reduced stability in the next generation relative to endogenous paramutation , which occurs 100% of the time and is always stably transmitted .
To test whether the b1 sequences upstream of the transcription start site ( TSS ) could induce silencing of the B-I allele from a non allelic position , two constructs carrying the b1 repeats and surrounding sequences were used to generate transgenic maize lines: pB , containing the 5′ part of the b1 transcription unit and 106 . 2 kb of sequences upstream of the ATG ( Figure 1A , [19] , [20] ) and pBΔ , which had 91 . 6 kb deleted between the tandem repeats and the proximal promoter of the b1 transcription unit relative to pB ( Figure 1A ) . These constructs allowed us to also address if , in addition to the tandem repeats , other sequences upstream of the TSS were required for paramutation . For example , the observed transcription of the repeats [23] , [24] is likely to be required for paramutation and the promoter sequences driving this transcription might be located outside of the repeats . The Hi-II maize stock used for transformation carried recessive neutral b1 alleles ( designated as b-N ) that do not participate in paramutation and do not confer anthocyanin plant pigment ( V . Chandler , unpublished data ) , enabling the monitoring of silencing activity of the transgenes after crossing the regenerated transgenic plants to B-I . To test whether the sequences within either construct could mediate B-I silencing , the primary transgenic plants were crossed with plants carrying the paramutable B-I allele and a neutral b-N allele ( Figure 2A ) . The presence of the neutral allele provided a means to propagate the transgenes in the absence of B-I ( Figure 2A ) , which was done for multiple generations by crossing with b-N testers ( Figure S1 ) . To test the ability of transgenes to induce silencing , transgenic plants at different generations of propagation were crossed with B-I ( Figure S1 , Table S1 ) . Scoring of plant pigment of the B-I/b-N progeny carrying transgene loci ( TG/- ) revealed that four out of ten pB , and five out of nine pBΔ transgene loci induced silencing of B-I ( Figure 2B ) . In the transgenic events with silencing , the frequencies of silencing varied across multiple generations , ranging from 17 to 100% ( Figure 2B , Table S2 ) . The phenotypes of plants showing transgene-induced silencing of B-I were very similar to those showing B'-induced paramutation of B-I ( Figure 2A and data not shown ) . In this paper , the transgene-induced silenced state of B-I is noted as B'# to signify the transgenic origin of this state , in contrast to paramutation induced by the endogenous B' allele . Non-transgenic sibling plants ( B-I/b-N ) served as controls for spontaneous paramutation of B-I to B' , which can happen frequently [14] . Data from families showing spontaneous paramutation in non-transgenic siblings were not included in this paper . Our results indicate that silencing of B-I can be mediated by sequences in ectopic , i . e . non-allelic , locations , paving the way for using a transgenic approach to further dissect the minimal sequences required for paramutation . Furthermore , these results demonstrate that a sub-fragment of the b1 locus , containing primarily the tandem repeats and the 5′ part of the b1 transcription unit , is sufficient to establish B-I silencing . The most prominent feature within the 16 . 3 kb sequence contained in the pBΔ construct are the seven 853 bp tandem repeats , and as paramutation strength correlates with the number of repeats [19] , they were strong candidates for the minimal sequences mediating paramutation . To determine which part of the repeat sequence is needed to induce silencing , the 853 bp tandem repeat unit was dissected into two halves based on their different GC content; one half ( hereafter referred to as FA ) is 48% AT-rich , while the other half ( hereafter referred to as FB ) is 68% AT-rich [19] ( Figure 1B ) . PCR-amplified sub-fragments ( FA or FB halves ) were ligated in head-to-tail orientation to form seven tandem repeats ( Figure 1B ) . Constructs carrying the FA and FB hepta-repeats , pFA and pFB , were then transformed into maize and the resulting twelve transgenic events were tested for their ability to induce B-I silencing , similar to the approach used for pB and pBΔ transgenic loci ( Figure 2A ) . Results revealed that all four pFA transgenic events induced B-I silencing at 100% frequency , indicating the pFA transgene contains all sequences sufficient for trans-silencing ( Figure 2B , Table S2 ) . None of the eight pFB transgenic events induced B-I silencing ( Figure 2B , Table S2 ) , suggesting the FB sequences were not sufficient for trans-silencing . Because pFB transgenic events do not induce silencing they serve as controls demonstrating that specific repeated sequences mediate silencing of B-I . One of the defining features of b1 paramutation is that B' is fully paramutagenic to B-I and the silencing is heritable [13] . To assay whether the transgene-induced B'# silenced state was heritable and paramutagenic , plants carrying B'# alleles , induced by three independent pBΔ and two independent pFA transgenic loci , were crossed with plants heterozygous for the paramutable B-I and a neutral b-N allele ( Figure S2A ) . Assaying the phenotype of the resulting non-transgenic B'#/b-N progeny revealed that the silenced B'# phenotype was heritable in the majority ( 78–100% ) of the non-transgenic plants ( Table 1b ) . Assaying the B'#/B-I non-transgenic progeny revealed that the B'# states were often paramutagenic ( 41–100%; Table 1d ) . To distinguish the various epigenetic states , we use B'∧ to signify a B-I allele silenced by B'# . Together , our results demonstrate that pBΔ and pFA-induced silencing of B-I to B'# can recapitulate the two key characteristics of paramutation; the silenced B'# state can be transmitted to progeny and it can be paramutagenic , inducing the B'∧ silenced state in the absence of the inducing transgene . Unlike the state induced by the B' allele , the heritability and paramutagenicity of the B'# state was not fully penetrant and the frequency varied between the different pBΔ transgenic events . To test whether prolonged exposure to the pBΔ transgenes would increase the heritability and paramutagenicity of B'# , B'#/b-N; TG/- plants carrying B'# alleles that had been exposed to the transgenes for two subsequent generations were crossed with either b-N or B-I ( Figure S2B ) . For all three pBΔ transgenic events tested , subsequent generation in the presence of the transgene increased the heritability and paramutagenicity of the B'# state to 100% ( Table 1ce ) . This could be because of prolonged in trans interactions between the transgene and B'# . Spontaneous paramutation of B-I can , however , not be completely ruled out . Roughly half of the pB and pBΔ transgenic events , and all of the pFB transgenic events were not paramutagenic ( Figure 2B , Table S2 ) . As the endogenous B' and B-I alleles have identical DNA sequences but differ in chromatin structure , expression levels and paramutation properties [19] , [21] , one possibility was that the transgenic events that were not paramutagenic might have assumed a B-I-like epigenetic state upon integration . If that was true , such transgenes should become paramutagenic upon exposure to B' . To test this hypothesis , b-N/b-N; TG/- F1 plants ( as indicated in Figure 2A and Figure S3 ) , which had never been crossed to B-I , but whose siblings crossed to B-I demonstrated they carried non-paramutagenic or weakly paramutagenic transgenic events , were crossed to B' . The resulting transgenic progeny plants were then crossed to B-I to determine if the paramutagenicity of the transgenes had increased ( crosses described in Figure S3 ) . Results shown in Table 2 demonstrate that four out of seven pB , and three out of four pBΔ transgenic events became highly paramutagenic . One potential explanation for the increased paramutagenicity could be spontaneous paramutation of the transgenic loci instead of an interaction with B' . The frequency of spontaneous paramutation of the transgenes can be estimated by carrying the transgenes for multiple generations with only neutral b1 alleles and then testing their ability to induce paramutation of B-I ( shown in Figure S1 and Table S1 ) . While there was some variability from generation to generation among the weakly paramutagenic events , none of the weakly paramutagenic transgenes became fully paramutagenic unless crossed to B' . For example , with event number 3-46 , its paramutation frequency ranged from 36 to 85% over six generations with neutral alleles . In contrast , after one generation with B' , its paramutation frequency was 100% . Similarly , several transgenes only became paramutagenic upon crossing with B' . For example , event 4-06 was not paramutagenic when carried for four generations with neutral b-N alleles ( 0% paramutagenicity , Table S1 ) , but became highly paramutagenic ( 97% ) after only one generation with B' ( Table 2 ) . We refer to these transgenic events as paramutable to distinguish them from the paramutagenic transgenes , which did not require crosses with B' to become paramutagenic . The ability of certain transgenes to become paramutagenic only after exposure to B' suggested that upon integration these transgenes initially assumed a B-I-like state . The transgenic events that did not become paramutagenic , even after crossing with B' , are referred to as neutral . In contrast to the majority of the pB and pBΔ transgenic events , none of the seven pFB transgenic events tested showed any paramutagenicity after exposure to B' ( Table 2 ) , suggesting that the repeat sequences in the pFB transgenes were not sufficient to receive and/or heritably transmit the paramutation signal . Failure of some transgenic events to participate in paramutation could be attributed to several factors . Transgenes may be truncated and not carry tandem repeats , which are absolutely required for endogenous paramutation [19] , or they may have integrated in genomic locations that prevent establishment of silencing . To determine how many events had the intact hepta-repeat fragment and to estimate the number of repeat units present in each event , DNA blot analyses ( Materials and Methods ) were performed on paramutagenic , paramutable and neutral events ( see previous section for definitions ) . As is typical for biolistic transformation , the DNA blot analysis revealed that the pB and pBΔ transgenic plants contained multiple copies of the transgenes , including complete and truncated fragments ( Figure 3A ) , which segregated as a single locus in each independent event . Six of the paramutagenic transgene loci carried an intact hepta-repeat fragment ( Figure 3A , black arrow , 7 kb ) and three paramutagenic events did not . None of the paramutable or neutral events carried an intact hepta-repeat . Thus , an intact hepta-repeat fragment was associated with paramutagenicity but was not absolutely necessary for an event to be paramutagenic or paramutable . As all of the insertions are complex we cannot rule out that one or more of the transgenic lines also contain repeats in an inverted orientation , a sequence arrangement known to mediate silencing [25] , [26] . We favour our hypothesis that it is the tandem repeats mediating paramutation because it is unambiguous from the fine structure mapping that tandem repeats mediate endogenous paramutation [19] and all the transgenic events with an intact tandem hepta-repeat were paramutagenic . The number of repeat units present within each event was estimated by normalizing to an endogenous fragment containing a single repeat unit ( Materials and Methods ) . In each functional category , paramutagenic , paramutable or neutral , there are examples of transgenic events that have relatively high or low numbers of repeat units ( Figure 3A ) . All transgenic events , except one neutral event ( 4–12 ) , carried more than one copy of the 853 bp repeat unit . There was not an absolute correlation between the number of the repeats and paramutation activity in the transgenic events ( Figure 3A ) , although all intact hepta-repeat events were paramutagenic . A similar lack of correlation was observed with the pFA and pFB transgenic events ( Figure 3B ) . The pFA transgenic events , which were all highly paramutagenic , had lower copy numbers ( 6–9 repeat units ) than most of the pFB events ( seven out of eight events had 16 or more repeat copies ) , which showed no paramutation ability . In addition , most of the pFB events had an intact fragment containing seven repeats , while none of the pFA events did ( Figure 3B ) . These results confirm that the pFA sequences are sufficient for paramutation , while the pFB sequences are not . Relative to B-I , the paramutagenic B' allele has high levels of cytosine methylation within the tandem repeats [21] . To determine if there was a correlation between the frequency of paramutation and DNA methylation levels at the transgenic repeats , two pBΔ transgenic events , 3-39 and 3-46 , were selected for DNA blot analysis . These two events have relatively simple transgene integrations; one intact hepta-repeat fragment and only a few other , truncated repeat-containing fragments ( Figure 3A ) , enabling the interpretation of the DNA blot results . Representative examples of the 3-39 and 3-46 transgenic loci that were in the presence of neutral b-N alleles ( in the immediate progeny of regenerated transgenic plants ) and had not been exposed to B-I or B' , are shown in Figure 4A . The transgenic repeats were mostly unmethylated within the assayed restriction sites ( Figure 4A , open and grey arrows; a total of four 3-39 and seven 3-46 plants were examined ) . The repeat DNA methylation levels were not only lower than those previously observed for B' and for plants undergoing spontaneous paramutation of B-I to B' , but were also lower than those observed for B-I ( Figure 4B and 4D; Figure S4 ) [19] , [21] . These results indicate that paramutation can be mediated by transgenic repeats that do not have the DNA methylation levels typical of B' . To test if the methylation levels of the transgene increased after it had mediated paramutation , we examined the 3-39 transgene after it had segregated from the F1 between the primary 3-39 transgenic plant and B-I [In this F1 , paramutation occurred at a frequency of 90% , ( Table S1 ) ] . The segregating 3-39 repeat transgene was extensively methylated , equivalent to B' ( Figure 4B; three plants examined ) . Thus , after paramutation and segregation the transgene was extensively methylated . This could be due to spontaneous increases in DNA methylation or due to interactions between the transgene and the endogenous allele ( resulting in paramutation of B-I to B'# ) , or both . To test for spontaneous DNA methylation within the repeats , we examined the 3-39 transgene maintained in the presence of neutral b1 alleles for four generations ( never exposed to B-I or B' ) . We observed a spontaneous increase in the DNA methylation levels in the transgenic repeats ( Figure 4C , black arrows , four plants tested ) up to the levels observed for the endogenous B' repeats ( Figure 4B and 4D ) . Thus , the increased methylation observed within the 3-39 transgenic repeats after encountering B-I could be due to spontaneous events . The 3-46 transgenic event had very low levels of DNA methylation ( Figure 4A ) in the immediate progeny of the primary transgenic event , and when crossed with B-I plants , paramutation occurred at a frequency of 66% ( Table S1 ) . After crossing the 3-46 transgene with B' and then outcrossing to B-I , 100% paramutation was observed . With this one event , we saw that after crossing with B' , both the transgene and B'# had acquired extensive DNA methylation ( summarized in Figure 4D and data not shown; a total of six B' TG/- plants , and 11 B'# TG/- plants were tested ) . This result indicates that transgenic repeats with low levels of DNA methylation can acquire higher DNA methylation , but more events and individuals need to be examined to determine if increased paramutagenicity correlates with DNA methylation . A key difference between transgene-mediated and endogenous allele-mediated paramutation is that the resulting silencing of B-I to B'# is less stable when induced by the transgenes than by B' ( Table 1 ) . To determine whether this difference in silencing , as measured by plant phenotypes , might correlate with the extent of repeat DNA methylation in the endogenous allele , non-transgenic progeny plants segregating B'# and displaying a range of pigment phenotypes were examined . These individuals derived from outcrossing the B'#/b-N; TG/- F1 to b-N ( Figure S2A ) . Notably , DNA methylation levels within the B'# repeats , induced by the 3-39 transgene , varied and this variation correlated with the extent of silencing; the more DNA methylation , the lower the plant pigment levels , which are a read-out of the level of B'# silencing ( Figure 4B and data not shown ) . The same correlation between the extent of silencing and DNA methylation was observed for the 3-46 transgene ( data not shown ) . While the number of individuals examined is small ( four 3-39 and six 3-46 plants looked at in total ) , these data are consistent with a correlation between the level of B'# silencing and extent of DNA methylation within the endogenous repeats . Paramutation by the endogenous B' allele requires the Mop1 gene [23] , which encodes a protein with high similarity to RDR2 , a putative RNA-dependent RNA polymerase required for RNA-directed transcriptional silencing in Arabidopsis [27] . To test whether MOP1 is required for the transgene-induced paramutation , the appropriate crosses were done to assay the ability of three pBΔ transgenes to paramutate B-I in the presence of the mop1-1 mutation ( Figure S5 ) . If paramutation was prevented , the segregating progeny should have the B-I phenotype , whereas if paramutation occurred , most progeny should have the B' phenotype . Analysis of the segregating non-transgenic progeny revealed that the majority of the plants had a B-I phenotype ( Table 3 ) , indicating that the mop1-1 mutation prevented the pBΔ transgenes from paramutating B-I to B'# . A few light B' plants were observed in three out of twelve testcross families . These could be the result of spontaneous paramutation of B-I to B' , or because paramutation was not fully prevented in all plants . The observation that MOP1 is required for the transgenes to silence B-I demonstrates RNA-mediated mechanisms are involved in transgene-induced paramutation of B-I . In addition to mediating silencing , multiple b1 tandem repeats are required for high B-I expression [19] . It is , however , not known if the repeats are sufficient to mediate high expression or whether additional sequences are needed . To test if the repeats can mediate high expression a construct was produced in which the seven tandem repeats of B' , B-I ( b1TR ) were fused to the minimal −90 bp Cauliflower Mosaic Virus 35S promoter ( 35S ) [28] and the GUS ( beta-glucuronidase , [29] ) reporter gene to generate the pb1TR::GUS transgene ( Figure 5A , Materials and Methods ) . As a negative control , a construct was made that carried only the minimal −90 bp 35S promoter fused to GUS ( p35S::GUS ) . Both constructs were used to generate transgenic maize lines; only lines carrying intact GUS reporter genes were examined for GUS activity ( Materials and Methods ) . Sheath and husk tissues were stained for GUS activity and scored using a graded scale shown in Figure 5B . High GUS activity was observed in pb1TR::GUS events 36-7 , 36-21 and 36-31 , but not in the event 36-11 ( Figure 5C ) . Southern blot analysis ( not shown ) revealed that the GUS transgenes in events showing high GUS activity carried about ∼7 repeats ( 36-7 , 1 transgene copy ) , 6 and 1 . 5 repeats ( 36-21 , 2 copies ) , and 4 and 3 repeats ( 36-31 , 2 copies ) , while the transgenes in the event showing weak GUS activity carried about 3 . 5 and 2 . 5 repeats ( 35-11 , 2 copies ) . Three p35S::GUS control events that contained no repeats showed low GUS activity , while one had high GUS activity ( 34-10 , Figure 5D ) . The high GUS activity in the p35S::GUS event 34-10 was unexpected and was hypothesized to be caused by integration of the transgene near an endogenous transcriptional regulatory element . If this hypothesis was correct , the expectation was that the GUS activity should not be silenced by B' . In contrast , if the high expression in the pb1TR::GUS events 36-7 , 36-21 and 36-31 was mediated by the repeats , B' should silence that expression . To test these hypotheses , the p35S::GUS event ( 34-10 ) and the three pb1TR::GUS transgenic events strongly expressing GUS ( 36-7 , 36-21 and 36-31 ) were crossed with the paramutagenic B' allele . The three pb1TR::GUS transgenic events were also crossed with two highly paramutagenic pBΔ transgenic events . Results shown in Figure 5E revealed that the expression of p35S::GUS event 34-10 was not affected by B' , consistent with the hypothesis that its high expression is caused by integration near an endogenous regulatory element that is insensitive to B' . In contrast , all three pb1TR::GUS transgenic events exhibited a significant reduction in GUS activity after exposure to B' ( Figure 5F ) or the paramutagenic pBΔ transgenes ( Figure 5G ) , providing additional support that the high expression was not simply due to insertion next to an endogenous enhancer . The silencing of the pb1TR::GUS transgenic loci in the presence of the paramutagenic pBΔ transgenes was not due to spontaneous paramutation , because for all three pb1TR::GUS loci control transgenic siblings segregating only the pb1TR::GUS transgenes showed higher GUS activity ( Figure 5G ) . Together , these data suggest that the b1 tandem repeats are sufficient to trigger expression of a heterologous gene and that this expression is sensitive to paramutation . To determine if the transcriptional regulatory activity within the repeats could be further delineated , transgenic lines containing seven FA or seven FB tandem repeats fused to the minimal p35S::GUS reporter gene were generated ( Figure S6 ) . GUS expression was observed in all the four intact pFA::GUS events and the one intact pFB::GUS event . However , because there was only one intact pFB::GUS event available , more experiments will be required to delineate where the transcriptional regulatory activity maps . Previous studies have shown that the tandem repeats in B-I and B' produce siRNAs [24] . Therefore various repeat transgenes were tested for the production of b1 repeat siRNAs from their ectopic locations . As b1 alleles that have a single copy of the repeat unit , and do not participate in paramutation , also produce b1 repeat siRNAs [24] , non-transgenic siblings with the same b1 genotype as their transgenic counterparts were tested alongside ( Figure 6 ) . Transgenic pBΔ 3-39 plants with the full length repeats showed slightly increased levels ( ∼2–3 fold ) of b1 repeat siRNAs relative to their non-transgenic siblings , suggesting that either the transgenic locus was producing b1 repeat siRNAs and/or it triggered an increase in the production of b1 repeat siRNAs from the endogenous alleles . Similar increases in b1 repeat siRNAs were seen with pFA::GUS and pFB::GUS transgenes ( Figure 6 and Figure S6A ) . Notably , the b1 oligoprobe used in this experiment hybridizes to the FA part of the repeats , indicating that , at least in the pFB::GUS event , the b1 siRNAs detected are derived from the endogenous b1 repeat sequences . In spite of similar siRNA levels , the pBΔ 3-39 and pFA::GUS transgenic events were paramutagenic , while the pFB::GUS transgenic event was not ( Figure 2 and data not shown ) , suggesting that the increased production of siRNAs was not sufficient to establish paramutation . A similar lack of correlation with paramutagenic ability and production of siRNAs was previously reported for endogenous b1 alleles [24] . The observation that the b1 tandem repeats are sufficient to recapitulate paramutation with a heterologous reporter gene in maize suggested that it might be possible to transfer the maize b1 paramutation system to Arabidopsis thaliana . For Arabidopsis , a large set of well-characterized mutations affecting epigenetic regulation exist that could be tested for their involvement in paramutation . The first step was to generate transgenic loci in Arabidopsis that would be dependent on the b1 tandem repeats for their expression . Constructs were generated with three to seven b1 tandem repeats fused to the minimal −90 35S promoter and the luciferase reporter gene ( Figure 7A ) . As a control , sequences upstream of the repeats ( Figure 7A ) or b1 proximal promoter sequences ( not shown ) were used . Extensive analysis of the transgenic Arabidopsis plants containing intact transgenes revealed that all transgenic events carrying the b1 repeats exhibited a low level of luciferase activity similar to that displayed by control events with no b1 sequences ( Figure 7A and Table S3 ) . One possibility was that the transgenes integrated into a B'-like epigenetic state , which is associated with DNA methylation [19] , [21] . Analyses of methylation using DNA blot analyses ( Figure 7B and 7C , Figure S7A ) revealed low levels of DNA methylation within the repeats and no detectable methylation in sequences upstream or downstream of the tandem repeats . All 7-repeat-containing transgenic events analyzed ( pEN-MS1 and pEN-MS2 ) showed similar DNA methylation patterns compared to each other and also to that of the maize transgenes with seven repeats ( Figure 4A ) . Such uniformity among transgenic events is unusual as methylation patterns between independent transgenic events are typically more variable [30]–[33] . The transgenic events carrying four and three b1 repeats ( pEN-MS3 and pEN-MS4 ) also displayed low methylation levels within the repeats , but there was more variation between the different independent transgenic events ( Figure 7B and 7C , and data not shown ) , similar to that seen for the endogenous maize three-repeat allele [19] . Together , these results demonstrate that , in the primary transgenic plants , the transgenic repeat sequence acquired similar sparse DNA methylation in maize and Arabidopsis . During the Arabidopsis transformation process de novo DNA methylation occurs [34] , [35] . We hypothesized that preventing any DNA methylation from occurring may enable the detection of the transcriptional regulatory function of the b1 repeats . To investigate this hypothesis , an Arabidopsis line in which the de novo DNA methyltransferases drm1 and drm2 ( DOMAIN REARRANGED DNA METHYLASE 1 and 2; [34] ) were mutated , was transformed with pb1::GFP constructs carrying b1 repeat- or b1 proximal promoter sequences fused to the minimal 35S promoter and GFP ( Green Fluorescent Protein ) coding region ( Figure S7B ) . As a positive control , the 35S enhancer was fused to the GFP reporter gene ( p35S::GFP ) . None of the pb1::GFP transgenic events showed GFP expression , while all of the p35S::GFP events did ( Figure S7B and S7C , and Table S4 ) . DNA blot analyses revealed that the drm1 drm2 double mutant background did prevent DNA methylation within the b1-repeats ( Figure S7D ) , indicating that the lack of GFP expression was not due to DNA methylation . Two other possible explanations for a lack of GFP expression , RNA-directed transcriptional or post-transcriptional silencing , were tested using the appropriate Arabidopsis mutants . Constructs with either seven or three b1 repeats ( Figure S7B ) were introduced into the rdr2-1 [35] and sgs2-1/rdr6 [36] mutants . RDR2 mediates RNA-directed transcriptional gene silencing , and RDR6 post-transcriptional gene silencing . None of the transgenic plants showed GFP expression ( Figure S7B , Table S4 ) , suggesting that neither RNA-directed transcriptional or post-transcriptional silencing is responsible for the lack of GFP expression . Taken together these data suggest that the maize b1 repeats do not have transcriptional regulatory activity in Arabidopsis . As one needs transcription to study transcriptional silencing this approach is not viable to study paramutation in Arabidopsis .
Results of the transgenic analysis presented in this paper demonstrate that specific tandem repeats are sufficient to both send and respond to the paramutation signal and that the repeat sequences need not be in an allelic position to communicate . The Mop1 gene , necessary for endogenous paramutation , is also required for transgene-induced paramutation , suggesting common mechanisms . The sequences required and sufficient for paramutation are localized in the first half of the b1 repeat unit . The tandem repeats are furthermore sufficient to enhance the expression of a heterologous reporter gene in maize , but not Arabidopsis . While transgenes are capable of inducing paramutation , several key differences exist between endogenous- and transgene-induced paramutation . Endogenous b1 paramutation is stable , fully penetrant and associated with dense DNA methylation within the b1 repeats , while transgene-induced paramutation displays variation in stability , penetrance and DNA methylation levels within the transgenic and endogenous b1 repeats . Repeats have been implicated in multiple examples of paramutation [5] , [19] , [37] , [38] and other silencing phenomena ( e . g . [39]–[41] ) , but detailed mechanisms for why multiple copies are quantitatively required is not known in any system . Multiple models postulating which properties of the repeats are being counted have been discussed ( reviewed in [42] ) . Models include a quantitative increase in a repeat product such as siRNAs [43] , the quantitative binding of regulatory proteins to the repeats [44] , the extent of DNA methylation within the repeats [21] , or the creation and amplification of a unique junction fragment [21] . The transgenes were able to slightly elevate the production of siRNAs in immature ears but as we previously observed [24] there was no correlation between levels of siRNAs and the ability to participate in paramutation . These results do not exclude the possibility of a correlation between repeat siRNA levels and paramutation in other tissue types and/or developmental timepoints . Our results that tandem repeats of either the full repeat unit or the FA half are both strongly paramutagenic , yet they have distinct junctions , argues against a critical role for the junction regions . Furthermore , our observation that multiple repeats of FB have no paramutation activity strongly suggests tandem repeats of a specific sequence within FA are being counted during paramutation . The FA and FB fragments differ in several properties that could be contributing to their ability to mediate paramutation . The FA half is much more GC rich relative to FB and as such , it contains most of the differentially DNA methylated region , including “the seed region” which becomes methylated very early in development in plants undergoing endogenous paramutation [21] . One possibility is that the AT richness of FB ( 68% ) and the resulting lower capacity for cytosine methylation may prevent it from receiving and/or transmitting silencing signals . Intriguingly , the FA transgenes tended to be more strongly paramutagenic than those with the full repeat , suggesting that removal of the FB sequence increases the strength of paramutation . A full repeat is likely to have a lower overall density of DNA methylation than an FA repeat , which could be the signal being counted . It is also possible that FA , but not FB contains the regulatory sequences necessary to generate RNA silencing signals . The endogenous FB sequence is transcribed at a lower level and produces lower amounts of siRNAs relative to FA [24] , [45] . Even though FB is neither required nor sufficient for paramutation in the transgenic assay , it may contribute to endogenous paramutation . Support for this hypothesis is that overexpression of a protein that binds to FB can induce a heritable and paramutagenic silenced state at the endogenous B-I allele [44] . Future experiments such as further dissecting the minimal sequences required for paramutation , mapping the key sequences mediating transcription of the b1 repeats and characterization of additional DNA binding proteins , should help to distinguish between hypotheses . Two broad classes of models have been proposed for the allelic interaction that mediates endogenous paramutation , diffusible trans-acting signals or pairing between the repeats - these models are not mutually exclusive . Our observation that many different transgenic loci , located at distinct genomic sites , efficiently induce paramutation is most consistent with a diffusible trans-acting signal mediating the initial communication establishing paramutation . Consistent with this hypothesis , mutations in multiple genes involved in the RNA-directed transcriptional silencing pathway prevent the establishment of paramutation ( reviewed in [42] ) , suggesting RNA may be the signal . However , our transgene experiments do not eliminate repeat pairing , as there are examples of pairing between homologous sequences in non-allelic positions in other systems [46]–[48] . Future experiments employing cytological methods may be able to shed light on whether there is a role for DNA pairing in paramutation . Fine structure recombination mapping and chromosome conformation capture studies demonstrated that the b1 tandem repeats are also required for transcriptional activation of b1 [19] , [22] , but those studies could not distinguish between a direct role , i . e . the repeats carry transcriptional regulatory sequences , versus an indirect role , i . e . they mediate the ability of regulatory sequences located elsewhere to activate b1 . Our maize transgenic results demonstrate that the b1 repeats do carry sequences that can mediate transcriptional activation of heterologous reporter genes , most consistent with a direct role of the repeats in transcriptional activation . Previous chromatin immunoprecipitation experiments demonstrated that upon transcriptional activation of B-I , the repeats are relatively depleted for nucleosomes and those that remain are enriched for H3ac histone marks [21] . These two properties , which strongly correlate with active transcriptional regulatory sequences [49] , [50] , are observed in both the FA and FB halves [21] . There is only one other paramutation system ( p1 , pericarp color ) in which the sequence mediating paramutation has been defined [5] , and that sequence also contains transcriptional regulatory activity [51] , [52] . However , simply having a transcriptional regulatory element is not sufficient for paramutation as there are two transcriptional regulatory elements at p1 and only one of them can induce paramutation [5] . In contrast to the observations in maize , the b1 tandem repeats did not function as a transcriptional activator in Arabidopsis , suggesting that the transcription factors recognizing this sequence are not conserved between maize and Arabidopsis . When B-I is paramutated by the repeat transgenes , the resulting transgene-induced B'# state , while heritable , often induced paramutation at a lower frequency and was less stable relative to the endogenous B' allele-induced B' state , in spite of the sequences being identical . The fact that after the transgenes are crossed to B' , they induced a much more stable B'# state , indicates that their non-allelic positions or the structure of the transgenic loci cannot be responsible for the original reduced penetrance and heritability . Furthermore , the observation that a generation together with B' increased the transgenes' paramutagenicity , relative to carrying the transgenes over neutral alleles , suggests some type of heritable epigenetic mark is accumulating . Precedence for a role for DNA methylation has been reported in Arabidopsis where the RNA-directed transcriptional silencing machinery requires the presence of pre-existing DNA methylation on the endogenous FWA locus for effective silencing of an incoming FWA transgene [40] . This may not be the case with paramutation in maize , as two transgenes with very low DNA methylation levels could induce paramutation of the endogenous allele . Our results do indicate that specific sequences within the FA region of the repeat are a critical component and given that most of the DNA methylation marks are within this region , it remains possible that DNA methylation marks contribute to the strength of paramutation . Further studies of multiple transgenic events will be required to test this hypothesis .
The b1 stocks were initially acquired from a variety of sources and have been maintained in the Chandler laboratory for a number of years . The B' , B-I and neutral b1 alleles were obtained from E . H . Coe , Jr . ( University of Missouri , Columbia ) and B-P was obtained from M . G . Neuffer ( University of Missouri ) . All maize plant stocks used in this study carry functional alleles for all biosynthetic genes and the other regulatory genes required for anthocyanin biosynthesis , unless otherwise indicated . All genetic tests were conducted in the irrigated field conditions in Tucson , Arizona . The seed stocks used were wild type Arabidopsis thaliana ( ecotype WS ) and the previously described mutants drm1 drm2 ( ecotype Ws-2; [34] ) , rdr2 ( ecotype Col-0 , SAIL_1277H08; [35] ) and rdr6 ( sgs2 , Col-0 [36] ) . All Arabidopsis plants were grown under standard greenhouse conditions . The pB clone ( Figure 1A ) contains 106 . 6 kb of sequences upstream of the b1 transcription start site plus exon one , two and part of exon three ( also named pBACB'1 in [20]; accession AY078063 ) . The pBΔ clone was produced by digesting pB with the SwaI restriction enzyme , removing 91 . 6 kb of internal sequences and religation of the remaining sequences [20] . To produce the pFA and pFB transgenes , the two halves of the repeat were PCR amplified and inserted one by one in the BamHI/BglII digested P1 . 0b::GUS plasmid [51] . The p35S::GUS construct ( Figure 5A ) was the same as −90 35S::GUS described in [53] and contained the minimal −90 bp Cauliflower Mosaic Virus 35S promoter ( 35S ) , the maize adh1gene intron1 , the omega leader , the beta-glucuronidase ( GUS ) coding region , and the potato PinII terminator . To produce the pb1TR::GUS construct , the seven 853 bp repeat array was inserted in the p35S::GUS construct upstream of the 35S promoter . To produce the pFA::GUS and pFB::GUS constructs , the FA and FB tandem repeats were ligated upstream of the 35S promoter of the p35S::GUS construct , respectively . Primer information and detailed information on cloning and vectors used for plasmid construction is presented in the Methods S1 . Transgenic maize plants were generated at the Iowa State University Plant Transformation Facility using biolistic particle bombardment of Hi-II immature embryos , which carry a neutral b1 allele ( b-N ) [54] , [55] . The plasmid pBAR184 carrying the BAR gene , which confers resistance to the herbicide bialaphos , was co-bombarded with each construct [55] . Herbicide resistant calli were screened for DNA of interest using DNA blot analysis . Transformation events carrying transgene copies of the b1 repeat DNA were regenerated from calli . The first set of plasmids used for Arabidopsis transformation carried the luciferase reporter gene ( Figure 7A ) . These plasmids were made by inserting fragments of the maize b1 gene in front of a −90 35S promoter fused to the omega leader , luciferase coding region and nopaline synthase ( nos ) polyadenylation signal . The second set of the plasmids contained a GFP reporter gene ( Figure S7 ) . These plasmids were produced either by replacing the luciferase reporter gene by a GFP reporter gene from the pFLUAR100 plasmid [56] or by transferring the b1 sequences to an intermediate plasmid containing the 90 bp-35S promoter-GFP-nos gene cassette . A detailed description of the cloning steps and vectors used for plasmid construction is provided in the Methods S1 . Arabidopsis plants were transformed as described by [57] using 5% sucrose , 0 . 05% Silwet L-77 , 0 . 5× Murashige & Skoog basal salts ( micro and macro elements; Duchefa ) . The dipped plants were covered with Saran wrap , placed in the dark the first night and then grown in the greenhouse to maturity . To screen for transgenic plants , depending on the binary vector used , fluorescent seeds were either selected using the Leica MZ FLIII stereo fluorescence microscope with a dsRed filter or seedlings were sprayed with 0 . 5% BASTA ( Glufosinate ) twice , two and three weeks after sowing in soil , and surviving plants were transferred to individual pots . Transgenic plants were examined for reporter gene expression . Luciferase activity was evaluated using the Luciferase Assay System ( Promega ) and GFP activity was examined using the Leica MZ FLIII stereo fluorescence microscope with a GFP2 and GFP3 filter . Transgenic maize calli were ground in liquid nitrogen and incubated with extraction buffer ( 200 mM Tris-HCl pH 7 . 5; 250 mM NaCl; 25 mM EDTA pH 8 . 0; 0 . 5% SDS ) for 10 minutes , followed by phenol∶chloroform ( 1∶1 ) and chloroform extraction . DNA was precipitated with 1/10 of the volume of 3 M NaOAc and an equal volume of isopropanol . Pelleted DNA pellet was washed with 70% ethanol and resuspended in TE ( 10 mM Tris-HCl pH 8 . 0; 1 mM EDTA ) . DNA extraction from maize leaves and Arabidopsis flower heads was performed according to [58] , [59] , respectively . For DNA blot analysis 4–5 µg of maize and 0 . 5–2 . 5 µg of Arabidopsis genomic DNA was digested with the appropriate restriction enzyme ( s ) following the manufacturer's specifications , size-fractionated by electrophoresis in 0 . 5× TBE 0 . 8–1 . 5% agarose gels , transferred to positively charged nylon membranes , fixed by UV fixation and hybridized with 32P labeled DNA probes as described [26] . All blots that contained samples digested with DNA methylation sensitive enzymes were probed with a fragment ( Probe A [19] ) that recognizes sequences that are not methylated in maize to confirm all restriction enzymes cut the DNA to completion [19] followed by hybridization to the b1 repeat probe . Details describing probe fragments and restriction enzymes used for DNA blot analysis of maize and Arabidopsis transgenes are in Methods S1 . Copy number of b1 repeat units in maize transgenic plants was estimated using the software packages Quantity One ( Biorad ) for pB and pBΔ , and ImageJ [60] for pFA and pFB . Copy number was calculated and normalized to the intensity of a single copy band of one the endogenous b1 allele present in each lane . Description of PCR-based genotyping of the endogenous b1 alleles and the mop1-1 mutation is presented in Methods S1 . Small RNA fractions were extracted from young , immature ( ∼5 cm ) maize ears as described by [24] . RNA was separated on denaturing polyacrylamide gels , hybridized with 32P end-labeled DNA/LNA b1 repeat ( VC1657F , [24] ) and U6 ( 5′-CGTGTCATCCTTGCGCAGGGGCCATGCTAATCTTCTCTGTATCGT-3′ ) oligos . Results were analysed similarly to described previously [24] . Tissues from transgenic plants ( Figure 5 and Figure S6 ) were collected between ∼50–60 days after germination and incubated with 1 ml of 0 . 1% X-GLUC solution ( 5-bromo-3-chloro-2-indolyl-b-D-glucuronic acid , Sigma ) in the dark at 37°C for 24 hours [52] . Chlorophyll pigment was removed by repeated incubations in 70% ethanol . Stained tissues were analyzed under a binocular microscope and categorized according to the staining levels shown in Figure 5B and Figure S6B .
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Paramutation is a fascinating process in which genes communicate to efficiently establish changes in their expression that are stably transmitted to future generations without any changes in DNA sequences . While paramutation was first described in the 1950s and extensively studied through the 1960s , its underlying mechanism remained mysterious for many years . Over the past ten years paramutation at the b1 locus in maize was shown to require transcribed , non-coding tandem repeats located 100 kb upstream of b1 . These repeats generate small RNAs , and mutations in multiple genes mediating small RNA silencing at the transcriptional level prevent paramutation . While underlying mechanisms are shared , current models for RNA-mediated transcriptional silencing that are based on experiments with S . pombe and Arabidopsis do not explain many aspects of paramutation . In this manuscript we used a transgenic approach to demonstrate that the b1 non-coding tandem repeats are sufficient to send and respond to the paramutation signals and that this occurs even when the repeats are not at their normal chromosomal location .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2013
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Specific Tandem Repeats Are Sufficient for Paramutation-Induced Trans-Generational Silencing
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The isoprenoid biosynthetic pathway leading from the production of mevalonate by HMGCoA reductase ( Hmgcr ) to the geranylation of the G protein subunit , Gγ1 , plays an important role in cardiac development in the fly . Hmgcr has also been implicated in the release of the signaling molecule Hedgehog ( Hh ) from hh expressing cells and in the production of an attractant that directs primordial germ cells to migrate to the somatic gonadal precursor cells ( SGPs ) . The studies reported here indicate that this same hmgcr→Gγ1 pathway provides a novel post-translational mechanism for modulating the range and activity of the Hh signal produced by hh expressing cells . We show that , like hmgcr , gγ1 and quemao ( which encodes the enzyme , geranylgeranyl diphosphate synthetase , that produces the substrate for geranylation of Gγ1 ) are components of the hh signaling pathway and are required for the efficient release of the Hh ligand from hh expressing cells . We also show that the hmgcr→Gγ1 pathway is linked to production of the germ cell attractant by the SGPs through its ability to enhance the potency of the Hh signal . We show that germ cell migration is disrupted by the loss or gain of gγ1 activity , by trans-heterozygous combinations between gγ1 and either hmgcr or hh mutations , and by ectopic expression of dominant negative Gγ1 proteins that cannot be geranylated .
Two distinct cell types , the primordial germ cells and the somatic gonadal precursor cells ( SGPs ) , coalesce to form the Drosophila embryonic gonad ( for review , see [1] , [2] ) . These cells arise in different regions of the embryo and are specified by completely different mechanisms . The SGPs are derived from the lateral mesoderm in parasegments 10–13 during mid-embryogenesis and are specified by the input from a combination of cell-cell signaling pathways and zygotic patterning genes [3] , [4] . By contrast , the primordial germ cells , or pole cells , are formed on the outside surface of the embryo at the posterior end during the syncitial blastoderm stage and are specified by determinants localized in the posterior pole plasm during oogenesis [5] , [6] . In order for pole cells to assemble into a gonad with the SGPs , they must traverse from the posterior end into the middle of the embryo and then subsequently move to the lateral mesodermal cell layer , which contains the newly formed SGPs . This is a multistep process that begins at gastrulation when the pole cells are carried into the interior of the embryo by the midgut invagination [1] , [2] . They then pass through the midgut epithelium , and move along the surface of the midgut until they split into two groups . The germ cells in each group migrate laterally and this brings them into contact with the gonadal mesoderm on either side of the embryo . The germ cells align themselves in a row with the SGPs in parasegments 10-13 and these juxtaposed cells coalesce into the embryonic gonad . Analysis of the different migration steps has suggested that a combination of repulsive and attractive cues guide germ cell migration through the midgut and toward the somatic gonadal mesoderm . Repulsive clues , whose production depends upon Wunen and Wunen2 , are thought to hasten the movement of the germ cells away from the midgut epithelium [7] , [8] . Once the germ cells exit the midgut and migrate along its surface , attractive cues produced by the SGPs are thought to entice the germ cells towards that lateral mesoderm and promote their subsequent association with the SGPs . One of the first genes implicated in the production of the germ cell attractant by the SGPs was hmgcr [9] . hmgcr is initially expressed broadly in the embryonic mesoderm; however , by the time germ cells commence their migration into the mesoderm , hmgcr expression is largely restricted to the SGPs [9] . In hmgcr mutants germ cells fail to migrate towards the SGPs and instead either remain associated with the midgut or scatter through the mesoderm . Conversely , ectoptically expressed hmgcr can induce germ cells to migrate towards tissues expressing the Hmgcr protein . Another gene that functions to induce migration towards the SGPs encodes the signaling molecule hedgehog ( hh ) [10] . Both ectopic expression of Hh and mutations that compromise the production or transmission of the Hh ligand by the SGPs induce mismigration . Since Hh functions as a morphogen in other contexts , one explanation for its effects on germ cell migration is that it acts indirectly by inducing cells to assume a SGP identity so that they can produce the actual attractant . However , a number of findings argue that Hh acts directly as an attractant . For one , the two known receptors of the Hh signal , Patched ( Ptc ) and Smoothened ( Smo ) are required in the germ cells for their proper migration . In the absence of the Hh ligand , the transmembrane receptor Ptc inhibits the 7-pass transmembrane protein Smo from mediating signal transduction [11]–[13] . When Hh binds to the Ptc receptor , the physical association between these two proteins is thought to relieve the negative influence of Ptc resulting in the relocalization of Smo to the cell membranes , and this in turn activates the signal transduction cascade downstream of the Hh signal . Consistent with their reciprocal functions in hh signaling , germ cells compromised for ptc or smo activity behave differently . For ptc the germ cells clump prematurely near the midgut as if they had already received the full Hh signal . For smo the germ cells behave as if they are ‘signal-blind’ and scatter randomly in the posterior of the embryo [10] . A second line of evidence supporting a direct role for Hh as the germ cell attractant comes from the discovery that hgmcr is required for the release of the Hh ligand by hh expressing cells . In embryos compromised for hmgcr activity [14] , Hh is inappropriately retained in the hh expressing cells . Conversely , the range and strength of the Hh signal can be substantially enhanced by ectopic expression of hmgcr . Critically , ectopic hmgcr only had an effect on hh signaling when it was expressed in cells that normally produce the Hh ligand , while there was no effect when hmgcr is ectopically expressed in cells that normally receive the Hh ligand . One important issue left unresolved by these studies is how hmgcr promotes the release of the Hh ligand by hh expressing cells . The hmgcr gene encodes HMGCoA reductase which is responsible for the conversion of 3-hydroxy-3-methylglutaryl coenzyme A to mevalonate . In mammals , mevalonate is a precursor for cholesterol which is used in the modification of the Hh protein . However , providing precursors for cholesterol biosynthesis is not a likely function for hmgcr in the hh signaling pathway as the genes encoding the enzymes required to synthesize cholesterol from appear to be absent in flies [15] . Mevalonate is also a precursor for many different compounds including carotenoids , isoprenoids , ubiquitones and vitamins A and E [16] . Recent studies by Santos and Lehmann [15] on the role of hmgcr in germ cell migration have implicated the isoprenoid branch of the mevalonate precursor pathway . The isoprenoids farnsyl-pyrophosphate ( FPP ) and geranylgeranyl-pyrophosphate ( GGPP ) are used in the posttranslational modification of proteins and are covalently attached to the C terminus of target proteins by farnysyl transferase and type I or type II geranylgeranyl transferases respectively . Santos and Lehmann showed that mutations in farnesyl-diphosphate synthetase ( fpps ) ( which synthesizes FPP ) , geranylgeranyl diphosphate synthetase ( qm ) ( which in turn converts FPP to GGPP ) , and geranylgeranyl transferase type I ( β-ggt1 ) disrupt germ cell migration . They also found that germ cell migration is perturbed when fpps and qm are ectopically expressed . Though the effects were much less dramatic than observed for ectopic hmgcr , this is not altogether unexpected since these two genes differ from hmgcr in that they are widely expressed in mid-to-late embryogenesis . While these findings indicate that the pathway leading from hmgcr to GGPP is important in germ cell migration because some critical target protein requires geranylation , the identity of this protein and the nature of its function in the production of the germ cell attractant remain to be established . Additionally , Santos and Lehmann [15] did not test whether hh signaling also depends upon this same isoprenoid biosynthetic pathway . Thus , the possibility remains open , especially if there is another germ cell attractant besides Hh , that hmgcr has some other function in hh signaling beside the production of isoprenoids . A possible answer to these questions comes from recent studies on cardiac development in flies . Hmgcr and downstream enzymes in the mevalonate pathway are required in cardioblasts to ensure their proper adhesion to the neighboring pericardial cells . Yi et al . [17] found that the endpoint for the isoprenoid branch of the hmgcr mevalonate pathway in heart development is the geranylgeranylation of the heterotrimeric G protein γ subunit 1 ( Gγ1 ) [17] , [18] . The C-terminus of the Drosophila Gγ1 protein has the isoprenylation CAAX motif sequence , Cys-Thr-Val-Leu . The leucine residue at the terminal position ( X ) specifies lipid modification by geranylgeranylation . Gγ1 requires this modification for membrane association and is inactive when geranylation is blocked . Significantly , gγ1 would be a quite plausible downstream target for hmgcr activity in the hh signaling pathway ( and thus in the production of the germ cell attractant ) . Though heterotrimeric G proteins are normally thought to mediate the transduction of extracellular signals by G-protein coupled receptors , recent studies indicate that these G protein complexes have other intercellular functions . In particular , the Gγ1:Gβ heterodimer together with Gα have been implicated in the transport of cargo from the trans-Golgi network ( TGN ) to the basolateral plasma membrane [19]–[21] . The involvement of machinery targeting proteins to the basolateral membrane from the TGN would make sense in the context of hh signaling as autoprocessed and fully modified Hh protein is found to preferentially accumulate in a punctate pattern along the basolateral membranes of Hh expressing cells in the embryonic ectoderm [22]–[24] . This protein is then released from the cell , through a Dispatched ( Disp ) dependent mechanism that is thought to involve translocation of the Hh puncta from their docking sites along the basolateral membranes to the apical membrane [25] , [26] . In the studies reported here we have asked whether the hmgcr→Gγ1 pathway is important for hh signaling and whether gγ1 is required for proper germ cell migration as is the case for hmgcr .
To test whether gγ1 is a component of the hh signaling pathway , we took advantage of the hhMoonrat ( hhMrt ) mutation [27] . hhMrt is a dominant gain-of-function hh allele that disrupts patterning of the wing as a heterozygote and is lethal as a homozygote . In wild type wing discs , hh expression is confined to the posterior compartment and it orchestrates wing development by signaling to cells in the anterior compartment along the compartment boundary to upregulate the expression target genes such as ptc and decapentaplegic ( dpp ) . In hhMrt/+ animals , in addition to being expressed normally in the posterior compartment , hh is ectopically activated in the anterior compartment of the wing disc . As a result dpp is expressed in a pattern that leads to overgrowth of the anterior tissues and the partial duplication of distal wing structures . The anterior-to-posterior transformations induced by the hhMrt allele can be dominantly suppressed by mutations in hh signaling pathway genes like disp and hmgcr that are required to promote hh signaling in the sending cells . The gain-of-function wing phenotype can also be suppressed by mutations in genes like toutvelu ( ttv ) that are required to promote hh signaling in the receiving cell ( unpublished data ) . If gγ1 functions as the downstream target for hmgcr in the hh signaling pathway , then mutations in gγ1 would be expected to dominantly suppress the hhMrt wing defects . To test for suppression we used two different gγ1 mutants . The first , gγ1N159 , is an EMS induced mutation [28] . The gγ1 open reading frame encodes a protein of 70 amino acids and this mutation inserts a stop codon at amino acid 59 . The second , gγ1k0817 , has a P-element insertion in the splice donor of the first gγ1 exon and produces aberrant transcripts . To assess the effects of these gγ1 mutations , the Mrt wing blades were assigned to 5 different classes based on the severity of the wing defects , with I being wild type ( not shown ) , and V being the most severely deformed wing ( not shown , for details see 27 ) . Under the conditions of this experiment about 70% of the hhMrt/+ flies were abnormal ( see the class III wing in panel A of Figure 1 ) . By contrast when the hhMrt/+ flies were heterozygous for gγ1N159 quite strong suppression was observed and more than 80% of the wings belonged to class I ( panel B ) . The suppression of the Mrt gain-of-function phenotype does not appear to be due to some non-specific background effect as the wing defects could also be dominantly suppressed by gγ1k0817 ( data not shown ) . Thus like hmgcr and other factors that function to promote hh signaling , gγ1 shows genetic interactions with the hhMrt . Moreover , the extent of suppression is similar to that observed previously with hmgcr [14] . The dominant suppression of the Mrt wing phenotypes suggests that like hmgcr , gγ1 functions in hh signaling . To test this possibility further we examined wingless ( wg ) expression during embryogenesis . In wild type embryos , wg stripes are activated by the pair-rule genes at the onset of gastrulation . Once the pair-rule gene products decay later in embryogenesis the maintenance of the wg expression depends upon hh signaling by the cells immediately posterior to the wg stripe and in hh mutants wg expression begins disappearing by stage 10/11 of embryogenesis . Maintenance of the wg stripes also requires hmgcr activity and in hmgcr mutant embryos the stripes begin to fade around stage 11 . However , unlike hh mutants , residual wg expression can still be detected in older hmgcr mutant embryos . Since maternal and zygotic hmgcr activity cannot be completely eliminated , this difference likely reflects ( at least in part ) the presence of residual Hmgcr in the hmgcr mutant embryos . If gγ1 functions downstream of hmgcr in the hh signaling pathway , then defects in wg expression should also be evident in gγ1 mutant embryos . To determine if this is the case we compared wg expression in gγ1− embryos with their heterozygous gγ1−/+ sibs . We found that wg expression in the homozygous mutant embryos is initially like wild type ( or gγ1−/+ ) ; however as shown in Figure 2B for gγ1N159 , the accumulation of Wg protein begins to decrease around stage 11–12 ( compare the gγ1N159 homozygote in panel B with the gγ1N159/+ sib control in panel A ) . Similar results were obtained for the gγ1k0817 ( compare panel C and D in Figure 1 ) . The extent of reduction in Wg protein in the two gγ1 mutants is not as severe as that seen in embryos compromised hh; however , as noted above this was also observed for hmgcr and likely reflects the perdurance of the maternally derived Gγ1 . Another gene whose expression in mid-embryogenesis depends upon hh signaling is engrailed ( en ) . en is part of an autoregulatory loop that is established between the neighboring hh and wg expressing cells . en is transcribed in the hh expressing cells in response to the Wg ligand . When wg signaling is disrupted because of a reduction in hh signaling , en transcription is in turn downregulated . As would be expected from the effects of gγ1 mutations on wg expression , we find that the accumulation of En protein is reduced in embryos homozygous mutant for both of the gγ1 alleles compared to their wild type ( gγ1−/+ ) sibs ( see Figure S1 ) . While the effects of gγ1 mutations on wg and en expression would be consistent with a role in hh signaling , it is also possible that gγ1 activity is required at some other point in the hh-wg autoregulatory loop , for example , in the expression of the Wg or En proteins . For this reason we next examined the effects of gγ1 on the Smo receptor which is a more direct target for the Hh ligand in the receiving cells . Upon reception of the Hh signal the Smo receptor is relocalized from intracellular membrane vesicles to the cell surface [29] , [30] . When hh signaling is compromised , this relocalization does not occur , and the Smo protein remains predominantly cytoplasmic in the receiving cells . Since Smo is not properly relocalized in hmgcr mutant embryos , a similar defect would be expected in gγ1 mutants if gγ1 functions downstream of hmgcr in the hh signaling pathway . Figure 3 shows that this prediction holds . In this experiment we compared the localization of the Smo receptor in homozygous gγ1 mutant embryos with their heterozygous sibs . The pattern of Smo accumulation in the heterozygous gγ1−/+ embryos ( panels A and B ) resembles wild type . There are a series of stripes that are approximately 5 cells wide in which the Smo protein is largely localized to the plasma membrane . These stripes are separated from each other by an equivalent band of about 5 cells that have a lower level of Smo at the surface of the cell . In homozygous gγ1 mutant embryos this Smo distribution pattern is disrupted . Although a weak stripe pattern can still be discerned in the homozygous mutant embryos ( see panel C ) it is much less distinct than in the heteterozygous sibs ( panel A ) . Panel D shows that Smo remains largely cytoplasmic in most of the cells in each segment and is not tightly localized at the plasma membrane as it is in wild type or gγ1−/+ heterozygous embryos . The finding that Smo protein does not properly relocalize in gγ1 mutant embryos would be consistent with the idea that Gγ1 acts downstream of hmgcr to promote the efficient release and/or transport of Hh protein . To test this hypothesis further , we compared the pattern of Hh accumulation in gγ1 mutant embryos with their heterozygous sibs . The distribution of Hh protein in gγ1−/+ embryos resembles that seen in wild type [22]–[26] . Hh is expressed in each parasegment in a two cell wide stripe , and most of the protein in these Hh expressing cells is distributed in the cell membrane in a fine grain or punctate pattern ( see arrowheads in panel A of Figure 4 ) . Emanating in both directions from the two cell wide stripe is an Hh protein gradient that appears to extend through much of the parasegment . In this gradient the highest levels of Hh protein are observed associated with cells adjacent to the two Hh expressing cells , while lower levels of protein are found in more distant cells . The distribution of Hh protein in gγ1 mutant embryos ( panels B and C ) resembles that seen in hmgcr mutant embryos [14] . First , in spite of the fact that the overall level of Hh expression is expected to be reduced in these embryos because of the disruption in the wg-hh positive autoregulatory loop ( see above ) , the relative amount of Hh in cells in the hh stripes appears higher than in wild type embryos , while there is a concomitant reduction in the amount of Hh in the gradient that extends through the interstripe region ( compare panels A with B & C ) . Second , the normal grainy or punctate pattern of Hh protein localized around the basolateral membrane of the hh expressing cells that is seen in wild type embryos ( see arrows in panel A and in the enlargement in panel D ) is largely lost . Instead , Hh accumulates in larger “clumps” or aggregates ( see arrows in panels B and C and in the enlargement in panels E and F ) that in many instances seem to be displaced from the cell membranes ( see top arrows in panel E and F ) . The results described in the previous sections demonstrate that like hmgcr , gγ1 is required for the efficient release/transmission of the Hh ligand by hh producing cells . Since the role of the isoprenoid branch of the hmgcr mevalonate pathway in heart development is the geranylgeranylation of Gγ1 , a plausible idea is that the function of hmgcr in hh signaling is to provide substrates for the modification of the Gγ1 protein . If this model is correct , then gene products that are downstream of hmgcr in the geranylgeranylation pathway should also be required for the release/transmission of the Hh ligand . To test this prediction we examined the distribution of Hh protein in qm mutant embryos . As described above , qm encodes geranylgeranyl diphosphate synthetase and this enzyme produces the substrate , GGPP , that is used by the geranyl transferase to modify Gγ1 . Figure 5 shows the distribution of Hh in a homozygous qm mutant embryo ( panel B ) and its heterozygous qm−/+sibs ( panel A ) . As observed for both hmgcr [14] and gγ1 ( see above ) , the Hh ligand is inappropriately retained in the hh producing cells in the qm mutant embryos ( compare Hh distribution in panels A and B ) . Like gγ1 the characteristic punctate distribution of Hh protein around the membranes of hh expressing cells ( arrowheads in pane A ) is reduced or lost and instead Hh accumulates in clumps or large aggregates ( arrows in panel B ) . It should also be noted that this particular qm mutation appears to cause a more pronounced defect in the release/transmission of the Hh ligand than is observed for gγ1 ( compare Figures 4 and 5 ) , while the defects in Hh distribution evident in hmgcr mutant embryos [14] are roughly intermediate between that in qm and gγ1 . The findings describe above indicate that gγ1 represents an endpoint for the isoprenoid branch of the hmgcr mevalonate pathway in the hh signaling pathway , and that like hmgcr , gγ1 is required for the efficient release/transmission of the Hh ligand . Since several components of this hmgcr mevalonate→isoprenoid pathway have also been implicated in the production or transmission of the germ cell attractant by the SGPs [15] , we tested whether mutations in gγ1 have any effects on germ cell migration . Embryos collected from gγ1k0817 and gγ1N159 stocks carrying an en:LacZ marked 2nd chromosome balancer were stained with b-galactosidase antibodies to identify the homozygous mutant embryos and Vasa antibodies to visualize the germ cells . In wild type embryos ( or in gγ1−/Cyo en:LacZ embryos ) germ cells associate with the SGPs in parasegments 10–13 at stages 12–13 ( see stage 13 WT embryo in Figure 6A ) and the two cell types coalesce into the embryonic gonad at stages 14–15 ( see stage 15 WT embryo Figure 6B ) . Although germ cells that fail to coalesce into the embryonic gonad are sometimes seen in wild type embryos , the number of lost germ cells is generally rather low . The germ cells in gγ1− embryos appear to have no difficulty in exiting the midgut pocket at stage 9–10 , while movement along the surface of the midgut also appears to be comparatively normal . However , as illustrated in panel C of Figure 6 , defects in migration are clearly evident by stage 13 . In this embryo , several of the germ cells are not properly aligned with the SGPs in PS10–13 ( compare with wild type in panel A ) . This problem persists and in stage 15 gγ1− embryos germ cells that haven't coalesced into the embryonic gonad can be seen scattered in the posterior ( see panel D ) . Quantitation indicates that in wild type the vast majority ( 90% ) of the stage 15 embryos ( n = 20 ) have few if any ( 0 to 2 ) scattered germ cells . In contrast , about 36% of the gγ11N159 embryos ( n = 20 ) have 3 to 4 scattered germ cells while nearly 40% have 5 or more scattered germ cells . Similar results were obtained for the second gγ1 allele , gγ1k0817 ( see Figure S2 ) . Though the severity of the germ cell migration defects in the two gγ1− mutants is similar to that reported for embryos zygotically compromised for either fpps or qm , it is not as strong as that observed for hmgcr mutant embryos [9] , or for embryos that lack both zygotic and maternal ( m− z− ) fpps [15] . While compromising both maternal and zygotic gγ1 would likely increase the severity of the germ cell migration defects as seen for fpps , the very severe patterning abnormalities observed in m−z− embryos [28] would make effects on germ cell migration impossible to interpret . These findings indicate that gγ1 is involved in germ cell migration just like the three enzymes , fpps , qm and β-GGT1 that are downstream of hmgcr in the geranylgeranylation branch of the mevalonate pathway . Ectopic expression of hmgcr , qm or fpps can induce the production of the germ cell attractant in inappropriate tissues . This ectopic source of attractant competes with the attractant produced by the SGPs and confuses the germ cells , disrupting their migration towards the SGPs [9] , [15] . If gγ1 is functioning in the same pathway as these three enzymes , then it should also be possible to confuse germ cells by ectopically expressing gγ1 . To test this hypothesis , females carrying the CNS driver elav-GAL4 were mated to males carrying a UAS transgene that drives a flag-tagged Gγ1 protein and the resulting elav-GAL4/UAS-flag gγ1 embryos were stained with Vasa antibodies to mark the germ cells . Figure 6E and 6F show that misexpression of Gγ1 in the central nervous system leads to a weak but reproducible germ cell migration defect . In wild type 90% of the stage 14–15 embryos have 0–2 scattered germ cells , while about 10% have 3 or more scattered or lost germ cells . In contrast in elav-GAL4/UAS-flag gγ1 embryos ( n = 51 ) , more than 40% of the embryos have 3 or more lost germ cells . The effects of elav driven Gγ1 expression are less than that reported for elav driven Hgmcr expresson ( 100% have 3 or more scattered germ cells ) but equivalent to that observed for elav dependent misexpression of either Fpps or Qm ( approximately 40% with 3 or more scattered germ cells: see 15 ) . In previous studies we found that expression of Hmgcr protein in hh producing cells was much more effective in inducing aberrant germ cell migration than when it was expressed in hh receiving cells . If gγ1 functions downstream of hmgcr in the production of the germ cell attractant , then ectopic Gγ1 should also have a more pronounced effect on germ cell migration when it is expressed in hh producing cells then when it is expressed in hh receiving cells . The experiment in Figure 7A shows that this prediction holds . There is little or no effect on germ cell migration when Gγ1 expression is induced in hh receiving cells by a ptc-GAL4 driver . In this case , less than 10% of the embryos have 3 or more lost germ cells , which is comparable to that seen in wild type embryos ( see bar graph in Figure 7A ) . In contrast , nearly one half of the embryos have 3 or more lost germ cells when Gγ1 is expressed in hh producing cells under the control of hh-GAL4 driver ( Figure 7A ) . While this result indicates that like Hmgcr , Gγ1 must be misexpressed in hh producing cells in order to induce aberrant germ cell migration , it is important to note that the effects of ectopic Gγ1 are less severe than that produced when Hmgcr expression is driven by the same hh-GAL4 driver [10] . Consistent with this difference , we do not observe any obvious alteration in the parasegmental distribution of Hh protein in UAS-gγ1/hh-GAL4 embryos ( not shown ) . By contrast , substantially more Hh protein is found in the interstripe regions when Hmgcr expression is driven by hh-GAL4 in hh producing cells [10] . While there are few if any defects in germ cell migration in hmgcr−/+ embryos , synergistic interactions are observed when hmgcr− is combined with mutations in two components of the hh signaling pathway hh and disp [10] . The perturbations in germ cell migration observed in the trans-heterozygotes taken together with the effects of hmgcr on the release/transmission of the Hh ligand from hh producing cells lent support to the hypothesis that the primary function of hmgcr in the production of the germ cell attractant by the SGPs is to potentiate the Hh signal emanating from these cells . Since the results presented above suggest that gγ1 also functions in the release/transmission of the Hh ligand , we wondered whether equivalent synergistic genetic interactions would also be observed for gγ1 . We first tested for interactions between gγ1 and hmgcr . Like hmgcr , there are at most only very modest defects in germ cell migration in gγ1N159/+ embryos . However , more than 60% of the trans-heterozygous embryos have 7 or more lost germ cells ( see Figure 8A ) . Next we tested for genetic interactions between gγ1N159/+ and hh . As shown in Figure 8B , the minor germ cell migration defects observed in hh−/+ embryos are greatly enhanced when the hh mutation is combined with gγ1N159 . These results support the idea that gγ1 could function in the germ cell migration pathway by facilitating the release/transmission of the Hh ligand . The results described in the previous sections suggest that the hmgcr mevalonate pathway is required in germ cell migration because gγ1 must be geranylgeranylated in order for it to potentiate Hh signaling by the SGPs . To test this idea further , we examined the effects of misexpressing either the wild type Gγ1 or Gγ1 proteins that have mutations in the C-terminal CTVL geranylgeranylation motif in the mesoderm using a twist-GAL4 driver . We anticipated that misexpressing wild type Gγ1 using the twist driver would induce aberrant germ cell migration because it would inappropriately potentiate signaling by hh expressing cells elsewhere in the mesoderm such as the fat body precursor cells ( FBP ) . The hh signal emanating from these cells would compete with the signal from the SGPs , and this would confuse the migrating germ cells . The results shown in Figure 7B indicate that this expectation is met . While there are only a few wild type embryos in this experiment which have more than 2 lost germ cells , more than half of the twist-GAL4:UAS-gγ1 embyros have at least 3 lost or mismigrated germ cells . We also anticipated that misexpressing Gγ1 proteins that have mutations in the C-terminal geranylgeranylation motif would induce germ cell migration defects as well . Gγ1 forms a heterodimer with a second G protein Gβ and together these two proteins interact with a third G protein , Gα to form a heterotrimeric complex . In order to form a functional complex with Gα and also interact with other factors and effectors , the Gβ:Gγ1 heterodimer must be anchored to the membrane and this is thought to be dependent upon geranylgeranylation of the Gγ1 protein [31] , [32] . We reasoned that Gγ1 mutant proteins that cannot be geranylated would likely behave as dominant negatives because they would compete with the endogenous Gγ1 protein for complex formation with Gβ , and thus reduce the effective concentration of functional membrane bound Gγ1:Gβ heterodimers . This idea is support by studies on the Drosophila eye specific Gγ protein Gγe . The C-terminal sequence Gγe is C-V-I-M which corresponds to the signal for farnesylation rather than geranylgeranylation . Mutations in Gγe that eliminate farnesylation have no effect on the formation of Gγe:Gβe heterodimers; however , these heterodimers do not interact with the membrane and are non-functional [32] . When the mutant Gγe protein is overexpressed it competes with the endogenous Gγe protein for heterodimer formation with Gβe , reducing the amount of functional membrane associated Gγe:Gβe heterodimers and disrupting signal transduction . If gernaylation defective Gγ1 proteins also behave like dominant negatives , they would be expected to interfere with the efficient release of the germ cell attractant by the SGPs when they are ectopically expressed in mesodermal cells and this should perturb germ cell migration . We tested two different Gγ1 mutant proteins , one in which the C-terminal CTVL motif is deleted ( Gγ1-ΔCAAX ) and the other in which the geranylated Cys residue is replaced by Ser ( Gγ1-C67S ) [16] . As shown in Figure 7B and Figure S3 , ectopic expression of the Gγ1-ΔCAAX protein disrupts germ cell migration and about 75% of the twist-GAL4/UAS-gγ1-ΔCAAX transgene embryos have 3 or more lost germ cells . ( Note: Figure S3 shows that ectopic expression of Gγ1-ΔCAAX in germ cells also disrupts their migration . ) With the caveat that there may be differences in expression levels of the UAS transgene , it would appear that the germ cell migration defects induced by the geranylation defective Gγ1-ΔCAAX protein are somewhat more pronounced than those observed with wild type Gγ1 . Consistent with this possibility , the Gγ1-C67S mutant protein also induces more extensive germ cell migration defects than wild type ( not shown ) .
Hh functions as an instructive cue in many different biological contexts . The signaling molecule is secreted from hh expressing cells and it induces morphogenesis in a concentration dependent fashion in neighboring cells by regulating the transcription of downstream target genes . Several mechanisms control the range and inductive activity of the Hh protein . These include the autoprocessing and lipidation [33]–[35] . Hh has two different lipid modifications that are important for the proper functioning of the Hh ligand . One is the palmitoylation of the N terminus which seems to be critical for signaling activity , while the other is the addition of cholesterol to the C terminus . The C-terminal cholesterol moiety is thought to be important for the dimerization of the Hh protein and for its assembly into LPSs ( Large Punctate Particles ) prior to secretion [36]–[39] . The LPSs appear to be lipid vesicles or micelles and they are thought to provide a hydrophobic environment for the lipid modified Hh which facilitates its movement through the extracellular matrix after it is secreted . The release and subsequent transport of the Hh ligand also requires specialized proteins that function in either Hh producing cells or in cells/compartments that are destined to receive the Hh ligand . The transporter class protein , Disp , and a secreted protein Shifted ( Shf ) are required in hh expressing cells for the efficient release and transmission of the Hh ligand [25] , [40]–[42] . In shf mutants , the basolateral accumulation of Hh protein in the wing disc is disrupted , while apical accumulation appears to be normal . The subsequent transport of the Hh ligand to the receiving cells depends upon the glypicans Dally-like ( Dlp ) and Dally , which are components of the extracellular matrix , and enzymes that are needed for glycosaminoglycan biosynthesis namely Sulfateless and Tout-velu [43]–[45] . The glycosaminoglycan is thought to promote long range signaling by Hh and other signaling molecules such as Wg by passing the ligand from one cell to its neighbor instead of presenting the ligand to the receptor [46] . It is thought to do so by directing the ligands to the lateral membranes where endocytosis is less efficient [47] . There are likely to be an extensive array of accessory factors like disp and dally that are required for the efficient release of the Hh ligand from hh expressing cells and its subsequent transport or transmission from one neighboring receiving cell to the next . We have previously shown that one such gene encodes the mevalonate biosynthetic enzyme Hmgcr [14] . We found that hmgcr is required in Hh expressing cells to facilitate the release or transmission of the Hh ligand; however , it was not clear from our studies why the biosynthesis of mevalonate would be important for the release/transmission of the Hh ligand in flies . The obvious explanation , that it is required for the synthesis of the cholesterol that is used to modify Hh , was not likely to be correct as flies do not have the downstream enzymes for cholesterol biosynthesis [15] . In the work reported here we have resolved this question . We show that the downstream target for hmgcr in the hh signaling pathway is the heterotrimeric G protein , Gγ1 , which must be geranylated in order to be active [17] , [31] , [48] . Like hmgcr and other genes that are required to promote hh signaling , mutations in gγ1 dominantly suppress the gain-of-function wing phenotypes of hhMrt in adult flies . In the embryo , the expression of wg which is activated by hh in the receiving cells is downregulated in both hmgcr and gγ1 mutants . This is also true for the en gene which is normally activated by wg signaling in hh expressing cells as part of the autoregulatory circuit that sustains hh and wg expression as the embryo develops . These transcriptional defects arise because the Hh signal is not properly conveyed to hh receiving cells . In wild type embryos Smo protein is redistributed to the membranes of the receiving cells when they receive the Hh signal transmitted from the neighboring Hh producing cells . As observed for hmgcr , Smo protein is not correctly relocalized in gγ1 mutant embryos , and instead it remains largely cytoplasmic . Finally , in the ectoderm of wild type embryos there is a gradient of Hh protein extending into the parasegment from the two cell wide stripe of hh expressing cells . Like hmgcr , this gradient is not properly formed in gγ1 mutant embryos , and instead Hh protein is inappropriately retained in the Hh producing cells . Since isoprenoid modifications , either farnesylation or geranylation , are known to be critical for the functioning of the Gγ family of proteins , these observations would argue that hmgcr is required for the release of the Hh ligand because it provides a precursor that is needed for the geranylgeranylation of Gγ1 . This conclusion is supported by the finding that qm , which synthesizes the activated substrate , GGPP , that is used to geranylate Gγ1 , is also required for the release of the Hh ligand from hh expressing cells . While these results implicate the biosynthetic pathway leading from mevalonate to the geranylation of Gγ1 in the proper release of the Hh ligand , we cannot exclude the possibility that there are important targets for geranylation in addition to Gγ1 or that other products of mevalonate might play some role in the hh signaling pathway . These possibilities remain open for a number of reasons . First , the defects in the release of Hh observed in antibody staining experiments seem to be more severe in the qm mutant ( and to a lesser extent in hmgcr: see 14 ) than in the gγ1 mutants we examined . One explanation for this difference is that the Qm enzymatic product , GGPP , is used for the geranylation of other proteins that are important for the release of the Hh ligand . However , this could also be due to , for example , differences in the perdurance of the maternal Qm and Gγ1 proteins . Second , ectopic expression of Hmgcr in hh expressing cells causes a readily discernible change in Hh protein distribution across the parasegment and relatively high levels of Hh are found even near the middle of the interstripe region . By contrast , we could not detect an equivalent alteration in Hh distribution when Gγ1 was ectopically expressed in hh producing ( or receiving ) cells . This difference could mean that the mevalonate produced by Hmgcr has uses in hh signaling besides the synthesis of GGPP and the geranylation of Gγ1 . An alternative and perhaps more interesting possibility is that the differences in the effects of misexpression on the release/transmission of Hh protein reflect the fact that Hmgcr is limiting whereas Gγ1 is not . Consistent with this idea , the distribution of hmgcr mRNAs becomes progressively restricted as development proceeds and by mid-embryogenesis ( stages 10–15 ) hmgcr mRNAs are only detected in the SGPs [9] . By contrast , mRNAs encoding Gγ1 , as well as several of the enzymes that are downstream of Hmgcr in the biosynthesis of GGPP , are much more widely expressed in the embryo at this stage [15] , [28] . A possible consequence of this difference in mRNA distribution is that the levels of Hmgcr protein would increase dramatically when it is ectopically expressed in the ectoderm during mid-embryogenesis while this would not be true for Gγ1 or , for that matter , the other GGPP biosynthetic enzymes . The idea that Hmgcr is a limiting component of signaling pathways that depend upon geranylation Gγ1 ( or other targets ) is also supported by the defects in germ cell migration that are induced by ectopic expression of these proteins . For example , expression of hmgcr in the CNS cause much more severe abnormalities in germ cell migration than those observed when fpps , qm , or gγ1 are misexpressed [15] . If these ideas were correct , than inducing or repressing the expression of the hmgcr gene would provide a novel posttranslational mechanism for regulating the potency of signaling molecules like Hh . The effects of gγ1 , qm and hmgcr on the distribution of Hh in the ectoderm indicates these genes are required for the release of the Hh ligand from hh expressing cells . For Gγ1 , a role in releasing the Hh ligand from the sending cells would dovetail nicely with a recently discovered function of this G protein and its partners , Gβ and Gα in the transport of cargo from the trans-Golgi network ( TGN ) to the basolateral plasma membrane [19]–[21] . Since Hh protein appears to be specifically targeted to the basolateral membrane in punctate structures ( LPSs ) prior to secretion [22]–[25] , [38] , [39] , it is not altogether surprising that components of the machinery needed for the transport of cargo from the TGN to the basolateral membrane would play a key a role in transmitting the Hh signal . Moreover , since Gγ1 requires geranylation for membrane association and activity , the retention of Hh in qm and hmgcr mutants would also be explained by a disruption in Gγ1-dependent TGN-plasma membrane transport . In this context it is interesting to note that while the levels of Wg are reduced in hmgcr [14] and gγ1 mutants , there is no obvious over accumulation of the Wg protein inside wg expressing cells like that observed for Hh . That the hmgcr→qm→gγ1 pathway would have no apparent effect on the release of Wg would make sense since this is thought to occur preferentially through the targeting of mRNAs to the apical surface of the cell [49] . Though the precise mechanisms for TGN-plasma membrane transport have yet to be elucidated , it is thought that the heterotrimeric G protein complexes mediate the release of cargo from the TGN by promoting membrane fission [25] . In one scenario , interaction of the cargo with an unidentified receptor in the TGN leads to the activation of the trimeric Gγ1:Gβ: Gα and the release of Gα The Gγ1:Gb heterodimer in turn activates several targets including phosphokinase C and a phosphoinostide-specific phospholipase C ( PI-PLC ) that generates diacylglycerol . PKC participates in cargo release from the TGN by activating Protein Kinase D ( PKD ) while locally high concentrations of diacylglycerol produced by PI-PLC are thought to change the properties of the TGN membranes and promote membrane fission . After membrane fission , the vesicle containing the cargo is then targeted to the basolateral plasma membrane [24] , [25] . A requirement in the formation of cargo containing vesicles would fit well with the effects of hmgcr , qm and gγ1 on the formation of the puncate Hh particles , or LPSs , that normally assemble along the basolateral membranes of Hh expressing cells . These LPSs are largely absent in hmgcr , qm and gγ1 mutant embryos and instead Hh accumulates in much larger aggregates or clumps . While the precise origin of the LPSs is not known , they are thought to be lipid containing vesicles ( or micelles ) and it would be reasonable to think that they could be generated by the budding of Hh containing vesicles from the TGN . In this case , the large aggregates or clumps of Hh protein seen in hmgcr , qm and gγ1 mutants would likely represent Hh trapped either in the TGN or in aberrant vesicles/structures that accumulate in the mutant cells when efficient cargo release from the TGN is disrupted . While the idea that Gγ1 promotes the transport of Hh from the TGN to plasma membrane would seem to fit best with the known functions of Gγ1 and its collaborating G proteins , it is also possible that Gγ1 ( plus Gβ and Gα ) functions at earlier steps in the secretion pathway , for example . in the transport of Hh from Endoplasmic Reticulum to the Golgi [50] . Alternatively , it is possible that some novel activity of Gγ1 at the plasma membrane rather than in the TGN is needed . For example , it could function to prevent the newly formed LPSs from clumping together into larger aggregates . Further studies will be required to distinguish between these and other possible mechanisms . Studies by Santos and Lehmann [15] provided convincing evidence that hmgcr is required in the soma for germ cell migration because its biosynthetic product , mevalonate , is the precursor for the synthesis GGPP by Qm . They also found that GGPP is used in turn by geranylgeranyl transferse type 1 ( β-GGT1 ) for the geranylation of some unknown target ( s ) . The experiments presented here indicate that one ( if not the only ) somatic target in the germ cell migration pathway is Gγ1 . Thus , the effects of both gain and loss of gγ1 function on germ cell migration closely resemble those reported for hmgcr , fpps , qm , and β-GGT1 . Also supporting the idea that Gγ1 must be a relevant target for the hmgcr-isoprenoid biosynthetic pathway , we find that Gγ1 proteins that cannot be geranylated behave as dominant negatives when ectopically expressed in the mesoderm and disrupt germ cell migration . In addition , there are other significant similarities between the two genes that have been studied in most detail , gγ1 and hmgcr . First , both genes show synergistic genetic interactions with components of the hh signaling pathway that perturb the process of germ cell migration . Second , germ cell migration can be disrupted when gγ1 or hmgcr are ectopically expressed in hh producing cells; however , there are no apparent effects when the genes are ectopically expressed in hh receiving cells . Taken together with the fact that the SGPs are known to be a source of Hh these findings would argue that a critical function of the biosynthetic pathway leading from hmgcr to the geranylation of Gγ1 is to upregulate Hh signaling in the SGPs , and it is the Hh ligand produced by these cells that serves to attract the migrating germ cells . Importantly , this model accounts for a number of different observations . Since Hmgcr is expressed at high levels in the SGPs , but is not expressed elsewhere in the mesoderm , it would explain how Hh signaling could be specifically potentiated in a special sub-population of cells . It would also explain why the effects of hmgcr misexpression are much greater than misexpression of the other genes in the hmgcr→gγ1 pathway that are more broadly transcribed in the embryo . Finally , it would explain why germ cells can be misdirected by ectopic expression of hh , hmgcr , the downstream genes in the geranylation biosynthetic pathway , and gγ1 in a variety of different tissues . By contrast , if the SGPs were to induce germ cell migration by expressing some unique and dedicated hmgcr→gγ1 dependent attractant , it is hard to understand how misexpression of these different upstream genes would be able orchestrate the production of this special molecule in a variety of cells and tissues that have little resemblance to the SGPs . It should be noted , however , that our results would also be compatible with more complicated models . For example , it is possible that the potentiation of Hh signaling by the hmgcr→gγ1 pathway induces the production of a specialized and as yet unknown germ cell attractant . Likewise , we also can not exclude the possibility that there is some other target for geranylation besides Gγ1 which is important for the production or activity of a second germ cell attractant and that this unknown molecule functions in concert with Hh to direct germ cell migration towards the SGPs . However , in either of these more complicated scenarios , the unknown germ cell attractant would have to be a molecule that can be induced in many different cell types in the embryo , but apparently only if these cells also express the Hh protein .
The embryo stainings were performed essentially as described in 51 . Vasa ( from Paul Lasko ) and Hh ( from Tom Kornberg ) antibodies are rabbit polyclonal antibodies . Both were used at a 1∶500 dilution . Engrailed and Wingless antibodies are mouse monoclonal antibodies and were used at 1;10 dilution . β-Galactosidase antibody was either a rabbit polyclonal purchased from Kappel ( used at 1∶1000 dilution ) or a mouse monoclonal antibody from Developmental Hybridoma Bank ( used at 1∶10 dilution ) . Smoothened antibody ( anti-rat ) was a kind gift from Steve Cohen and was used at 1∶500 dilution . For confocal analysis a magnification of 40× was used in almost all the instances and images were collected using identical settings for the control and experimental samples . Multiple pairs of wild type ( sibs ) and mutant embryos were imaged in each case and representative examples are presented . gγ1 mutant stocks , gγ1N159 and gγ1k0817 , were obtained from Fumio Matsuzaki while the various 1UAS- gγ1 stocks ( gγ1 , gγ1 ΔCAAX and gγ1 C67S ) were kindly provided by the Olson lab . The other UAS and GAL4 stocks used for the misexpression studies: UAS- hmgcr , hairy-GAL4 , elav-GAL4 , nanos-GAL4 , patched-GAL4 , UAS-β-galactosidase , hh-GAL4/TM6 Ubx-LacZ . In most experiments , males carrying two of the copies UAS transgene were mated with virgin females carrying two copies of the GAL4 transgene . The resulting progeny embryos were fixed and stained for subsequent analysis [51] .
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Previous studies have shown that HMGCoA reductase ( Hmgcr ) is required for the production of a germ cell attractant by the somatic gonadal precursor cells ( SGPs ) and for the release of the Hedgehog ( Hh ) ligand by hh expressing cells . However , it was not clear what role mevalonate , the biosynthetic product of Hmgcr , played in either of these processes or whether the hmgcr-dependent germ cell attractant corresponds to the Hh ligand ( which is known to be expressed by the SGPs ) . We show here that the downstream target for Hmgcr both in generating the germ cell attractant and in releasing the Hh ligand is the G protein , Gγ1 . Gγ1 must be geranylated in order to function , and the substrate for this posttranslational modification , geranylgeranyl-pyrophosphate , is one of the biosynthetic products of mevalonate . In addition to demonstrating a critical role for Gγ1 ( as well as the hmgcr isoprenoid biosynthetic pathway ) in releasing Hh from hh expressing cells , our findings provide additional evidence that Hh protein produced by the SGPs is an hmgcr-dependent germ cell attractant .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology/morphogenesis",
"and",
"cell",
"biology",
"cell",
"biology/cell",
"signaling",
"cell",
"biology/developmental",
"molecular",
"mechanisms",
"developmental",
"biology/cell",
"differentiation",
"developmental",
"biology/developmental",
"molecular",
"mechanisms"
] |
2009
|
Gγ1, a Downstream Target for the hmgcr-Isoprenoid Biosynthetic Pathway, Is Required for Releasing the Hedgehog Ligand and Directing Germ Cell Migration
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Many cells in a developing embryo , including neurons and their axons and growth cones , must integrate multiple guidance cues to undergo directed growth and migration . The UNC-6/netrin , SLT-1/slit , and VAB-2/Ephrin guidance cues , and their receptors , UNC-40/DCC , SAX-3/Robo , and VAB-1/Eph , are known to be major regulators of cellular growth and migration . One important area of research is identifying the molecules that interpret this guidance information downstream of the guidance receptors to reorganize the actin cytoskeleton . However , how guidance cues regulate the actin cytoskeleton is not well understood . We report here that UNC-40/DCC , SAX-3/Robo , and VAB-1/Eph differentially regulate the abundance and subcellular localization of the WAVE/SCAR actin nucleation complex and its activator , Rac1/CED-10 , in the Caenorhabditis elegans embryonic epidermis . Loss of any of these three pathways results in embryos that fail embryonic morphogenesis . Similar defects in epidermal enclosure have been observed when CED-10/Rac1 or the WAVE/SCAR actin nucleation complex are missing during embryonic development in C . elegans . Genetic and molecular experiments demonstrate that in fact , these three axonal guidance proteins differentially regulate the levels and membrane enrichment of the WAVE/SCAR complex and its activator , Rac1/CED-10 , in the epidermis . Live imaging of filamentous actin ( F-actin ) in embryos developing in the absence of individual guidance receptors shows that high levels of F-actin are not essential for polarized cell migrations , but that properly polarized distribution of F-actin is essential . These results suggest that proper membrane recruitment and activation of CED-10/Rac1 and of WAVE/SCAR by signals at the plasma membrane result in polarized F-actin that permits directed movements and suggest how multiple guidance cues can result in distinct changes in actin nucleation during morphogenesis .
Cell migration in response to signals from outside the cell drives developmental processes from embryonic morphogenesis and the establishment of the nervous system , to aberrant migrations during diseases like metastatic cancer . Understanding how cells respond to signals is particularly complicated in developing embryos where tissues , or groups of cells of related identity , must often respond to multiple migration signals while maintaining the integrity of the migrating tissue . It has been proposed that outside signals lead to cellular movements through the rearrangement of the F-actin cytoskeleton . However , the details of how this is accomplished are still being worked out . Ultimately , understanding this process will require understanding how the outside signals are able to organize the cellular cytoskeleton . In this study we addressed what specific changes in the actin cytoskeleton occurred when different migration signals were removed . In addition , we asked if changes in the levels or localization of specific F-actin regulators in response to the migration signals could explain the changes in the actin cytoskeleton and in cell migration . Studies in C . elegans have identified three pathways that guide the migrations of axons during development . C . elegans forward genetic screens led to the identification of the netrin/UNC-6 cue that signals to the UNC-40/DCC receptor to guide axonal migrations in larvae [1] , [2] . Two additional signaling pathways , ephrin and Robo signaling , guide axonal migrations in C . elegans larvae [3]–[6] . In addition , ephrin and Robo signaling contribute to the epidermal cellular migrations that result in epiboly in C . elegans embryos . The ephrin VAB-2/EFN-1 and its Eph receptor VAB-1 , the only C . elegans Eph receptor tyrosine kinase , are required in embryonic neuroblasts to permit epidermal cell enclosure [7] , [8] . SAX-3/Robo is essential during embryonic morphogenesis , with requirements within both the migrating epidermis and the underlying neuroblasts for epidermal cell migrations [9] . In contrast , the ligand for SAX-3/Robo , SLT-1 , has no embryonic phenotype on its own , suggesting that SAX-3 either has additional ligands besides SLT-1 , or does not need a ligand to mediate its embryonic effects [10] . Netrin/UNC-6 and its receptor , UNC-40 , have not been examined for epidermal cell migration defects during embryonic development , although neuronal and mesodermal cell migration defects were reported [1] . In addition , tagged UNC-6 and rescuing UNC-40/DCC transgenes are expressed in embryos [2] , [11] . Cell migrations in the embryo require dynamic rearrangements of the actin cytoskeleton . Our previous studies have identified an actin nucleation pathway , including the small GTPase CED-10/Rac1 , the WAVE/SCAR complex and the Arp2/3 complex , as essential components for embryonic morphogenesis [12] . Mutations or depletion by RNAi of the GTPase CED-10/Rac1 , any WAVE/SCAR component , or any Arp2/3 component result in complete loss of epidermal cell shape changes and cell movements . The resulting loss of epidermal cell migration leads to the Gex ( gut on the exterior ) phenotype first described for WAVE/SCAR complex components GEX-2/Sra1/p140/PIR121/CYFIP and GEX-3/NAP1/HEM2/Kette [12] , [13] . The Arp2/3 complex nucleates branched actin polymers , however it is a poor actin nucleator until it is activated by Nucleation Promoting Factors ( NPFs ) like WAVE/SCAR . The WAVE/SCAR complex is thought to be activated through membrane recruitment by the small GTPase Rac . Of the three C . elegans Rac-like GTPases , we have proposed that CED-10/Rac1 functions like the upstream Rac that recruits WAVE/SCAR during embryonic development . We based this proposal on the strong ced-10 morphogenesis phenotype that is almost as strong as loss of WAVE/SCAR components or Arp2/3 [12] , [13] . It is not known which external signals reorganize the actin cytoskeleton through Arp2/3 , nor the impact of distinct signals on the actin cytoskeleton . In addition , what happens downstream of Rac signaling is not well understood . Elegant genetic studies in C . elegans neurons have identified complex genetic regulation of actin regulators downstream of multiple Rac GTPases [14] . However , as is true in other organisms , the consequences of Rac signaling on the actin cytoskeleton have not been made clear . Genetic and molecular studies have suggested that axonal guidance pathways may reorganize F-actin through effects on Rac signaling [15] . Genetic studies suggest UNC-40/DCC signals through CED-10/Rac1 in neurons [16] while in vitro studies show that Netrin can activate Rac1 through DCC [17]–[19] . Mammalian studies suggest that the unengaged Eph receptor is permissive for Rac activation , while Ephrin activation leads to RhoA activation , Rac inactivation , and actin depolymerization [20] , [21] . In Slit-Robo signaling , activation of Robo receptors by SLIT leads to Rac activation [22] , [23] . Studies in Drosophila suggest that the Robo receptor signals through the Rac GTPase [22] , [24] . In this study we show that three guidance pathways , netrin/DCC , SLIT/Robo and ephrin , regulate embryonic morphogenesis and F-actin polarization through effects on the WAVE/SCAR complex . The receptors in all three pathways are required for the proper levels and organization of F-actin in the embryonic epidermis . All three regulate the subcellular distribution and levels of molecules that are essential for embryonic morphogenesis: CED-10/Rac1 , the WAVE/SCAR complex and F-actin . Since each of the three guidance pathways has embryonic morphogenesis defects similar to but milder than the loss of CED-10 , WAVE/SCAR or Arp2/3 , we tested our hypothesis that the three cues are redundant for a shared morphogenesis function . We found instead that each cue promoted morphogenesis through distinct effects on CED-10/Rac1 , WAVE/SCAR and on epidermal F-actin . UNC-40/DCC regulated the membrane enrichment of CED-10 , and promoted correct WVE-1 subcellular distribution required for normal levels of F-actin nucleation , but polarization of F-actin was minimally affected . Thus signals from UNC-40/DCC are important for total F-actin levels , and less important for F-actin polarization required for migrations . This essential role of netrin signaling in embryos had probably been missed due to the low penetrance of the phenotypes . SAX-3 positively regulated CED-10/Rac subcellular distribution , which led to WAVE/SCAR recruitment to membranes , and resulted in appropriate levels and polarization of F-actin in migrating cells . Finally , Eph signaling regulated CED-10 distribution , which is required for the correct WAVE complex localization in the epidermis , resulting in properly polarized F-actin in the migrating epidermal cells . This shows that ephrin receptor strongly affects events in the epidermal cells required for polarized F-actin distribution . Thus , these studies illustrate that distinct signals at the plasma membrane result in differential effects on the F-actin regulating WAVE/SCAR complex , required for both the correct levels and polarization of the actin cytoskeleton during morphogenesis . Interestingly , the degree of F-actin polarization , rather than the total levels , seems to determine whether a cell can initiate migrations or not .
In order to identify the upstream signals that reorganize the actin cytoskeleton during embryonic morphogenesis , we took a candidate gene approach by searching for signaling receptors which shared loss-of-function phenotypes with mutations in the WAVE/SCAR complex , a major regulator of embryonic F-actin organization . C . elegans receptors that transmit signals upstream of embryonic actin regulators would be expected to be expressed in embryos , and their loss of function phenotype should include embryos with the Full Gex , or gut on the exterior phenotype seen 100% of the time when WAVE/SCAR or Arp2/3 components are missing ( Figure 1A ) . They might also share the Gex post-embryonic phenotypes including the Egl or Egg laying defective phenotype [13] . The discovery that three signaling pathways , Netrin , Robo and Ephrin , were contributing to embryonic morphogenesis , but with weaker embryonic morphogenesis phenotypes than loss of WAVE/SCAR , led us to use double mutant analysis to test the hypothesis that these cues act redundantly during embryonic morphogenesis . This experiment was complicated by the fact that some double mutant combinations using null alleles are lethal [9] ( our unpublished observations ) . We therefore sometimes used combinations of one null allele and one hypomorphic allele . We predicted that if the pathways are redundant , then removing or reducing two pathways that activated WAVE/SCAR would lead to more penetrant Full Gex phenotypes . We found that all the double mutant combinations led to increased embryonic lethality , and synergistic increases in the Partial Gex lethality . However only the unc-40; sax-3 double mutant displayed a synergistic increase in the Full Gex phenotype ( Table 1 ) . The double mutants between the vab-1 null allele , dx31 ( 2% Full Gex ) and the putative null allele unc-40 ( e1430 ) ( 3% Full Gex ) or between the vab-1 hypomorph , e2 ( 0% Full Gex ) , and the sax-3 null allele , ky123 , ( 3% Full Gex ) resulted in only 6% and 2% Full Gex , respectively ( Table 1 , Figure 1C ) . These experiments did not support simple redundancy between the vab-1 pathway and either the unc-40 or sax-3 pathway for the regulation of the WAVE complex and are better explained by the pathways having parallel inputs that result in the Gex phenotype . The double between the putative null unc-40 ( e1430 ) ( 1% Full Gex at 25°C ) and the hypomorphic sax-3 ( ky200ts ) allele ( 9% Full Gex at 25°C ) at the restrictive temperature ( 25°C ) increased the Full Gex phenotype to 19% ( Table 1 , Figure 1C ) . This synergistic effect on the Full Gex phenotype suggested that there is redundancy between the unc-40 and sax-3 pathways for activating the WAVE complex . Since loss of the guidance pathway proteins altered morphogenetic movements , these proteins may be required for the organization of the actin cytoskeleton . We therefore analyzed the effects of the three guidance pathways on the plin-26::vab-10 ABD ( actin binding domain ) ::gfp ( mcIs51 ) transgene that permits live imaging of F-actin enrichment in the epidermis of embryos undergoing morphogenesis [12] , [27] . In wild-type embryos this transgene is expressed at high levels in the six rows of epidermal cells . Wild-type embryos have abundant F-actin that is dynamically enriched toward the leading edge of the ventral migrating cells . In particular , the two anterior Leading Cells ( LCs ) on each side , which are essential for guiding the ventral migration of the epidermis [28] , make large filopodial protrusions and form a broad lamellar front ( Figure 2A ) . The highest F-actin enrichment was seen , on average , 2 µm behind the protrusive front in the LCs . Loss of either arp-2 or gex-3 resulted in less actin at the leading edge and loss of filopodial protrusions and lamellar protrusions in the LCs [12] ( Figure 2A , 2C , Videos S1 and S2 ) . To compare the F-actin organization in wild-type , WAVE/SCAR depleted , and guidance pathway mutants , we made movies starting at 240 minutes after first cleavage , when epidermal morphogenesis begins in wild type , and collected images every 2 minutes until at least 380 minutes after first cleavage at 23°C ( see Materials and Methods ) . Since sax-3 and vab-1 mutants have delayed gastrulation movements that precede epidermal migration , we timed the occurrence of actin-based events . The time intervals between first large protrusions of the pocket cells , ventral actin enrichment in the Leading Cells ( LCs ) , LC protrusion initiation , and ventral meeting of the LCs were increased in unc-40 , sax-3 , and vab-1 mutants ( Figure 2B ) , and are reminiscent of the gastrulation cleft closure delays described for sax-3 and vab-1 [8] , [9] . We therefore used the first protrusion of the pocket cells , which occurs at 250 minutes in wild-type and mutant embryos , and the meeting of the LCs , which occurs at 320 minutes in wild-type embryos , but later in mutant embryos , as reference points , and measured actin accumulation relative to these events ( Figure 2B ) . Crossing the plin-26::vab-10 ABD::gfp transgene into animals carrying putative null alleles of unc-40 , unc-6 , sax-3 and vab-1 illustrated the distinct effects of each axonal guidance pathway on epidermal F-actin . Most embryos missing unc-40 or unc-6 are able to enclose and live ( Figure 1B , Table 1 ) . Loss of unc-40 or unc-6 resulted in a significant decrease of overall F-actin levels in the ventral row of migrating epidermal cells for all time points observed , but undiminished protrusive activity . In the unc-40 and unc-6 embryos shown in Figure 2A all the ventral cells express low levels of F-actin , yet the LCs are still capable of protrusive activity including filopodial protrusions ( Videos S1 and S2 , Figure 2A , Figure 3 ) . Further , the distribution of F-actin from ventral to dorsal regions of the LCs showed similar ventralward enrichment as seen in wild-type embryos ( Figure 2D , 2E ) . The continued dynamic protrusions and the ventral F-actin enrichment explain the relatively mild embryonic lethality of unc-40 and unc-6 embryos . Close to half of the embryos missing sax-3 ( 45% ) fail to enclose and die ( Figure 1B , 1D , Table 1 ) . On average , sax-3 embryos had decreased ventral F-actin levels by 330 minutes ( Figure 2A , 2C , Videos S1 and S2 ) . These embryos were delayed in initiating ventralward movements ( Figure 2B ) , especially in the LCls ( Figure 1B , Figure 2A ) , and show decreased ventralward enrichment of F-actin ( Figure 2D , 2E ) . Close to half of the embryos missing vab-1 ( 42% ) fail to enclose and die ( Figure 1 , Table 1 ) . Loss of vab-1 resulted in increased levels of epidermal F-actin in the ventral-most row of epidermal cells by 300 minutes ( Figure 2A ) , but disorganization of the F-actin distribution ( Figure 2E ) . vab-1 mutant embryos maintained high F-actin levels at the leading edge ( Figure 2C ) , but had inappropriately increased enrichment of F-actin on the dorsal side of the LCs ( Figure 2A , 2D , 2E ) . The LCs were delayed in making filopodia or lamella compared to wild type ( Figure 2A , 2B , Videos S1 and S2 ) . Thus ephrin signaling supports ventrally enriched F-actin distribution that correlates with the timely migration of the epidermal cells and with successful enclosure . The F-actin movies were captured at 2-minute intervals to minimize phototoxicity , so we could not measure rapid changes in actin dynamics . However , the movies show that in wild type , protrusions at the leading edge form and retract dynamically , on average lasting 2 . 5 minutes . These dynamic changes contribute to the ventralward migration of the cells . In contrast , in the WAVE/SCAR and axonal guidance mutants , protrusions often formed and retracted more slowly , leading to minimal changes at the leading edge . In wild type , unc-40 or unc-6 embryos , protrusions lasted , on average , 2 . 5 to 3 minutes , and the majority of embryos enclosed . In contrast in gex-3 , sax-3 and vab-1 embryos , protrusions lasted 9 , 6 and 6 minutes , respectively , and 100% , 45% and 42% of the embryos failed to enclose ( Figure 3 ) . To explore how the three guidance pathways might signal to WAVE/SCAR during post-embryonic neuronal cell migrations , we took advantage of gain-of-function alleles in each guidance receptor . These alleles have been used to ask if other genes are genetically downstream of these guidance signals in neurons . CED-10/Rac1 has been placed genetically downstream of UNC-40 and of SLT-1/SAX-3 due to the ability of loss-of-function mutations in ced-10/Rac1 to partially suppress gain-of-function mutations in SLT-1 and UNC-40 that alter the post-embryonic migrations of axons labeled with mec-4::gfp ( zdIs5 ) [16] , [39] . Further , similar gain-of-function studies of VAB-1/Eph using myristoylated VAB-1 have been used to identify genes , including NCK-1 and Wasp , that function downstream of VAB-1 [40] . We used these same strains to ask if WAVE/SCAR behaves like a component of the netrin , Robo or ephrin pathway during post-embryonic neuronal migrations .
While the ephrin and slit/robo pathways had long been examined for embryonic morphogenesis effects , there was little notice of netrin embryonic roles . The one exception is the 1990 netrin pathway paper by Hedgecock and colleagues that reported embryonic neuronal and mesodermal cell migration defects [1] . We observed that all four unc-40 putative null alleles and the unc-6 deletion null showed low penetrance embryonic lethality , and a small but significant number of embryos with the Full Gex phenotype ( no enclosure ) . This was true after we out-crossed four putative null unc-40 mutants and the unc-6 deletion null strain twice . Therefore it is highly unlikely that secondary mutations or strain background can explain the unc-40 and unc-6 embryonic phenotypes . The distribution of F-actin in the migrating epidermal cells is highly dynamic and enriched toward the leading edge . We previously showed that loss of the WAVE complex leads to fewer , smaller protrusions at the leading edge of the migrating epidermal cells [15] . The movies made for this study show waves of F-actin enrichment that are dynamically oriented toward the leading edge ( Video S1 and S2 ) . In vivo imaging of F-actin distribution in embryos missing either the netrin , Robo or ephrin receptors demonstrated quantifiable changes in epidermal F-actin levels and enrichment . When the epidermal cells initiate their migrations , robust filopodial and lamellar protrusions extend from the two Leading Cells at the anterior epidermis . Loss of sax-3 or vab-1 caused a significant delay in Leading Cell protrusions that correlated with a drop in ventralward enrichment of F-actin ( Figure 2A , 2E ) . These changes in F-actin distribution help explain the high percent of embryonic lethality seen in sax-3 and vab-1 embryos . In contrast , loss of unc-40 permitted ventral protrusions in all embryos examined , and ventralward enrichment of F-actin , despite a drop in overall F-actin levels . This helps explain the much milder embryonic lethality seen in unc-40 and unc-6 mutant embryos and suggests F-actin polarization or enrichment is more important for cell migration than total F-actin levels . Removal of any of the guidance cues analyzed here altered the rate of protrusion turnover ( Figure 3 , Video S3 ) . Some actin regulators , like cofilin , are involved in the turnover of protrusions by helping to disassemble polymerized actin , and thus contribute to the recycling of actin components that promotes cell movements [42] , [43] . Other actin regulators , like myosin II and Rho , help turn over protrusions by helping to remodel adhesive structures [44] . Turnover of protrusions is thus an essential component of cell migrations . We propose that axonal guidance cues may contribute to all of these kinds of actin changes that promote cell migrations including protrusion formation and turnover . More thorough understanding of how changes at the membrane result in dramatic changes in the F-actin levels and enrichment shown here will require additional studies . However , our identification of CED-10 and WVE-1 as essential read-outs of the signals is an important first step in understanding this complicated process . Loss of unc-40 , sax-3 and vab-1 altered the distribution and levels of CED-10::GFP and GFP::WVE-1 at subcellular regions . To understand how three distinct pathways could contribute to the correct regulation of cell movements that depend on actin regulators , we tested the model that all the pathways act redundantly . Genetic and molecular studies show that a simple redundancy model does not explain the integration of three signals to regulate the WAVE/SCAR actin nucleation complex . Instead , our results suggest the following Model for the roles of the three signaling pathways ( Figure 7 ) . We propose that UNC-40 activity supports the transport of inactive CED-10/Rac1 ( Rac-GDP , grey circles in Figure 7 ) to endosomes where it is activated ( Rac-GTP , red circles , Figure 7 ) . Activated CED-10/Rac1 is then targeted to the plasma membrane where it is recruited by SAX-3/Robo . Activated CED-10/Rac1 can then recruit and help assemble the WAVE/SCAR complex , which leads to robust branched actin polymerization through the Arp2/3 complex . VAB-1/Ephrin inhibits the targeting of activated CED-10/Rac to the membrane thereby modulating branched actin polymerization . VAB-2 and VAB-1 , Ephrin and Ephrin receptor , were thought to act in the underlying neuroblasts for epidermal morphogenesis to occur [6]–[8] . However recent studies of the vab-1 promoter fused to GFP suggest that some epidermal cells express VAB-1 [48] . More fine-tuned analysis of actin dynamics in the epidermal and neuronal cells in animals depleted of ephrin and ephrin receptor could address the tissue requirements of ephrins during this process . WAVE/SCAR components have been shown to affect axonal guidance and ectopic branching in the PDE neuron [14] . Loss of WAVE/SCAR components affected the ventral migration of the AVM axon ( Figure 6A ) , suggesting WAVE/SCAR proteins contribute to some of the same axonal guidance events that are regulated by netrins , slt-1/Robo and ephrins . One caveat is that we depleted the WAVE/SCAR components by RNAi in all tissues , so these effects on neurons could also be due to the functions of WAVE/SCAR in other tissues . Tissue-specific depletion of WAVE/SCAR components would clarify this issue . We tested if the role of WAVE/SCAR downstream of axonal guidance receptors extends to neurons by using gain-of-function strains that alter the AVM axonal migration ( Figure 6 ) . The ability of WAVE/SCAR and Arp2/3 depletion to suppress the slt-1/sax-3 gain-of-function defects may support our Model that SLT-1/Robo can signal through Rac , and that Rac activates WAVE/SCAR . The inability of WAVE/SCAR to suppress the Myr-VAB-1 gain-of-function defects suggests that Ephrin in C . elegans has targets other than WAVE/SCAR . For example , it has been suggested that VAB-1 signals through Wasp and NCK-1 [40] . The inability of WAVE/SCAR depletion to suppress Myr-UNC-40 phenotypes was a surprise , given the expectation that UNC-40 activates Rac , which can activate WAVE/SCAR . There are several ways to interpret this result . Myr-UNC-40::GFP may alter other cytoskeletal components other than the WAVE/SCAR complex to interfere with the correct AVM axon migration . Another possibility is that Myr-UNC-40 , which is retained at the membrane , may not be simply more active . If the failure of Myr-UNC-40 to turn over , or to interact with other UNC-40 Receptors blocks a positive cue , then Myr-UNC-40 may be causing a loss-of-function phenotype . In relation to our proposed model , if UNC-40 activation of CED-10/Rac1 supports SAX-3 recruitment of active CED-10/Rac1 , then UNC-40 loss would enhance defects caused by loss of WVE components , just like it enhances loss of SAX-3 . An alternative interpretation is that in the absence of WAVE/SCAR in all tissues ( as we did here ) other axonal molecules , like SLT-1 , are not properly localized . This could lead to enhancement of the Myr::UNC-40 defects . Future experiments with reagents that can show how loss of one signal affects the other signals will be helpful in further determining how these multiple signals converge to regulate CED-10/Rac1 enrichment at membranes , WAVE/SCAR recruitment and activation , and properly polarized and dynamic F-actin .
The following strains were used in this analysis: unc-40 ( n324 ) , unc-40 ( e1430 ) , unc-40 ( n473 ) , unc-40 ( e271 ) , unc-6 ( ev400 ) , sax-3 ( ky123 ) , sax-3 ( ky200 ) , vab-1 ( dx31 ) , vab-1 ( e2 ) , FT48 xnIs16 [dlg-1::gfp]; him-8 , OX469 unc-40 ( n324 ) ; xnIs16 [dlg-1::gfp] , OX248 unc-40 ( e1430 ) ; xnIs16 [dlg-1::gfp] ) , OX243 unc-6 ( ev400 ) ; xnIs16 [dlg-1::gfp] , OX242 sax-3 ( ky123 ) ; xnIs16 [dlg-1::gfp] , OX485 vab-1 ( dx31 ) ; xnIs16 [dlg-1::gfp] , OX471 pjIs1[gfp::wve-1; rol-6] , OX490 unc-40 ( n324 ) ; pjIs1 [gfp::wve-1; rol-6] , OX491 sax-3 ( ky123 ) ; pjIs1 [gfp::wve-1; rol-6] , OX484 vab-1 ( dx31 ) ; pjIs1 [gfp::wve-1; rol-6] , OX466 pjIs4 [ced-10::gfp::ced-10; unc-76 ( + ) ] , OX482 unc-40 ( n324 ) ; pjIs4 [ced-10::gfp::ced-10] , OX480 sax-3 ( ky123 ) ; pjIs4 [ced-10::gfp::ced-10] , OX483 vab-1 ( dx31 ) ; pjIs4 [ced-10::gfp::ced-10] , ML1154 mcIs51 [plin26::vab-10ABD::gfp; pmyo-2::gfp] , OX353 gex-3 ( zu196 ) /Dnt1;mcIs51 [plin26::vab-10ABD::gfp; pmyo-2::gfp] , OX487 unc-40 ( n324 ) ; mcIs51 [plin26::vab-10ABD::gfp; pmyo-2::gfp] , OX521 unc-6 ( ev400 ) ; mcIs51 [plin26::vab-10ABD::gfp; pmyo-2::gfp] , OX488 sax-3 ( ky123 ) ; mcIs51 [plin26::vab-10ABD::gfp; pmyo-2::gfp] , OX489 vab-1 ( dx31 ) ; mcIs51 [plin26::vab-10ABD::gfp; pmyo-2::gfp] , OX441 unc-40 ( n324 ) /hT2; vab-1 ( dx31 ) , OX134 unc-40 ( e1430 ) ; sax-3 ( ky200 ) , IC361 vab-1 ( e2 ) /mIn1; sax-3 ( ky123 ) , SK4005 zdIs5 [mec-4::gfp] , LE2661 lqIs18 [mec-7::myr unc-40::gfp] , CX5078 dpy-20 ( e1282 ) IV;zdIs5; kyIs218 [myo-3::slt-1/40 integrated+str-1::gfp+dpy-20 ( + ) ] , IC400 zdls5 I;quls5 [myr-vab-1] II;him-5 ( e1490 ) V . Lysates were prepared as described for embryonic lysates above but mixed staged animals were used and Triton was excluded from the Lysis buffer . All lysates were processed immediately . The lysates were spun at increasing speeds and times using a Beckman Coulter Optima TLX Ultracentrifuge , rotor # TLA-120 . 2 . The supernatant was removed after each spin and spun at the next speed . The spin speeds and times were: spin 1 , 1 K rpm for 10 minutes; spin 2 , 10 K rpm for 10 minutes; spin 3 , 30 K for 20 minutes; spin 4 , 100 K for 90 minutes . At each step the pellet was resuspended in a volume equal to the supernatant it was derived from . 5× Laemmli Buffer was then added to each fraction , the fractions were boiled at 95°C for 5 minutes before loading on gels for Western blotting . Equal volumes of each supernatant and pellet pair were loaded per lane . For all feeding RNAi , cDNAs of the genes were inserted into L4440 vector and transformed into HT115 cells . Saturated overnight cultures were diluted 1∶250 and incubated for 6–7 h at 37°C with agitation until the OD600 was close to 1 . Bacteria were pelleted by centrifugation and resuspended in LB Amp , 100 µg/ml . 1 mM IPTG was added to the bacteria and Amp plates before use . C . elegans animals were synchronized by hypochlorite treatment followed by hatching in M9 Buffer . For lysates L1 worms were fed either control HT115 E . Coli , or HT115 containing the L4440 plasmid carrying the gene of interest and were grown at 20°C for 3 days . Lysates were made from the mixed population of adults and eggs . For embryonic analysis embryos were collected on the third day and imaged . For adult analysis , animals were assayed for neuronal phenotypes after two days on the RNAi food . All experiments were performed at 20°C unless otherwise noted . For immunohistochemistry , embryos were fixed to poly-lysine slides and freeze-cracked by incubating on dry ice for 15 minutes . Slides were then fixed in methanol for 20 minutes at −20°C , blocked in 2% PBST for 5 minutes , washed 3 times with PBS and incubated with primary antibodies for 1 hour at 37°C . Slides were then washed 3 times with PBS and incubated with secondary fluorophore conjugated antibodies for 1 hour at 37°C . Slides were mounted in PGND solution as described . All images ( except live imaging of plin-26::vab-10 ABD::gfp , Figure 2 , Figure 3 ) were acquired on a Zeiss Axioskop 2 Plus microscope using a 40× oil objective with iVision 4 . 0 software driving a Roper SensiCam QE camera . The images were then analyzed using ImageJ software . Two to four cell stage embryos ( 0–20 minutes after first cleavage ) were dissected from adult hermaphrodites and mounted on 3% agarose pads in water . The embryos were incubated at 23°C for 240 minutes , then imaged every 2 minutes for at least 120 minutes . The interval was chosen to reduce photo bleaching of the signal and to avoid damage to the embryo due to the exposure to UV light . Live plin-26::vab-10 ABD::gfp embryos were imaged using a 40×1 . 3 NA oil immersion lens on a Nikon TE2000 inverted microscope fitted with a Yokogawa CSU21 spinning-disk confocal scanhead ( Perkin Elmer ) , a Melles-Griot argon laser ( 514 nm excitation ) controlled by a Neos programmable AOTF . Multidimensional datasets were acquired using the software MetaMorph on a Hamamatsu Orca-AG cooled CCD camera , and stereo QuickTimeVR movies were assembled from the raw data using a custom-written plug-in for the Java program ImageJ ( http://rsb . info . nih . gov/ij/ ) . Background noise from the camera was reduced to the lowest grey levels of the image bit depth , via a linear contrast stretch . Images taken at the time points of interest were analyzed using ImageJ software or the ImageJ-based GLOWormJ viewing and analysis program: http://www . glowormnotes . org . Embryos expressing plin26::vab10ActinBindingDomain::gfp were filmed at 2-minute intervals . Stacks were projected into 4D QuickTime movies that allowed viewing of the embryos from multiple angles . All quantitation was done on the raw images . The figure legends indicate when images were enhanced for contrast , and the same enhancement was applied to a mosaic of the related images for that figure . All graphs show the mean of the data and the Standard Error of the Mean ( SEM ) . For grouped data , statistical significance was established by performing a two-way Analysis of Variance ( ANOVA ) followed by the Bonferroni multiple comparison post-test . For ungrouped data a one-way ANOVA was performed followed by the Tukey post-test . Asterisks ( * ) denote p values<0 . 05 . All statistical analysis was performed using GraphPad Prism .
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Neurons and other cells are most dynamic during embryonic development . Later in life , a diminished developmental potential in mature neurons makes injuries difficult to treat . Neuronal regeneration studies have benefited from genetic studies that identified the molecules that work during embryonic development to give neurons their plasticity and dynamism . Growth and regeneration require dynamic changes in the actin cytoskeleton . In this study we ask how signals that are known to guide migrations of neurons and other cells during development and regeneration are able to reorganize the actin cytoskeleton . Understanding how multiple signals are integrated to control actin dynamics is essential for understanding how cellular movements are regulated in embryos and adults . We find that the actin-nucleation regulating WAVE/SCAR complex molecules , which are conserved from the C . elegans soil nematodes to human beings , are localized and regulated by axonal guidance signals during embryonic development . These studies illustrate a mechanism by which different signals reorganize cellular F-actin through their regulation of the actin regulating WAVE/SCAR complex .
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"cytoskeleton",
"biology",
"molecular",
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"signal",
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] |
2012
|
UNC-40/DCC, SAX-3/Robo, and VAB-1/Eph Polarize F-Actin during Embryonic Morphogenesis by Regulating the WAVE/SCAR Actin Nucleation Complex
|
In order to understand the role of dengue virus ( DENV ) specific T cell responses that associate with protection , we studied their frequency and phenotype in relation to clinical disease severity and resolution of viraemia in a large cohort of patients with varying severity of acute dengue infection . Using ex vivo IFNγ ELISpot assays we determined the frequency of dengue viral peptide ( DENV ) -NS3 , NS1 and NS5 responsive T cells in 74 adult patients with acute dengue infection and examined the association of responsive T cell frequency with the extent of viraemia and clinical disease severity . We found that total DENV-specific and DENV-NS3-specific T cell responses , were higher in patients with dengue fever ( DF ) , when compared to those with dengue haemorrhagic fever ( DHF ) . In addition , those with DF had significantly higher ( p = 0 . 02 ) DENV-specific T cell responses on day 4 of infection compared to those who subsequently developed DHF . DENV peptide specific T cell responses inversely correlated with the degree of viraemia , which was most significant for DENV-NS3 specific T cell responses ( Spearman’s r = -0 . 47 , p = 0 . 0003 ) . The frequency of T cell responses to NS1 , NS5 and pooled DENV peptides , correlated with the degree of thrombocytopenia but had no association with levels of liver transaminases . In contrast , total DENV-IgG inversely correlated with the degree of thrombocytopenia and levels of liver transaminases . Early appearance of DENV-specific T cell IFNγ responses before the onset of plasma leakage , appears to associate with milder clinical disease and resolution of viraemia , suggesting a protective role in acute dengue infection .
Dengue virus is the cause of the most common mosquito-borne viral infection worldwide , indeed over half of the global population live in areas where there is intense dengue transmission putting them at risk of dengue infection [1] . Dengue virus causes 390 million infections annually , of which nearly a quarter are clinically apparent causing a spectrum of disease phenotypes ranging from mild dengue fever ( DF ) to dengue hemorrhagic fever ( DHF ) . DHF is defined by a transient increase in vascular permeability resulting in plasma leakage , with high fever , bleeding , thrombocytopenia and haemoconcentration , which can lead to shock ( dengue shock syndrome ( DSS ) ) [2] . It is however not fully understood why some people develop more severe forms of the disease , with patient history , immunity , age , viral serotype , sub-strain and epidemiological factors all postulated to play a role [3] . It was highlighted during a recent summit to identify correlates of protection for dengue , that dengue virus ( DENV ) specific T cell immunity should be studied in more detail , in order to develop safe and effective dengue vaccines [4] . Although a dengue vaccine ( Denvaxia ) is now licensed in several countries , the efficacy is low in dengue seronegative individuals and provides only partial protection against DENV2 [5] . Although it is now generally believed that DENV specific T cells are protective , it is important that dengue vaccines should not induce “harmful” T cell immunity [4 , 6–8] . Indeed , a significant hurdle in developing an efficacious dengue vaccine has been our limited understanding of the protective immune response in acute dengue infection and the added complexity of the presence of four DENV serotypes that are highly homologous . Although the evidence for T cells playing a possible protective role in DENV infections is emerging , there is still conflicting evidence as to the role of antigen-specific T cells during dengue infection is reported in the literature . T cell responses to DENV are predominantly directed towards the nonstructural proteins ( NS ) , with the majority of the CD8+ T cell responses directed towards NS3 followed by NS5 and CD4+ T cell responses to envelope , PrM and NS1 proteins [9–11] . It was believed that highly cross-reactive T cells specific to DENV-NS3 , and other proteins , associate with severe clinical disease ( DHF ) , and it was thought that these cells contribute to DHF by inducing a ‘cytokine storm’[12–15] . It is hypothesized in the ‘original antigenic sin’ theory that T cell responses against the initial DENV serotype of primary infection persist and dominate during subsequent infections; and that these T cells are suboptimal in inducing robust antiviral responses upon re-challenge [13 , 14 , 16] . However , it has been shown that DENV-NS3 specific T cell responses were at very low frequency during acute disease , and only detected in the convalescent phase pointing away from a role in vascular leak [14 , 16 , 17] . Recently it was observed that DENV-specific T cells are found in large numbers in the skin during acute dengue infection , and it is speculated that highly cross-reactive , pathogenic skin T cells could be contributing to DHF , despite being absent or present at low frequencies in the peripheral blood [8 , 18] . As the frequency of skin resident DENV-specific T cells was investigated in a small patient cohort , it is not yet clear whether the frequency of the skin T cells associated with clinical disease severity . Conversely some studies in both humans and mouse models have shown that DENV-specific T cells in the blood are likely to be protective [19–23] . It was shown that in individuals who were naturally infected with DENV , polyfunctional CD8+ T cells responses of higher magnitude and breadth were seen for HLA alleles associated with protection [21] . Similar findings were seen with DENV-specific CD4+ T cell responses [23] . Our previous studies have also shown that the magnitude of IFNγ-producing DENV NS3-specific memory T cell responses was similar in those who had varying severity of recovered past dengue infection , suggesting that the magnitude of the memory T cell response does not correlate with clinical disease severity[22] . While many studies have been carried out to elucidate the functionality of T cell responses in dengue , these have been limited to studying T cells specific for particular HLA types by using tetramers/pentamers [16 , 18] , or to investigating T cell responses in individuals with unknown severity of dengue . To aid the generation of an effective vaccine it will be important to understand the role , phenotype and frequency of dengue-specific T cell responses in relation to clinical disease severity and clearance of viraemia [6 , 7] . Therefore , here we investigate T cell responses to immunodominant DENV NS proteins in patients with DHF and DF , and analyse the association of such responses with resolution of viraemia .
The study was approved by the Ethical Review Committee of The University of Sri Jayewardenepura . All patients were adults and recruited post written consent . We recruited 74 adult patients with acute dengue infection from the National Infectious Diseases Institute , between day 4–8 of illness , following informed written consent . The patients were followed up throughout their hospital stay and all clinical features were recorded several times each day , from time of admission to discharge . Ultra sound scans were performed to determine the presence of fluid leakage in pleural and peritoneal cavities . Full blood counts , and liver transaminase measurements were performed serially through the illness . Clinical disease severity was classified according to the 2011 WHO dengue diagnostic criteria [24] . Accordingly , patients with ultrasound scan evidence of plasma leakage ( those who had pleural effusions or ascites ) were classified as having DHF . Those who did not develop any clinical or laboratory features of plasma leakage throughout their hospital stay , were diagnosed as having DF . Shock was defined as having cold clammy skin , along with a narrowing of pulse pressure of ≤ 20 mmHg . Based on this classification , 45 patients had DHF and 29 patients had dengue fever ( DF ) of the 74 patients recruited for the study . Acute dengue infection was confirmed in serum samples using a PCR ( see below ) and dengue antibody detection . Dengue antibody assays were completed using a commercial capture-IgM and IgG ELISA ( Panbio , Brisbane , Australia ) [25 , 26] . Based on the WHO criteria , those who had an IgM: IgG ratio of >1 . 2 were considered to have a primary dengue infection , while patients with IgM: IgG ratios <1 . 2 were categorized under secondary dengue infection [27] . The DENV-specific IgM and IgG ELISA was also used to semi-quantitatively determine the DENV-specific IgM and IgG titres , which were expressed in PanBio units . DENV were serotyped and viral titres quantified as previously described [28] . RNA was extracted from the serum samples using QIAamp Viral RNA Mini Kit ( Qiagen , USA ) according to the manufacturer’s protocol . Multiplex quantitative real-time PCR was performed as previously described using the CDC real time PCR assay for detection of the dengue virus [29] , and modified to quantify the DENV . Oligonucleotide primers and a dual labeled probe for DENV 1 , 2 , 3 , 4 serotypes were used ( Life technologies , India ) based on published sequences [29] . In order to quantify viruses , standard curves of DENV serotypes were generated as previously described in Fernando , S . et . al [28] . The peptide arrays spanning DENV NS1 ( DENV-1 Singapore/S275/1990 , NS1 protein NR-2751 ) , NS3 ( DENV-3 , Philippines/H87/1956 , NS3 protein , NR-2754 ) and NS5 proteins ( DENV-2 , New Guinea C ( NGC ) , NS5 protein , NR-2746 ) were obtained from the NIH Biodefense and Emerging Infections Research Resource Repository , NIAID , NIH . The DENV NS3 peptide array consisted of 105 , 14–17 mers peptides , NS1 and NS5 proteins were comprised of 60 and 156 peptides respectively . The peptides were reconstituted as previously described [30] . NS1 , NS3 and NS5 peptides were pooled separately to represent the DENV- NS1 , NS3 and NS5 proteins . In addition , total NS1 , NS3 and NS5 peptides were combined to represent a ‘DENV-all’ pool of peptides . Ex vivo IFNγ ELISpot assays were carried out as previously discussed using freshly isolated peripheral blood mononuclear cells ( PBMC ) obtained from 74 patients [22] . Fresh PBMCs were used due to concerns of possible reduction/alterations in IFNγ production by cryopreserved PBMCs [31] . DENV-NS3 , NS1 , NS5 and the combined DENV-ALL peptides were added at a final concentration of 10 μM and incubated overnight as previously described [16 , 32] . All peptides were tested in duplicate . PHA was included as a positive control of cytokine stimulation and media alone was applied to the PBMCs as a negative control . The spots were enumerated using an automated ELISpot reader ( AID Germany ) . Background ( PBMCs plus media alone ) was subtracted and data expressed as number of spot-forming units ( SFU ) per 106 PBMCs . Quantitative ELISA for TNFα ( Biolegend USA ) and IL-2 ( Mabtech , Sweden ) were performed on ELISpot culture supernatants according to the manufacturer’s instructions . PRISM version 6 was used for statistical analysis . As the data were not normally distributed , differences in means were compared using the Mann-Whitney U test ( two tailed ) . Spearman rank order correlation coefficient was used to evaluate the correlation between variables including the association between DENV-specific T cell responses and platelet counts , degree of viraemia and liver transaminases .
To investigate the role of T cells in the progression of dengue infection we stratified patients based on disease severity . The clinical and laboratory features of the 74 patients recruited to the study are shown in Table 1 . There was no statistically significant difference in the age of the individuals who had DF ( median 29 , IQR 29 to 42 years ) , when compared to those who had DHF ( median 33 , IQR 33 to 39 years ) . Of those who had DF , 18 ( 62 . 1% ) were males and in those who had DHF 31 ( 68 . 9% ) were males . Of these 74 patients , 45 had DHF and 29 had DF , and all 45 patients with DHF had ascites with 10 of them also experiencing pleural effusions . None of the patients developed shock and only one person progressed to bleeding manifestations ( Table 1 ) . The median duration of illness when recruited to the study was similar for patients with DF ( median 5 , IQR 5 to 6 days ) and DHF ( median 5 , IQR 4 to 6 days ) . To evaluate the role of T cell derived cytokine in the immunopathology or regulation of acute dengue infection , we stimulated PBMCs isolated from patients with either DF or DHF with peptides constituting DENV-derived non-structural protein ( NS ) and assessed cytokine production by ELISPOT . We stimulated the patient PBMCs with different pools of overlapping peptides making up either full length NS1 , NS3 or NS5 protein , or a pool of total NS1 , 3 and 5 peptides ( DENV-all ) . NS3 and NS5 were selected for investigation as CD8+ T cell responses have been shown to be directed to these proteins and CD4+ T cells have been shown to target structural proteins and NS1 as the main non-structural protein[11 , 21] . This combination of NS proteins from the particular DENV strains has previously been used to study DENV specific T cell responses [33] . We used this ex vivo ELISPOT method to model antigen presentation of dengue-derived peptides to antigen-specific T cells in vitro and assessed T cell activation by IFNγ production , as a representative cytokine produced by T cells during dengue infection . T cell responses to the pooled DENV peptides ( DENV-ALL ) ( p = 0 . 02 ) were higher in PBMCs derived from patients with DF than DHF patients and the NS3-specific responses showed a trend to be higher in those with DF than DHF ( Fig 1A ) . T cell responses to DENV-NS1 peptides were similar in patients with DF and DHF . 26/45 patients with DHF and 12/29 patients with DF , had zero responses to NS5 . We did not detect TNFα in the ex vivo ELISpot culture supernatants , which is in contrast to studies performed by others on T cell clones that implied TNFα producing DENV-specific T cells contribute to disease pathogenesis [15] . We also did not detect significant quantities of IL-2 . The T cell responses to the overlapping peptides were not different in males compared to females , and none of the peptide-specific responses correlated with the age of the individuals . To assess if detection of DENV specific T cell responses before the onset of the critical phase ( vascular leakage phase ) , was associated with a reduced likelihood of developing leakage , we isolated the data from DF and DHF patients recruited on day 4 post the onset of illness and analysed IFNγ production by peptide stimulated PBMCs . None of the patients had evidence of vascular leakage on day 4 of illness and those who developed leakage ( patients with DHF ) , did so on day 5 or 6 . DF patients ( those who did not develop any plasma leakage throughout their illness ) had a significantly higher IFNγ secretion response ( p = 0 . 02 ) to the DENV-all peptide pool ( median 42 . 5 , IQR = 22 . 5 to 945 SFU/106 PBMCs ) , when compared to DHF patients ( median 0 , IQR = 0 to 12 . 5 SFU/106 PBMCs ) ( Fig 1B ) . As such , significantly higher DENV-specific T cell responses were seen in those who did not develop fluid leakage , and those who had lower DENV-specific T cell responses proceeded to develop fluid leakage ( DHF ) . Responses to DENV-NS3 , NS1 and NS5 also appeared higher in patients with DF at this time point , although this did not reach statistical significance ( Fig 1B ) . To further assess the time-course of the response we obtained a second blood sample from eight patients within our cohort two days after collection of the first sample . T cell responses to DENV-ALL and DENV-NS3 peptides increased from the first sample ( day 4 ) to the second ( day 6 ) , but it was not statistically significant ( p>0 . 05 ) ( S1 Fig ) Thrombocytopenia is associated with clinical disease severity and higher degrees of thrombocytopenia are seen in those with DHF compared to those with DF[24] . We found that DENV peptide specific T cell responses correlated with the degree of thrombocytopenia . While this correlation with T cell responses and platelet counts was significant for DENV-NS1 ( Spearmans r = 0 . 26 , p = 0 . 01 ) ( Fig 2A ) , NS5 ( Spearmans r = 0 . 4 , p = 0 . 0002 ) ( Fig 2B ) and DENV-All ( Spearmans r = 0 . 31 , p = 0 . 005 ) ( Fig 2C ) , it was not significant for NS3 ( Spearmans r = 0 . 18 , p = 0 . 09 ) ( Fig 2D ) . No association was seen with DENV-peptide specific T cell responses and aspartate transaminase ( AST ) and alanine transaminase ( ALT ) ( S2 Fig ) , which are indicators of liver dysfunction [28 , 34] . While some studies report that certain DENV serotypes associate with DHF [35 , 36] , others have shown that the risk of DHF is similar regardless of serotype [37] . Therefore , we proceeded to determine whether there were differences in the T cell responses to DENV-proteins based on the viral serotype that the patients were infected with . Within our cohort 30 ( 40 . 5% ) patients were infected with DENV1 , 19 ( 25 . 7% ) with DENV2 , 4 ( 5 . 4% ) with DENV-3 and 2 ( 2 . 7% ) with DENV-4 ( Table 1 ) . The serotype could not be determined in 19 ( 25 . 7% ) patients , as they were not viraemic at the time of recruitment . DHF developed in 14/30 ( 46 . 7% ) of the patients infected with DENV-1 and 15/19 ( 78 . 9% ) of those infected with the DENV-2 and in 11/19 ( 57 . 9% ) who were aviraemic at the time of recruitment ( Fig 3A ) . Thus , it appeared that DENV-2 infection was more likely to lead to development of DHF ( odds ratio 3 . 3 , 95% CI 0 . 93 to 12 . 1 ) , however the association was not statistically significant ( p = 0 . 08 ) in this cohort . Aviraemic individuals displayed significantly higher IFNγ T cell responses to NS1 ( p = 0 . 002 ) , NS3 ( p = 0 . 02 ) , NS5 ( p = 0 . 02 ) and DENV-ALL pooled peptides ( p = 0 . 0004 ) when compared to those who were viraemic at the time of recruitment . In addition , those who were infected with the DENV-2 serotype , with a trend towards increased DHF susceptibility , had significantly lower responses to NS1 ( p = 0 . 002 ) , NS3 ( p = 0 . 04 ) , NS5 ( p = 0 . 003 ) and DENV-All ( p = 0 . 0003 ) peptides when compared to those who were infected with DENV-1 . As the PBMCs of patients infected with different DENV serotypes , were stimulated with the non-structural proteins from different virus serotypes ( NS1-DENV1 , NS3-DEN3 and NS5-DEN2 ) , we sought to assess the sequence identity of these proteins between serotypes . Multiple alignment of the NS5 protein sequences of DENV2 ( 58 sequences ) and DENV3 ( 28 sequences ) was performed using virus variation resource [38] and analysed using Clustal omega and showed a sequence identity of > 72 . 1% between the NS5 proteins of these viral serotypes [39] . Multiple alignment of the NS3 protein of DENV2 ( 61 sequences ) and DENV3 ( 28 sequences ) showed a sequence identity of > 72 . 02% . Multiple alignment of the NS1 protein of DENV2 ( 62 sequences ) and DENV3 ( 28 sequences ) showed a sequence identity of >65 . 11% . The homology between DENV1 and DEN2 NS5 was >71 . 83% ( comparison of 102 DENV1 sequences and 58 DENV2 sequences ) [38] , while the homology between DENV1 and DENV3 NS3 was >76 . 9% ( comparison of 102 DENV1 sequences and 28 DENV3 sequences ) [38] . Therefore , the T cell responses to different DENV serotypes is unlikely to be profoundly influenced by using non-structural protein sequences of different DENV serotypes . However , since there was some concern that stimulating using different serotypes would influence the results , we carried out further analysis . Since the most immunodominant protein was NS3 , which was from DENV3 , we also compared NS3 specific T cell responses in patients with DENV1 ( n = 30 ) and DENV2 ( n = 19 ) . Although we did not find any significant difference in the T cell responses to NS3 based on infecting DENV serotype ( p = 0 . 06 ) , the responses to DENV3 NS3 , appeared higher in patients with an acute DENV1 infection ( median 85 , IQR 5 to 435 SFU/million PBMBs ) compared to those with an acute DENV2 infection ( median 10 , IQR 0 to 66 . 25 SFU/million PBMBs ) ( S3A Fig ) . We then went on to compare responses to NS5 peptides , which were derived from DENV2 , in patients with an acute DENV1 and DENV2 infection . Again , those with an acute DENV2 infection had significantly lower responses to the NS5 ( p<0 . 0001 ) compared to patients with DENV1 ( S3B Fig ) . We believe this difference is due to 15/19 ( 78 . 9% ) patients with DENV2 having DHF ( and thus poor T cell responses ) , whereas only 14/30 ( 46 . 7% ) of those with DENV1 had DHF . We carried out a similar comparison within the group of patients with acute DENV1 for NS1 ( which was from a DENV1 strain ) and again did not see any difference within the DENV1 group in those with DF and DHF ( S3C Fig ) , which was compatible with responses of the overall results . DHF patients have been shown to have higher viral loads , exhibit prolonged viraemia [40 , 41] and persistent DENV-NS1 antigenaemia [42 , 43] . As such we attempted to elucidate a correlation between T cell cytokine responses and viremia . DENV specific T cell responses to NS1 , NS3 and NS5 peptides in addition to the pooled peptides ( DENV-ALL ) inversely correlated with the degree of viraemia , which was most significant for DENV-NS3 specific T cell responses ( Spearman’s r = -0 . 47 , p = 0 . 0003 ) ( Fig 3B and S4 Fig ) . The viral loads significantly inversely correlated with the platelet counts ( Spearmans r = -0 . 34 , p = 0 . 01 ) , with the platelet counts being lowest in individuals with the highest viral loads . It is thought that a second dengue virus infection with a different viral serotype is a risk factor for developing DHF[44] . To determine the effect of secondary infection on the resulting T cell response , we characterized patient infection history and assayed patient blood for the presence of dengue specific IgM and IgG . Primary infection was defined by DENV- specific IgM:IgG >1 . 2 [24] . Accordingly , 19 ( 25 . 7% ) patients were classified as experiencing a primary dengue infection and 48 ( 64 . 9% ) were defined as secondary dengue infection . The antibody results were inconclusive for 7 ( 9 . 4% ) patients . Our results showed no significant difference in DENV specific T cell responses between primary and secondary dengue infection patient groups ( p>0 . 05 ) for any of the DENV peptide pools ( Fig 3C ) . We semi-quantitatively determined the DENV-specific IgM and IgG antibody titres in all patients with DF and DHF , and we found that neither the DENV-IgM nor IgG antibody titres correlated with T cell responses to DENV-NS1 , NS5 and NS3 . However , the DENV-specific IgG antibody titres inversely correlated with viral loads in those with DHF ( Spearman’s r = -0 . 37 , p = 0 . 03 ) ( Fig 4A ) , but not in those with DF ( Spearmans r = -0 . 25 , p = 0 . 16 ) . In analysis of the IgG antibody titres of all patients ( n = 74 ) they too inversely correlated with the degree of thrombocytopenia ( Spearmans r = -0 . 29 , p = 0 . 009 ) ( Fig 4B ) . DENV-specific IgG also correlated with the highest aspartate transaminase ( AST ) ( Spearmans r = 0 . 51 , p = 0 . 004 ) ( Fig 4C ) and alanine transaminase ( ALT ) levels ( Spearmans r = 0 . 4 , p = 0 . 03 ) in all patients with acute dengue infection ( Fig 4D ) .
In this study we set out to investigate the role of T cells in dengue immunity and found that DENV-specific T cells are present at low frequency during acute infection , consistent with previous reports published by us and by others [16 , 17 , 45] . IFNγ production was significantly higher in patients with DF as opposed to DHF , especially during early infection . Those who had lower DENV-NS3 specific T cell responses on day four since the onset of illness ( before development of fluid leakage ) , were significantly more likely to subsequently develop vascular leakage of DHF . In addition , the frequency of pooled DENV-peptide specific , in particular DENV-NS3 specific , T cell responses was associated with resolution of viraemia . Aviraemic patients had significantly higher DENV- specific T cell responses when compared to those who were viraemic . However , overall the majority of patients with both DF and DHF , had a very low magnitude of DENV specific T cell responses . T cell IFNγ responses to DENV NS1 , NS5 and pooled DENV ( NS1 , NS3 and NS5 ) peptides inversely correlated with the degree of thrombocytopenia , but we did not show any relationship with liver transaminases ( AST and ALT levels ) . Both the degree of thrombocytopenia and a rise in both AST and ALT , have been shown to associate with dengue severity [24 , 28] . Therefore , our data show that the early appearance ( on day 4 of illness before any patient developed plasma leakage ) of DENV-NS3 specific T cell responses is associated with milder disease , which is compatible with recent studies regarding the role of T cells in DENV infection [18 , 21–23] . This suggests that DENV-peptide specific T cells are possibly have a protective role against developing severe forms of dengue infection . Although Appana et al also evaluated ex vivo IFNγ to selected peptides of structural and non-structural DENV proteins by ELISpot assays , they did not find any differences in the frequency of DENV-specific T cell responses in patients with DF when compared to those with DHF [46] . However , only peptides that were predicted to bind to certain major HLA alleles were included in the authors’ peptide pools used in the ELISpot assays [46] , whereas here we utilised peptides spanning the entire length of DENV NS1 , NS3 and NS5 , proteins . This difference in experimental approach may have affected the cytokine production profile of the responding T cells in the different disease states . In addition , as the viability and function of T cells have been shown to be affected in those with acute dengue infection [31] , we used freshly isolated PBMCs in all our experiments to limit extraneous cellular stress in contrast to previous studies [15 , 21 , 46 , 47] . In this study , some of the non-structural peptides used were of a different DENV serotype than that causing the acute infection as we used fresh PBMCs in our assays before the infecting serotype was known . As many previous studies on T cell responses have used peptides of unmatched DENV serotypes to assess T cell responses[33 , 46] and also as it was shown that the breadth or the magnitude of DENV specific T cell responses , were similar even when peptides of unmatched serotypes were used [9] , we too proceeded with the same approach . However , there is a possibility that using unmatched peptides could affect the magnitude of the T cell responses . Subsequent subanalysis of T cell responses to DENV1-NS1 and DENV3-NS3 of patients with an acute DENV1 and DENV2 infection , carried out by us also did not show any difference . However , analysis of T cell responses to DENV2 derived NS5 overlapping peptides , showed that patients with an acute DENV2 infection ( matched peptides ) had significantly lower responses than patients with DENV1 infection . We believe this difference is possibly due to 78 . 9% patients with DENV2 having DHF ( and thus poor T cell responses ) , whereas only 46 . 7% of those with DENV1 had DHF . As with most viral infections , the severity of the illness and T cell responses to the DENV has also been shown to depend on the HLA type of the individual [21 , 23 , 48] . However , we did not assess the T cell responses in relation to their HLA type as the primary aim of this study was to assess the overall DENV specific T cell responses based on clinical disease severity and viraemia , irrespective of their HLA types in a large cohort , with relevance to pathogenesis and vaccine design . As the HLA type is known to influence the magnitude of the T cell response , there is a possibility that the differences in the magnitude of T cell responses to different DENV overlapping peptides , could also be due to the differences in their HLA types , which were not assessed here . In general , more severe forms of dengue infection are observed during a secondary heterologous dengue infection [4] , which gave rise to the hypothesis that cross reactive T cells responding to the primary infecting DENV serotype are suboptimal in clearing the secondary virus , and lead to development of more severe disease [14 , 16] . In these studies , it was shown that a tetramer of different viral specificity to the current infecting DENV serotype , sometimes had a higher affinity to the DENV specific T cells [16] . In our study , we did not observe any difference in IFNγ production in overall ex vivo ELISpot assays from PBMCs derived from patients with primary or secondary dengue infection; however , we did not examine variant peptide-specific responses . The broad differences we observed in DENV-specific T cell responses correlated only with clinical disease severity . Interestingly , the DENV-specific IgG levels , which were measured semi-quantitatively , inversely correlated with the degree of thrombocytopenia and also AST and ALT levels , which are known to associate with liver damage . DENV-specific IgG levels are known to be significantly higher in patients with secondary dengue , compared to primary dengue , indeed it is one of the criteria for definition of a secondary dengue infection . However , as we assessed the relationship of total IgG with these laboratory parameters and did not assess the presence of neutralizing antibodies , which are more likely to be protective , this needs to be further evaluated . In summary , we found that DENV-specific T cell IFNγ responses , were associated with milder clinical disease severity and resolution of viraemia , suggesting a protective role for peptide specific T cells early in acute dengue infection .
|
In order to understand the role of dengue virus ( DENV ) specific T cell responses in protection against infection , we studied T cell cytokine production in relation to clinical disease severity and resolution of viraemia in a large cohort of patients with varying severity of acute dengue infection . We found that DENV-specific T cell responses were higher in patients with dengue fever , when compared to those with dengue haemorrhagic fever . In addition , early appearance of DENV-specific T cell responses was significantly associated with milder clinical disease ( p = 0 . 02 ) . DENV peptide specific T cell responses inversely correlated with the degree of viraemia , which was most significant for DENV-NS3 specific T cell responses ( Spearman’s r = -0 . 47 , p = 0 . 0003 ) . The frequency of NS1 , NS5 and pooled DENV peptides , correlated with the degree of thrombocytopenia but had no association with liver transaminases . Our data suggest that early appearance of DENV-specific T cell IFNγ responses appear to associate with milder clinical disease and resolution of viraemia , suggesting a protective role in acute dengue infection .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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2018
|
Quantification of dengue virus specific T cell responses and correlation with viral load and clinical disease severity in acute dengue infection
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Granulomatous and fibrosing inflammation in response to parasite eggs is the main pathology that occurs during infection with Schistosoma spp . CD4+ T cells play critical roles in both host immune responses against parasitic infection and immunopathology in schistosomiasis , and coordinate many types of immune cells that contribute to fibrosis . ICOSL plays an important role in controlling specific aspects of T cell activation , differentiation , and function . Previous work has suggested that ICOS is essential for Th17 cell development . However , the immunopathogenesis of this pathway in schistosomiasis fibrosisis still unclear . Using models of schistosomiasis in ICOSL KO and the C57BL/6 WT mice , we studied the role of the ICOSL/ICOS interaction in the mediation of the Th17 response in host granulomatous inflammation , particularly in liver fibrosis during S . japonicum infection , and investigated the immune responses and pathology of ICOSL KO mice in these models . The results showed that ICOSL KO mice exhibited improved survival , reduced liver granulomatous inflammation around parasite eggs , markedly inhibited hepatic fibrosis development , lower levels of Th17-related cytokines ( IL-17/IL-21 ) , Th2-related cytokines ( IL-4/IL-6/IL-10 ) , a pro-fibrotic cytokine ( IL-13 ) , and TGF-β1 , but higher level of Th1-related cytokine ( IFN-γ ) compared to wild-type ( WT ) mice . The reduced progression of fibrogenesis was correlated with the down-regulation of Th17 and Th2 and the elimination of ICOSL/ICOS interactions . Our findings suggest that IL-17-producing cells contribute to the hepatic granulomatous inflammation and subsequent fibrosis . Importantly , there was a clearly positive correlation between the presence of IL-17-producing cells and ICOS expression in ICOSL KO mice , and additional results indicated that Th17 was involved in the pathological tissue remodeling in liver fibrosis induced by schistosomiasis .
T cell activity is regulated by a complex network of transmembrane receptor/ligand pairs that act in synchrony with the T cell receptor ( TCR ) to inhibit ( co-inhibition ) or enhance ( co-stimulation ) immunity [1] . ICOS , a member of the CD28 family of co-receptor molecules whose expression is induced on activated T cells , was discovered over a decade ago using antibodies raised against activated human T cells and cloned as a 2 . 6 kb complementary DNA sequence encoding a protein with 39% similarity to human CD28 [2] . The ligand of ICOS , ICOSL ( B7h , GL50 , LICOS , B7RP-1 ) , is constitutively expressed at low levels on B cells , macrophages and dendritic cells , and ICOSL expression is further up-regulated upon activation of these cells [3] . The ICOS ligand ( ICOSL ) plays an important role in controlling specific aspects of T cell activation , differentiation , and function [2 , 4] . Both ICOS-deficient and ICOSL-deficient mice have defects in humoral immunity characterized by decreased levels of IgE and IgG1 in the serum and defects in antibody class switching and GC formation [4 , 5] . Fibrosis is a normal consequence of tissue injury and chronic inflammation and is characterized by the accumulation and activation of excessive numbers of fibroblasts , the deposition of extracellular matrix ( ECM ) proteins such as collagen , and the distortion of normal tissue architecture [6] . Although fibrosis typically begins as part of wound healing , the excessive accumulation of collagen and other ECM components during chronic inflammation can lead to the destruction of normal tissue architecture and the loss of function [6] . Thus , fibrosis is a major cause of morbidity and mortality worldwide [7 , 8] . Granulomatous and fibrosis inflammation in response to parasite eggs is the main pathology that occurs during infection with Schistosoma spp . [9 , 10] . CD4+ helper T cells adapt and amplify their responses to match different categories of infections and coordinate many types of immune cells that contribute to fibrosis [11–13] . Mice infected with Schistosoma mansoni develop hepatic granulomas around parasite eggs [14] . However , concurrent immune responses to an extremely diverse repertoire of antigens cause marked exacerbation of the fibrosis in an environment characterized by high levels of IL-13 and IL-4 in the chronic phase of infection [6 , 15] . Reciprocal APC and CD4+ T cell activation following stimulation with egg Ag leads to the increased expression of the co-stimulatory molecules CD80 and CD86 , the secretion of proinflammatory cytokines and chemokines that cause increased lesional recruitment of neutrophils , and ultimately , to the exacerbation of pathology [14] . Extensive evidence links wound healing and fibrosis with Th2 differentiation , characterized by expression of cytokines IL-13 and IL-4 and protection against helminth [11–13 , 16] . The Th1 lineage-specific T-box transcription factor T-bet has been shown to directly repress Th17 differentiation by preventing RUNX1-mediated activation of the lineage-specific transcription factor RORγt [17] . IL-17 and IFN-γ are derived from distinct CD4+ T cells , and the production of each cytokine is suppressed by the other [18] . Using an in vitro system , Stadecker et al . have demonstrated that egg-induced Th17 cell development is driven primarily by IL-23 and IL-1β [19] . Two groups have shown that IL-17-deficient mice develop reduced liver injury compared to wild-type mice [20 , 21] . Previous work has suggested that ICOS is essential for Th17 cell development [18] . Spleen cells isolated from ICOS−/− mice produce significantly less IL-17 than those from normal animals [22] . In contrast , ICOS stimulation of naïve , splenic T cells from normal mice increases IL-17 production [22 , 23] . CBA mice , a naturally high pathology strain , also displayed elevated IL-17 levels comparable to those seen in SEA/CFA-immunized BL/6 mice , and their lesion were similarly reduced by in vivo treatment with anti-IL-17 [24] . Taken together , these findings suggest that Th17 responses are essential for the establishment of schistosome egg-induced immunopathology and that ICOS plays an important role in the regulation of the Th17 response . However , neither the significance nor the immunopathogenesis of this pathway have been elucidated in schistosomiasis fibrosis . Here , usingthe ICOSL KO mice as a model of schistosomiasis , westudied the role of the ICOSL/ICOS interaction in the mediation of the Th17 response in host granulomatous inflammation , particularly in liver fibrosis during S . japonicum infection . It might reveal new therapeutic targets that interfere with Th17 cell migration or differentiation in granulomas and the subsequent fibrosis following infection with S . japonicum .
Animal experiments were performed in strict accordance with the Regulations for the Administration of Affairs Concerning Experimental Animals ( 1988 . 11 . 1 ) , and all efforts were made to minimize suffering . All animal procedures were approved by the Institutional Animal Care and Use Committee ( IACUC ) of SoochowUniversity for the use of laboratory animals ( Permit Number: 2007–13 ) . Female C57BL/6 WT mice ( 6–8 weeks old ) were purchased from the Center of Comparative Medicine of Yangzhou University ( Yangzhou , China ) . Female ICOSL KO C57BL/6 mice were purchased from Jackson Laboratory ( Bar Harbor , Maine , USA ) . All mice were raised under specific pathogen-free conditions at the laboratory animal research facility of Soochow University ( Suzhou , China ) . Snails ( Oncomelaniahupensis ) harboring S . japonicum cercariae ( Chinese mainland strain ) were purchased from Jiangsu Institute for Schistosomiasis Control ( Wuxi , China ) . For the kinetic analysis of T cell populations , cytokines and serumhyaluronic acid ( HA ) and hydroxyproline ( HYP ) titers , each mouse was infected with 14 ( ±1 ) cercariae of S . japonicum through the abdominal skin . At 4 , 7 , 12 , 16 , and 20 weeks post-infection , five mice were randomly chosen from the infected and control groups and sacrificed for further studies . Single-cell splenocyte suspensions were prepared by mincing the spleens in PBS ( Sigma Corporation , St . Louis , USA ) containing 1% FBS ( Gibco , Grand Island , NY ) . Red blood cells were lysed using ACK lysis buffer . Soluble egg antigens ( SEA ) of S . japonicum were purchased from Jiangsu Institute for Schistosomiasis Control ( Wuxi , China ) . The splenocytes from S . japonicum infected mice were cultured in complete RPMI 1640 medium ( Gibco ) containing 10% FBS , 25 μg/ml of SEA , 100 U of penicillin/ml , and 0 . 1 mg/ml of streptomycin . Subsequently , the cells were plated in flat-bottom 96-well platesat a density of 3×106 per well and cultured withcomplete media for 72 hours ( h ) at 37°C in 5% CO2 condition . Culture supernatants were collected at 4 , 7 , 12 , 16 , and 20 weeks post-infection for ELISA . IFN-γ , IL-2 , IL-12p40 , IL-4 , IL-17A , IL-21 , TGF-β1 , IL-13 , IL-6 and IL-10levels in the cultured supernatant were measured by ELISA using the ELISA Ready-SET-Go kit ( eBiosicence , San Diego , CA ) according to the manufacturer’s protocol . The optical density ( OD ) of the plates was read at 450 nm using an ELISA reader ( Bio-Rad mod . 550 ) . Serum HA and HYPtiters of C57BL/6 WT mice infected with S . japonicum were measured by ELISA using the ELISA Ready-SET-Go kit ( eBiosicence , San Diego , CA ) according to the manufacturer’s protocol . The optical density ( OD ) of the plates was read at 450 nm using an ELISA reader ( Bio-Rad mod . 550 ) . Livers were dissected and immediately fixed in 10% buffered formalin , and liver sections were embedded in paraffin . The immunohistochemical technique employed a two-step method ( peroxidase-conjugated polymer ) . Endogenous peroxidases were blocked with 3% H2O2 , and the non-specific binding was inhibited with 10% normal goat serum ( Boster , Wuhan , China ) . The slides were incubated with primary antibodies diluted with PBS ( 1:100 ) at 37°C for 1 h and then at 4°Covernight . The slides were further incubated with the secondary antibodies ( ChemMate Envision/HRP , rabbit/mouse detection kit , Gene-tech , Shanghai , China ) at 37°C for 1 h . The reaction was then developed with DAB as the chromogen , and histological sections were counterstained with Mayer’s hematoxylin . For the negative controls , PBS was used instead of the primary antibody . In brief , five high-power fields ( ×400 ) were randomly selected and observed with a light microscope ( Leica DM2500 ) . The staining intensity and percentage of positive cells were assessed using the Leica QWin Plus software , version 3 . 5 . 1 ( Leica Microsystems , Switzerland ) . The percentage of positively staining cells in 15 granulomas was assessed using the Leica QWin Plus software , version 3 . 5 . 1 ( Leica Microsystems , Switzerland ) . The mean of % positively staining cells in 15 granulomas +/− SD was then calculated to assess the expression of TGF-β1 ( rabbitpolyclonal; 1:500; Santa Cruz , USA ) , IL-13 ( rabbitpolyclonal , 1:100 , Boster , China ) , and the levels of the fibrosis-associated immunopathological elements MMP-9 ( rabbitpolyclonal , 1:150 , Boster , China ) and TIMP-1 ( rabbitpolyclonal , 1:100 , Boster , China ) in the liver granulomas . Paraformaldehyde-fixed liver specimens were dehydratedin a graded alcohol series . Following xylene treatment , the specimens were embedded in paraffin blocks , cutinto 5-μm thick continuous sections , and placed on glass slides . The sections were then stained with Masson trichrome ( MT ) according to standardprocedures [25] . To describe and evaluate liver pathologicalchanges , a pathologist who was blinded to the researchdesign examined 10 different low-power fields of MT-stained sections ( selected fields were in almostthe same location ) for each mouse . In addition , the percentageof collagen calculated by a multimedia color imageanalysis system ( Image-Pro Plus 6 . 0 ) was measured asa relative objective index to evaluate the degree of liver fibrosis . Each MT-stainedsection was examined at 400×magnification . Fibrotic areas were scanned and summed bythe software . The percentage of collagen was expressedas the ratio of the collagen-containing area to the wholearea [25] . Furthermore , liver samples from ICOSL knockout and C57BL/6J mice at 7 , 12 , 16 and 20 weeks after infection were embedded in paraffin . Liver sections were examined under a microscope to determine the pathology of egg granuloma . Individual egg granulomas were located and their maximal diameters across opposing axes ( A and B ) were measured under an optical microscope; the volume of granuloma was calculated based on formula V = πAB2/6 [26] . Briefly , 1×106 splenocytes were incubated in 100 μl of PBS . The cells were then stained with a mixture of PE- and FITC-conjugated mAbs for 30 min , washed twice , then fixed with 4% paraformaldehyde in PBS . The analysis was performed on a FACS Calibur Flow Cytometer ( BD Biosciences ) . All procedures were performed on ice until the time of analysis . The mAbs for flow cytometry were purchased from eBioscience ( San Diego , USA ) and included FITC-conjugated anti-CD4 , FITC-conjugated anti-CD19 , PE-conjugated anti-ICOS , PE-conjugated anti-ICOSL , PE-conjugated anti-RORγtand PE-conjugated anti-IL-17R . All statistical analyses were performed by SPSS13 . 0 Data Editor ( SPSS Inc . , Chicago , IL , USA ) . The differences of the data between all the groups were compared by two-way ANOVA followed by Tukey’s multiple comparison test . Spearman’s rank correlation was used for correlation analyses . Differences with P<0 . 05 were considered statistically significant . Each individualexperiment was conducted with groups of 5 mice and repeatedat least twotimes .
To elucidate the role of ICOSL/ICOS signaling in modulating the pattern of cytokine production in the ICOSL KO and WT C57BL/6 control strains , the mice were infected with S . japonicum ( 14±1 cercariae ) and euthanized at 0 ( before infection ) , 4 ( early stage ) , 7 ( acute stage ) , 12 ( chronic stage ) or 16 ( advanced stage ) weeks post-infection . Splenocytes were cultured in the presence of SEA for 72 h , and cytokines were measured in the culture supernatants by ELISA . The results showed that the production of IFN-γ , IL-2 and IL-12 ( Th1-related cytokines ) were elevated at 4 weeks post-infection and peaked at 7 weeks post-infection ( Fig . 1A , 1B , 1C ) . When the disease progressed from the acute to the chronic phase , the expression levels of Th1-related cytokines started to decrease , while the production of IL-4/IL-6/IL-10 ( Th2-related cytokines ) ( Fig . 1D , 1I , 1J ) and IL-17A/IL-21 ( Th17-related cytokines ) ( Fig . 1E , 1F ) increased . The levels of Th2- and Th17- related cytokines peaked at 12 weeks post-infection before decreasing gradually . The production of IL-17A/IL-21 by ICOSL KO mice was significantly lower than that byWT controls ( Fig . 1E , 1F ) . In contrast , the production of IFN-γby ICOSL KO mice was significantly higher than that byWT controls ( Fig . 1A ) . The production of anti-inflammatory cytokine , TGF-β1 , and the classic pro-fibrotic cytokine IL-13 by whole spleen cells were measured following infection . The results showed that ICOSL KO mice produced significantly lower amounts of TGF-β1 and IL-13 than those of the WT controls ( Fig . 1G , 1H ) . Then , we determined the HA and HYP titers in C57BL/6 mice following S . japonicum infection and analyzed the correlation between the HA/HYPtiters and the IL-4/IL-13/TGF-β1/IL-10/IL-17A levels ( S1 Fig . ) . The IL-4/IL-13/TGF-β1 levels were positively correlated with the HA/HYP titers in C57BL/6 mice following S . japonicum infection ( P<0 . 0001 ) ( S2 Fig . ) . Importantly , the IL-17A levels were also positively correlated with the HA/HYP titers in C57BL/6 mice following S . japonicum infection ( P<0 . 01 or P<0 . 05 ) ( S2 Fig . ) . The data suggest that ICOSL/ICOS interactions play a key role in establishing the pattern of the cytokine response to S . japonicum infection . The expression levels of ICOS and ICOSL in splenocytes of the WT mice were elevated at 4 weeks post-infection and peaked at 12 weeks before decreasing gradually ( Figs . 2A , 3A ) . Relatively small changes in ICOS expression were observed in CD4+ T cells of ICOSL KO mice infected with S . japonicum . In contrast , the WT mice showed a comparatively considerable increase in ICOS expression after infection . The data also showed that the expression of ICOS was significantly down-regulated in ICOSL KO mice compared to WT controls at 4 , 7 , 12 , and 16 weeks post-infection ( Fig . 2A ) . As expected , the expression of ICOSL was extremely low in ICOSL KO mice at all time points after S . japonicum infection ( P<0 . 05 ) ( Fig . 3A ) . ICOSL KO mice also exhibited decreased levels of RORγtand IL-17Rafter 4 weeks post-infection ( Figs . 2B and 3B ) . We then analyzed the correlation between the RORγt levels and the HA/HYP titers . The RORγt levels were positively correlated with the HA and HYP titers in C57BL/6 mice following S . japonicum infection ( P<0 . 0001 ) ( S3 Fig . ) . These data suggest thatICOSL/ICOS might be required for expanding IL-17-producing cells in mice following S . japonicum infection and Th17 responses are involved in the pathogenesis of fibrosis . Histological examination of granulomas in mice infected with S . japonicum showed that granulomas were found in mouse livers 7 weeks post-infection ( Fig . 4A ) . The volume of the granuloma was the largest at that time point ( Fig . 4A ) . Twelve weeks after the infection , the formation of granuloma began to reduce ( Fig . 4A ) . Comparing the volume of granulomas in the ICOSL KO and wild type mice at 7 , 12 , 16 and 20 weeks after the infection showed that the size of granulomas were significantly smaller in the ICOSL KO mice than those of the WT mice ( P<0 . 05 ) ( Fig . 4A ) . Furthermore , ICOSL KO mice showed improved survival compared to WT mice ( P = 0 . 017 ) ( Fig . 4B ) . Along with more extensive size of granulomas in the liver , the expression of TGF-β1 and IL-13 was significantly increased in murine schistosomiasis ( Fig . 5B ) . Many cells were stained dark yellow in the slides of liver tissue , mainly around granuloma inflammatory cellsand the portal area cells around areas of fibrosis ( Fig . 5A ) . Liver cells around granulomas also showed strong expression of TGF-β1 and IL-13 . The expression levels of TGF-β1 and IL-13 in S . japonicum infected ICOSL KO mice were lower than those in S . japonicum infected WT mice at 12 weeks post-infection ( P<0 . 05 ) ( Fig . 5B ) . These observations were consistent with analysis of cytokines in the supernatants of SEA-stimulated splenocytes ( Fig . 1G , 1H ) . In addition , we observed lower levels of the fibrosis-associated immunopathologic elements MMP-9 and TIMP-1 in the ICOSL KO mice compared to the controls at the advanced stage of infection ( 16 weeks ) ( Fig . 5B ) . Masson trichrome stained sections of liver showed typical pathological characteristics of liver of schistosomiasis with remarkable acute granuloma formation and subsequent liver fibrosis from week 7 through week 16 ( Fig . 6A ) . Moreover , analysis of Mason trichrome staining showed that the ICOSL KO group developed mild hepatic fibrosis and reduced collagen production compared to WT mice ( Fig . 6B ) . These data indicate that blockade of ICOSL/ICOS interaction might decrease schistosomiasis-induced immunopathology and fibrogenesis by suppressing Th17 and Th2 generation .
Schistosomiasis is a parasitic disease that has a devastating impact on both humans and animals [9] . Both humoral immunity and cellular immunity are involved in the formation and development of hepatic egg granuloma [9 , 14] . The full activation and differentiation of T cells into Th1 , Th2 or Th17 cells requires co-stimulatory molecules and cytokines [1–4] . ICOS has also been implicated in chronic inflammation and is critical for Th17 cell development [21] . By use of anti-ICOS mAbs , the blockade of ICOS during the effector phase of EAE has been shown to abrogate disease , whereas blockade during priming does not; this suggests an important role for ICOS in Th17 effector responses [27] . The ICOSL/ICOS pathway plays different roles in different models of autoimmune and infectious disease [28–31] . ICOS knockout miceareincapable of controlling viral or worm infections owing toimpaired Th1 and Th2 responses , respectively [28] . Administration of blocking anti-ICOSL mAbs results in a striking reduction in the development of experimental rheumatoid arthritis and lupus nephritis , which correlates with reduced T follicular helper ( Tfh ) differentiation and germinal center formation [29] . Although several studies have focused on the contribution of Th2 cells to chronic inflammatory disease and fibrosis , which is characterized by the cytokines IL-4 and IL-13 [11 , 12 , 16 , 32] , CD4+ IL-17-secreting T cells have been shown to contribute to pathology in some models of liver fibrosis . In patients with idiopathic pulmonary fibrosis ( IPF ) , IL-17A cooperates with and cross-regulates IL-1β , and the interaction of these cytokines contributes critically to neutrophil recruitment and lung fibrosis and possibly to liver fibrosis [33–35] . IL-17A is also elevated in IPF patients [35] . The analysis of cytokines in the supernatants of SEA-stimulated splenocytes ( Fig . 1 ) showed that ICOSL KO mice produced higher levels of IFN-γ but lower levels of IL-17A than WT mice . Usingthe IL-17−/− and IFN-γ−/− mouse model , Rutitzky et al . [14] demonstrated that severe immunopathology in murine schistosomiasis is primarily due to IL-17 and is regulated by IFN-γ . IL-17−/− mice demonstrated significantly reduced immunopathology , despite increased levels of IFN-γ , while IFN-γ−/− mice displayed markedly elevated immunopathology correlating with increased levels of IL-17A [14] . As shown in Fig . 1F , ICOSL KO mice displayed reduced levels of IL-21 compared to WT mice , particularly at 7 weeks post-infection . As an autocrine regulator of Th17 cell development , IL-21 plays a key role in inducing the differentiation of Th17 cells and suppressing the Th1 response [36 , 37] . Also , it is well known that the secretion of IL-21 is restricted mainly to Tfh cells and Th17 cells , and IL-21 is associated with Tfh cells as well as IL-17 responses [38] . Therefore , eliminating ICOSL has shown defective ICOSL/ICOS interactions in the ICOSL KO mice infected with S . japonicum , leading to reduced levels of IL-21 , which may have decreased the Tfh and B cell responses , and thus provide one explanation for the down-regulation of the Th17 response associated with IL-21 and ICOSL/ICOS interactions . In addition , the ICOSL KO mice had elevated IL-2 levels ( Fig . 1B ) , and this cytokine has been shown to elevate Th1 responses and suppress Th17 responses [36] . The results ( Fig . 1G , 1H ) also showed significantly reduced levels of TGF-β1 and IL-13 in the supernatant of SEA-stimulated splenocytes at both the acute and advanced stages . Researchers have demonstrated that TGF-β1 plays a predominant role in the differentiation of Th17 cells and limits Th1 and Th2 responses [15 , 36–37 , 39–43] . Our data further indicated that blocking ICOSL/ICOS signaling might result in defective differentiation and expansion of Th17 cells following S . japonicum infection through the down-regulation of TGF-β1 . The observation that ICOS was down-regulated in CD4+ T cells of ICOSL KO mice indicates a critical role for ICOSL/ICOS signaling in the expression of ICOS following S . japonicum infection . As shown in Fig . 2B , ICOSL KO mice exhibited significantly lower levels of RORγt at the chronic stages compared with WT controls . RORγt is considered to be dispensable in the development of Th17 cells but is required for the full differentiation of naïve CD4+ T cells into Th17 cells [37 , 39–41] . These results indicated that ICOSL/ICOS interactions may promote the differentiation and expansion of Th17 cells following infection with S . japonicum . Meanwhile , the percentages of RORγt+ cells in CD4+ T cells were positively correlated with the HA and HYP titers in mice infected with S . japonicum ( S3 Fig . ) . Serum HA and HYPare good markers for the initial phase of hepatic fibrosis and it was able to assess severity of liver disease in schistosomiasis [6 , 44 , 45] . To further understand how the ICOSL/ICOS signal contributes to the development of severe hepatic fibrogenesis after Schistosoma infection , paraffin sections of liver from infected mice were evaluated by immunohistochemistry . Consistent with results of the cytokine analysis ( Fig . 1 ) , IL-13 and TGF-β1 werealso shown to be markedly reduced in ICOSL KO mice compared to the WT controls at 12 weeks post-infection ( P<0 . 001 ) ( Fig . 5 ) . IL-13 is a potent inducer of MMP-9 and TGF-β1 [46 , 47] . TGF-β1 , a known mediator of fibrosis , is the most widely studied cytokine in the context of fibrogenesis [46] . It has been suggested that IL-13 mediates its effects by regulating the production and activation of TGF-β1 [47] . The data presented hereinindicate that the neutralization of ICOSL affords protection against the development of severe hepatic granulomatous inflammation , particularly fibrosis induced by the immune response to egg Ags . The fibrotic tissue of ICOSL KO mice also contained lower levels of MMP-9 and TIMP-1 than those of WT mice ( Fig . 5 ) . Furthermore , the ICOSL KO mice exhibited lower fibrillar collagen expression around S . japonicum eggs ( Fig . 6 ) and improved survival ofmice infectedwith S . japonicum than that of WT mice ( Fig . 4B ) . These results provide further evidence of a down-regulated granulomatous immune response/fibrosis synthesis in ICOSL KO mice , due in part to a defect in the expansion of the differentiated Th17 cell population , but also IL-13 , TGF-β1 and IL-4 . Studies with other systems have shown that ICOS expression persists at high levels on Th2 cells[48] . Furthermore , disruption of ICOSL/ICOS pathway has been found to be beneficial when treating diseases dominated by Th2-type cytokine production , such as asthma [49 , 50] . All these studies are in line with ours; however , ICOS deficiency or blocking ICOS has been reported to no change or increase in the size of egg induced granulomas during S . mansoni infection[51 , 52] . The results of the current study contradict these studies , which may be due to the different Schistosoma species or different mice strains used . It appears that the ultimate effects of the ICOSL/ICOS pathway is dependent on the particular model of study . All of these results suggest that IL-17-producing cells could contribute to the hepatic granulomatous inflammation and subsequent fibrosis in addition to the Th1 , Th2 and Th17 associated cytokines . Also , a clearly positive correlation between the presence of IL-17-producing cells and ICOS expression in ICOSL KO mice was observed , which suggested that Th17 cells were involved in the pathological tissue remodeling in liver fibrosis induced by schistosomiasis . The well-understood Th2 response in previous studies [53–55] in combination with our present studies of correlation betweenTh2/Th17 and fibrosis ( S1 , S2 , S3 Figs . ) , indicated that both Th2 and Th17 responses could play animportant role in pathology/mortality including the fibrosis in schistosomiasis . In summary , our findings indicated that Th17 responses is one of the promotor driving fibrosis in schistosomiasis in addition to Th2 responses , and emphasizedthat ICOSL/ICOS signaling mediates the IL-17-producing CD4+ T cell response which could contribute to severe hepatic granulomatous inflammation and subsequent fibrosis via Th17 . This study further clarifies the immune regulatory mechanism of fibrosis and sheds light on the understanding of the immunopathogenesis of Schistosoma induced fibrosis .
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The full activation and differentiation of T cells into Th1 , Th2 or Th17 cells requires costimulatory molecules and cytokines . ICOS has also been implicated in chronic inflammation and is critical for Th17 cell development . CD4+ IL-17-secreting T cells have been shown to contribute to pathology in some models of liver fibrosis . However , neither the significance nor the immunopathogenesis of this pathway have been elucidated in schistosomiasis fibrosis . The present study used the ICOSL KO mice to assess the role of the ICOSL/ICOS interaction in the mediation of the Th17 response in host granulomatous inflammation , particularly in liver fibrosis during S . japonicum infection . This study further clarifies the immune regulatory mechanism of fibrosis and sheds light on the understanding of the immunopathogenesis of Schistosoma-induced fibrosis . It might reveal new therapeutic targets that interfere with Th17 cell migration or differentiation in granulomas and the subsequent fibrosis following infection with S . japonicum .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Th17 Down-regulation Is Involved in Reduced Progression of Schistosomiasis Fibrosis in ICOSL KO Mice
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Staphylococcus aureus frequently invades the human bloodstream , leading to life threatening bacteremia and often secondary foci of infection . Failure of antibiotic therapy to eradicate infection is frequently described; in some cases associated with altered S . aureus antimicrobial resistance or the small colony variant ( SCV ) phenotype . Newer antimicrobials , such as linezolid , remain the last available therapy for some patients with multi-resistant S . aureus infections . Using comparative and functional genomics we investigated the molecular determinants of resistance and SCV formation in sequential S . aureus isolates from a patient who had a persistent and recurrent S . aureus infection , after failed therapy with multiple antimicrobials , including linezolid . Two point mutations in key staphylococcal genes dramatically affected clinical behaviour of the bacterium , altering virulence and antimicrobial resistance . Most strikingly , a single nucleotide substitution in relA ( SACOL1689 ) reduced RelA hydrolase activity and caused accumulation of the intracellular signalling molecule guanosine 3′ , 5′-bis ( diphosphate ) ( ppGpp ) and permanent activation of the stringent response , which has not previously been reported in S . aureus . Using the clinical isolate and a defined mutant with an identical relA mutation , we demonstrate for the first time the impact of an active stringent response in S . aureus , which was associated with reduced growth , and attenuated virulence in the Galleria mellonella model . In addition , a mutation in rlmN ( SACOL1230 ) , encoding a ribosomal methyltransferase that methylates 23S rRNA at position A2503 , caused a reduction in linezolid susceptibility . These results reinforce the exquisite adaptability of S . aureus and show how subtle molecular changes cause major alterations in bacterial behaviour , as well as highlighting potential weaknesses of current antibiotic treatment regimens .
The factors promoting persistence of bacterial infection in the face of apparently effective antimicrobial therapy have not been clearly defined . This particularly applies to Staphylococcus aureus , especially methicillin-resistant S . aureus ( MRSA ) , which remains a major human pathogen that frequently causes invasive disease , often associated with a high mortality rate [1] , [2] , [3] . A number of bacterial factors have been associated with persistent bacteremia and failed antimicrobial therapy for serious MRSA infections , including reduced activity of the quorum sensing system agr , resistance to host antimicrobial peptides , and the evolution of reduced vancomycin susceptibility in patients treated with this antibiotic [4] , [5] . Although traditionally considered an extracellular organism , recently it has been demonstrated that S . aureus can reside and persist in an intracellular state [6] . A staphylococcal phenotype that appears to be particularly associated with cellular invasion and clinical persistence is the small colony variant ( SCV ) phenotype [6] , [7] . This is phenotypically characterised by reduced growth rate , small colony size and in some cases auxotrophism for hemin or menadione , related to mutations in genes encoding products involved in the electron transport system . Small colony variants of S . aureus have been associated with persistent and recurrent S . aureus infections , and with increased antimicrobial resistance [7] . The mechanisms of the SCV phenotype in S . aureus have been investigated in detail over a number of years . Defined hemB and menD mutants [6] , [7] of laboratory S . aureus strains have defects in electron transport , and have demonstrated global transcriptional changes [8] , increased cellular attachment , invasion and persistence [9] , [10] , [11] , reduced antibiotic susceptibility [12] , and reduced virulence [13] . However , despite this significant work the molecular correlates of persistence have not been definitively elucidated in clinical isolates of S . aureus . One important bacterial response to stress and nutritional starvation , including antimicrobial challenge , is activation of the stringent response , mediated by intracellular accumulation of the alarmones ppGpp and pppGpp [ ( p ) ppGpp] , which are usually controlled by the activities of a synthetase ( RelA ) and a hydrolase ( SpoT ) [14] . In gram positive organisms , including S . aureus , a single rel gene encodes a protein with synthetase and hydrolase domains that controls the stringent response under stressful conditions , while other synthetases such as RelP and RelQ provide basal levels of ( p ) ppGpp during non stressful conditions [14] , [15] , [16] , [17] . The stringent response has been associated with persistence of infection in Mycobacterium tuberculosis , where it is important for the long term survival of the organism [18] , and recently has been linked with growth defects and vancomycin tolerance in E . faecalis [17] . However , different bacteria have developed different strategies to utilize the alarmones in intracellular signalling , with diverse regulatory changes found in different organisms [19] . The impact of an active stringent response has not been studied in S . aureus , mainly because a functional hydrolase domain of the RelA/SpoT homolgue in S . aureus ( RelA ) is essential for survival of the organism [19] , [20] , [21] . Although mupirocin is a strong inducer of the stringent response in S . aureus and has been used to investigate the transcriptional profile of an active stringent response in this organism , it also leads to RelA/SpoT independent transcriptional changes [19] , [22] , indicating that the mupirocin model alone is not an optimal strategy to study the stringent response in this organism . Although it could be anticipated that the bacterial stringent response would play a role in the adaptation of S . aureus to antimicrobial challenge during persistent infection , this has not been previously reported . For many years vancomycin has been the mainstay of therapy for serious MRSA infections [5] . However , with increasing antimicrobial resistance in MRSA , including resistance to vancomycin , the newer , novel antimicrobials such as linezolid and daptomycin are the last available therapies in some patients [5] . While there are increasing reports of daptomycin non-susceptible S . aureus strains [23] , reports of reduced linezolid susceptibility in S . aureus have , to date , been rare . Linezolid is the first in a new class of antimicrobials , the oxazolidinones , that bind to the A site of the peptidyl transferase centre ( PTC ) of the bacterial ribosome [24] , inhibiting bacterial ribosomal protein synthesis . Resistance to linezolid in S . aureus has primarily been related to target site mutations in domain V of 23S rRNA , especially the G2576U mutation [25] , [26] . Recently , however , a naturally occurring resistance gene cfr , which encodes Cfr methyltransferase and leads to modification of adenosine at position 2503 in 23S rRNA has been described in a single S . aureus isolate from Columbia , and in two staphylococcal clinical isolates from the USA [27] , [28] . The cfr gene on the chromosome was associated with mobile genetic elements , suggesting the resistance mechanism may be transferable [27] . The S . aureus genome encodes a number of conserved RNA methyltransferases , including RlmN ( encoded by SACOL1230 ) , and although methylation of rRNA is a common mechanism of acquired antimicrobial resistance [29] , mutations in chromosomally encoded RNA methyltransferases have not been linked to reduced linezolid susceptibility in S . aureus . Recently , we treated a patient with persistent and recurrent methicillin-resistant S . aureus ( MRSA ) bacteremia despite extensive , appropriate antimicrobial therapy . The clinical isolates obtained following treatment demonstrated significant antimicrobial resistance , including reduced susceptibility to linezolid , and features characteristic for small colony variant strains ( SCV ) of S . aureus [6] , [7] . However , phenotypic features suggested that mutations were not present in hemin or menadione biosynthesis genes . Therefore we investigated the mechanisms of persistence and antimicrobial resistance in these isolates using a combined comparative and functional genomics approach , and discovered a clinical isolate with a persistently activated stringent response , and a novel mechanism of reduced linezolid susceptibility .
A 73-year old man with end-stage renal failure was admitted with line related methicillin-resistant S . aureus ( MRSA ) bacteremia . The MRSA was susceptible to clindamycin , trimethoprim-sulfamethoxazole , ciprofloxacin , vancomycin , rifampicin and fusidic acid . He was commenced on intravenous vancomycin , and due to persistent S . aureus bacteremia , rifampin and ciprofloxacin were added . After 16 days of ongoing bacteremia and detection of heterogeneous vancomycin-intermediate S . aureus ( hVISA ) , vancomycin was changed to oral linezolid and he completed 18 days of linezolid combined with rifampicin and ciprofloxacin . Multiple investigations including transesophageal echocardiogram , computed tomography of brain , chest , abdomen , pelvis and lumbar spine , and white cell/SPECT imaging did not reveal any definite focus . Eleven days later he developed fever , hypotension and back pain and blood cultures were again positive for MRSA , on this occasion a small colony variant ( SCV ) . He was recommenced on oral linezolid and completed 6 weeks of therapy . Five days later he developed severe lumbar back pain and raised inflammatory markers . A single blood culture and a lumbar aspirate from the L3–4 region again cultured SCV-MRSA ( Fig . 1 ) . He was commenced on intravenous linezolid and completed 6 weeks of therapy , and was changed to trimethoprim-sulfamethoxazole for long-term suppressive treatment . Pulsed field gel electrophoresis demonstrated that the SCV strain JKD6229 emerged from the parental strain ( JKD6210 ) [5] ( Fig . 1 ) , but JKD6229 did not demonstrate auxotrophism for hemin or menadione [7] . Both strains were multi-locus sequence type 5 . During failed therapy , resistance to ciprofloxacin , rifampin and reduced susceptibility to linezolid developed ( Table 1 ) . Initially , to understand the molecular determinants of clinical persistence in the SCV-MRSA isolate JKD6229 the transcriptional profile was analysed . Using microarray transcriptional analysis significant global gene expression changes were found in the SCV strain ( JKD6229 ) compared to the parental strain ( JKD6210 ) ( 349 genes up-regulated and 175 genes down-regulated ≥2-fold ( see Fig . 2 , Table 2 and Table S1 ) . Changes included pronounced up-regulation ( up to 80-fold ) of genes encoding capsule biosynthesis in JKD6229 ( cap5A to cap5P; SAV0149 to SAV0164 ) . To confirm the biological impact of capsule gene transcriptional changes the capsule type of JKD6210 and JKD6229 was confirmed as type 5 by PCR [30] , and a capsule immunoblot was then performed . This demonstrated significant enhancement of capsule production in JKD6229 compared to the parental strain JKD6210 and the capsule type 5 control strain Newman ( Fig . 2B ) . Intracellular persistence and the SCV phenotype of S . aureus has previously been associated with down regulation or complete loss of activity of the global quorum sensing accessory gene regulator ( agr ) [31] , however all genes encoding the agr locus ( SAV2036 to SAV2039 ) and the delta-hemolysin precursor ( SAS1940a ) were significantly up-regulated in the SCV strain JKD6229 ( 2 to 10-fold increased expression ) . Associated with this was up-regulation of two genes encoding exotoxins ( alpha-hemolysin [SAV1163] , 5 . 9-fold increase; enterotoxin P [SA1761] , 2 . 8-fold increase ) , however the SAV1163 orthologue in JKD6210 and JKD6229 was found to be a pseudogene because of a point mutation introducing a premature stop codon . Distinct differential regulation of genes involved in carbohydrate transport and metabolism , amino acid metabolism and oligopeptide transport was also detected . Genes involved in lactose utilization and galactose metabolism ( SAV2189-SAV2194 ) were remarkably down-regulated ( up to 100-fold ) , with similar changes found in genes encoding key glycolysis enzymes such as pgi ( SAV0962 , glucose-6-phophate isomerase ) , while genes with products potentially involved in metabolism of alternative carbon sources such as sucrose , fructose and galactitol ( scrA , gatC , fruA , fruB ) were up-regulated in SCV JKD6229 . Amino acid metabolism was another distinct functional class that was up-regulated in SCV JKD6229 . Genes encoding valine , leucine and isoleucine biosynthesis enzymes showed increased expression , as did genes such as rocD ( SAV0957 ) and argJ ( SAV0183 ) linked to ornithine and arginine production . Striking too was the up-regulation of the Opp3 oligopeptide transport system ( SAV0986–SAV0994 ) . Opp3 facilitates the acquisition 4–8 aa-long peptides from the extracellular environment and it is the only known functional oligopeptide transport system in S . aureus [32] . The prominent transcriptional changes detected in JKD6229 compared to JKD6210 suggested SCV JKD6229 had undergone important genetic changes . In addition , the transcriptional profile of SCV JKD6229 was significantly different to the transcriptional profile of the SCV hemB mutant , suggesting that mutations in other genes may be contributing to the SCV phenotype of this strain [8] . Therefore whole genome sequencing and comparison of the parental MRSA strain JKD6210 and the SCV JKD6229 was performed . Illumina short-read sequencing yielded 2 . 7 Mb of mappable data for each genome . After detailed reciprocal sequence comparisons and comparisons against the reference genomes S . aureus COL and S . aureus N315 , the only changes detected in JKD6229 compared to JKD6210 were two nucleotide substitutions , two codon insertions , and the loss of a ∼15 kb plasmid ( Table 3 ) . The sequences for JKD6210 and JKD6229 were aligned to the genome sequence of N315 ( also MLST 5–the same as JKD6210 and JKD6229 ) and this demonstrated that 97 . 2% of N315 was covered to a depth of ≥20 in both JKD6210 and JKD6229 . The regions not covered in N315 by the JKD6210 sequence were the same as the regions not covered by the JKD6229 sequence . PCR and Sanger sequencing confirmed the presence of each mutation in SCV JKD6229 , and PCR and plasmid analysis confirmed the loss of the plasmid in JKD6229 . Annotation and BLAST analysis of the plasmid ( denoted as pJKD6210 ) revealed a pUSA300-HOU-MS-like replicon ( Fig . 3 ) with genes encoding beta-lactam resistance , but absence of the genes encoding cadmium resistance that are present on pUSA300-HOU-MS [33] . All four changes in nucleotide sequence were associated with a predicted amino acid change or addition , suggesting one or more of these mutations might be responsible for the phenotypic changes in JKD6229 . Two of the four mutations clearly corresponded with the acquired antibiotic resistance of SCV JKD6229 . The change in rpoB that led to a H481Y substitution is a mutation commonly linked with rifampin resistance in S . aureus [34] and the amino acid insertion in parC ( encoding Topoisomerase IV ) likely contributed to reduced ciprofloxacin susceptibility in this strain . Single mutations in topoisomerase IV without additional mutations in DNA gyrase are often associated with low-level quinolone resistance [35] , as demonstrated in JKD6229 ( Table 1 ) . The ‘CAA’ insertion in SACOL1230 , encoding RlmN , a ribosomal RNA large subunit methyltransferase , was associated with the linezolid exposure of SCV JKD6229 . RlmN methylates 23S ribosomal RNA at adenosine 2503 , and deletion of the gene renders S . aureus more susceptible to linezolid [36] . Linezolid resistance in clinical isolates of staphylococci is often linked to G2576T mutations in domain V of the 23S rRNA genes [37] or acquisition of a plasmid-encoded cfr ( methyltransferase ) , which also methylates ribosomal RNA at position 2503 [28] . Interestingly , a 23S rRNA T2500A mutation has also been previously linked to linezolid resistance in a clinical isolate of S . aureus [38] , but mutations in SACOL1230 have never been reported . The ‘CAA’ insertion in JKD6229 is predicted to incorporate an additional glutamate to the motif ( DIDACCGQ’Q’ ) at the extreme C-terminus of the enzyme , a motif that is absolutely conserved among diverse Gram positive and negative bacteria [36] . An allelic replacement experiment was performed , where the normal SACOL1230 sequence from JKD6210 was replaced with the mutated SACOL1230 allele from JKD6229 using pKOR1 [39] . The SCV clinical strain ( JKD6229 ) and the mutant JKD6300 ( JKD6210 with SACOL1230 ‘CAA’ insertion ) both demonstrated an increase in linezolid MIC within the susceptible range when an Etest using a 2 McFarland inoculum was used ( Table 1 ) . The fourth mutation occurred in SACOL1689 . Based on high amino acid sequence similarity ( 71% amino acid similarity ) to an ortholog in Streptococcus mutans , SACOL1689 ( relA ) is predicted to encode a bifunctional enzyme that modulates the amount of the intracellular signalling molecules guanosine 3′-diphosphate 5′-triphosphate and guanosine 3′ , 5′-bis ( diphosphate ) , abbreviated to ( p ) ppGpp [40] . Accumulation of ( p ) ppGpp , activates the bacterial stringent response leading to a switch to “survival mode” [17] , [18] . The mutation in relA ( SACOL1689 ) was of particular interest with respect to SCV formation because of the involvement of this gene in the bacterial stringent response and the potential impact on growth characteristics of an enhanced stringent response . Additionally , the microarray transcriptional profile of JKD6229 suggested the stringent response was active in this strain , with upregulation of amino acid catabolism pathways , significant over expression of genes encoding oligopeptide transport proteins , up-regulation of genes associated with isoleucyl tRNA limitation ( including ilvB and ilvD , 4 to 6-fold increase; and leuABCD , up to 7-fold increase ) [41] , over expression of genes encoding extracellular proteases ( hrtA , splB , SAV1612 , SAV1613 ) , and up-regulation of the quorum sensing system agr . The transcriptional profile was very similar to the profile of S . aureus after in vitro induction of the stringent response by exposure to mupirocin , an agent that inhibits isoleucyl tRNA synthetase [22] . Structural and functional studies of RelA in Streptococcus mutans ( RelASm ) have shown that the enzyme can modulate intracellular levels of ( p ) ppGpp through a N-terminal hydrolase domain and C-terminal synthetase domain that act antagonistically in a ligand-dependant manner , either by degrading ( p ) ppGpp within the hydrolytic domain or converting GDP or GTP to ( p ) ppGpp within the synthetic domain [40] . Scanning mutagenesis of RelASm has defined regions of the enzyme that are critical for its hydrolytic function [40] . An alignment of the N-terminus of RelA from SCV JKD6229 ( RelASCV ) with RelASm shows that the F128Y mutation occurred in a region known to be critical for hydrolase function in S . mutans ( Fig . 4A ) . Thus , the alignment data and microarray results suggested that RelASCV might have impaired ( p ) ppGpp hydrolase function leading to an accumulation of ( p ) ppGpp and the persistent activation of the stringent response . To confirm that the RelA F128Y mutation was causing accumulation of ( p ) ppGpp , the relA allele from SCV JKD6229 was introduced into the parental strain JKD6210 , and ppGpp levels were measured using the fluorescent chemosensor PyDPA [42] . As predicted , a significant increase in ppGpp levels was demonstrated in JKD6229 ( clinical SCV ) and the mutant RelA F128Y mutant JKD6301 , compared to the parental strain JKD6210 ( Fig . 4B and C ) , suggesting that the F128Y mutation reduced the hydrolase activity of RelA . This is the first time an activated stringent response has been implicated as a mechanism of SCV formation in clinical S . aureus . The phenotypic features and impact on virulence of a persistently activated stringent response have not been previously investigated in S . aureus , because of the inability to generate a mutant strain without RelA hydrolase activity [19] . Therefore , the discovery of the clinical strain JKD6229 with the active stringent response , and creation of the relA mutant JKD6301 provided a unique opportunity to investigate the active stringent response in this organism . A number of phenotypic characteristics were investigated ( Fig . 5 and 6 ) . JKD6301 demonstrated a reduced growth rate in MH broth , and reduced colony size on HBA after 24 hours incubation indicating that the relA mutation contributed significantly to the growth defect of the clinical SCV strain JKD6229 ( Fig . 5A and B ) . An analysis of vancomycin susceptibility in JKD6301 using macromethod Etest [5] , and population analysis profile ( data not shown ) demonstrated no increase in vancomycin resistance in the mutant compared to JKD6210 ( Table 1 ) , indicating that although the stringent response has been linked to vancomycin tolerance in E . faecalis [17] , the relA mutation alone was not responsible for the reduced vancomycin susceptibility in JKD6229 . Susceptibility to other antimicrobials was also unchanged in JKD6301 compared to JKD6210 ( Table 1 ) . Previous studies have demonstrated enhanced invasion and persistence of some S . aureus SCV strains [6] . Therefore , the attachment , invasion , and persistence potential of the clinical isolate pair , and the relA mutant strain were tested ( Fig . 5C , D ) . Bacterial attachment to HeLa cells was decreased in JKD6229 and JKD6310 compared to the parental strain JKD6210 , while invasion was increased only in the SCV strain JKD6229 , indicating that the stringent response promotes factors that facilitate bacterial attachment but these changes alone are not sufficient to enhance invasion . In contrast to reported studies of electron transport deficient SCV strains , after 72 hours incubation there was no difference in intracellular persistence of SCV JKD6229 compared to the other strains . This observation might reflect the activated agr expression and increased toxin gene expression in JKD6229 ( Table 2 ) which is unusual for SCV S . aureus where reduced agr expression and alpha-toxin expression is thought to promote intracellular persistence without lethal effects on the host cell [7] , [31] , [43] . The larval stage of the Greater Wax Moth ( Galleria mellonella ) is an invertebrate model used to assess S . aureus virulence [44] . A comparison in this model of the virulence of parental strain JKD6210 with SCV JKD6229 and the relA mutant JKD6301 demonstrated a marked reduction in virulence in the SCV strain JKD6229 and also in the relA mutant ( Fig . 6 ) . The attenuation of SCV JKD6229 and JKD6310 was not due to their reduced growth rate compared to JKD6210 because the infected larvae had equivalent bacterial burden after 48 hours incubation . These experiments indicate that the increased persistence of SCV JKD6229 is associated with a reduced ‘virulence’ phenotype caused by the relA mutation .
In this study comparative and functional genomics has demonstrated the remarkable adaptive response of S . aureus to antimicrobial challenge during chronic infection , where four point mutations were sufficient to permit the strain to persist and resist multiple antibiotic therapies . This confirms the role of sequential point mutations in S . aureus adaptation during persistent infection , initially described by Mwangi et al [45] . We have uncovered a novel mechanism of growth inhibition contributing to SCV formation by S . aureus through mutation of relA and activation of the stringent response , and have described for the first time phenotypic features of an active stringent response in S . aureus , associated with profound global transcriptional changes . Analysis of the stringent response in S . aureus has been previously hampered by the inability to generate relA knock-out strain in this organism [21] , confirming the unique nature of the naturally occurring clinical isolate JKD6229 . Here , using the clinical strain JKD6229 and a mutant with a single base swap in relA ( JKD6301 ) , we demonstrate that an active stringent response in S . aureus leads to a reduced growth rate and features characteristic of SCV strains , as well as attenuated virulence in the G . mellonella invertebrate infection model . These data contrast with a recent report describing attenuated virulence of a S . aureus Rsh synthetase mutant in a murine infection model [20] , suggesting that both persistent activation or inactivation of the stringent response is associated with attenuated virulence in S . aureus . The specific impact of the relA mutation was clearly demonstrated by replicating the same single nucleotide change in relA from the SCV strain JKD6229 into the parental strain JKD6210 , and measuring the cellular levels of ppGpp using the fluorescent chemosensor PyDPA ( Fig . 4 ) . It is likely that the mutation detected in relA of JKD6229 partially impairs hydrolase function of the enzyme , leading to accumulation of the alarmones ( p ) ppGpp , but not cell death as has been described following complete loss of hydrolase function [19] . Despite the attenuated virulence of the strain in the invertebrate model , it was associated clinically with a persistent infection , suggesting that the mutation leading to permanent activation of the stringent response in this strain may have provided a survival advantage during chronic infection . Further analysis of the clinical impact of an active stringent response in S . aureus is now needed , with particular focus on the impact of this response on bacterial immune evasion , persistence and response to antimicrobial treatment . In addition to an activated stringent response the clinical strain JKD6229 harboured a number of mutations leading to the reduced antimicrobial susceptibility that also promoted persistent infection . Most intriguingly , we have described for the first time a codon insertion in the methyltransferase gene SACOL1230 ( RlmN ) that reduces linezolid susceptibility in clinical S . aureus . Early reports of linezolid resistance in S . aureus , and other Gram positive organisms , suggested that mutations in domain V of 23S rRNA are primarily responsible for resistance [25] , [26] , in particular the G2576T mutation , which continues to be detected in resistant strains from multiple S . aureus lineages [46] , [47] , [48] . Recently , mutations in ribosomal proteins L3 and L4 have also been associated with linezolid resistance in staphylococci [48] , [49] , and it has also become apparent that changes in ribosomal methylation can affect susceptibility to linezolid and other antimicrobials in S . aureus and other organisms [50] , [51] , [52] . The conserved methyltransefrase RlmN methylates 23S rRNA at position A2503 and a S . aureus strain with a knock-out of the gene encoding RlmN demonstrated a 2-fold increase in linezolid susceptibility [36] . Additionally , an acquired mechanism of linezolid resistance due to acquisition of cfr has recently been described [53] , [54] . The product of cfr hypermethylates 23S rRNA at position A2503 leading to the presence of not one , but two methyl groups which affects drug binding [50] . The impact of the codon insertion in SACOL1230 in our strain was confirmed by an allelic exchange experiment where the identical insertion was created in the linezolid susceptible parent strain JKD6210 . Although the change in linezolid MIC was not large , this is consistent with previous reports of changes in linezolid resistance in S . aureus due to acquisition of the methyltransferase cfr , where prolonged incubation was required to detect an increase in MIC using Etest [53] . We therefore propose that the CAA insertion in SACOL1230 enhanced ribosomal methylation in the clinical isolate JKD6229 leading to a reduction in linezolid susceptibility . The clinical impact of subtle changes in linezolid susceptibility of S . aureus have not been defined . However , similar to recent findings with reduced vancomycin susceptibility in this organism [5] , subtle reductions in susceptibility to an antibiotic may significantly impact the outcome of therapy , especially in patients with deep-seated infection as occurred in this case . Two additional mutations were detected in JKD6229 , as well as the loss of a ∼15 kb plasmid . The mutation in rpoB was clearly linked to the acquired rifampin resistance in JKD6229 , and has been previously described [34] . Likewise , the codon insertion in parC contributed to an increase in quinolone MIC of the organism [35] . The plasmid which was present in JKD6210 , but absent in JKD6229 ( pJKD6210 ) , shared high sequence homology to pUSA300-HOU-MS and encodes beta-lactam resistance , but did not contain the genes encoding cadmium resistance which are present on pUSA300-HOU-MS [33] . Over recent years there has been significant interest in the role of small colony variants of S . aureus in persisting and relapsing infections , and intracellular invasion and persistence is a frequently described feature of these strains [7] . While an understanding of the genetic determinants of SCV S . aureus has focussed on mutations in genes encoding hemin , menadione or thymidine biosynthesis [55] , [56] , [57] , our data clearly demonstrates the heterogeneic nature of this phenotype , with permanent activation of the bacterial stringent response also leading to a growth defect in S . aureus . Not surprisingly , the global transcriptional profile and phenotypic features of stringent response S . aureus demonstrate significant differences to those of the defined hemB and menD mutants , while the transcriptional profile of the stringent response SCV JKD6229 shared significant similarity to the profile of S . aureus after exposure to mupirocin [22] . For example , auxotrophs for hemin , menadione or thymidine have been shown to have reduced tricarboxylic acid cycle ( TCA ) metabolism leading to reduced electron transport [8] , [58] , [59] . The SCV strain JKD6229 was not an auxotroph for hemin or menadione and the genes for the TCA cycle were up-regulated in JKD6229 compared to JKD6210 . The SCV strain JKD6229 demonstrated increased intracellular invasion , however there was no increase in persistence compared to the parental strain ( Fig . 5 ) . Increased fibronectin-binding protein gene expression was found in JKD6229 , possibly contributing to increased cellular invasion , as has been previously described for the hemB mutant [11] . However , the absence of increased persistence is interesting . It has previously been demonstrated that reduced agr expression and alpha-toxin expression occurs in clinical SCV S . aureus , and in the hemB and medD mutants [31] , and it has been suggested that these changes favour intracellular persistence by avoiding lysis of the invaded cells [7] , [43] . In the SCV strain JKD6229 , increased expression of the agr locus was demonstrated; an unusual finding for an SCV strain , but this is also associated with the mupirocin induced stringent response in S . aureus [22] , and could potentially explain the failure to demonstrate increased intracellular persistence . An interesting finding of this study was the profound increase in expression of capsule biosynthesis genes , associated with a significant increase in capsule production in JKD6229 , demonstrated by capsule immunoblot ( Fig . 2B ) . A previous microarray transcriptional comparison of the hemB mutant to its parental strain also demonstrated an increase in capsule biosynthesis genes , however not to the same degree found in JKD6229 [8] . Given the association of staphylococcal capsule production with innate immunity evasion mechanisms and virulence in animal models [60] , this phenotypic change in the SCV strain JKD6229 also likely contributed to the clinical behaviour of the organism . The growth defect of SCV JKD6229 was incompletely replicated in the relA mutant strain JKD6301 , suggesting that additional factors contributed to the growth defect of the clinical strain . Although it appears unlikely that the other mutations detected in JKD6229 would lead to an additional growth defect , step-wise generation of each mutation in JKD6301 would be required to confirm this . Another unanswered question from this study is the mechanism of reduced vancomycin susceptibility in the strain JKD6229 , which demonstrated a heterogenous-vancomycin intermediate S . aureus ( hVISA ) phenotype based on the macromethod Etest result ( Table 1 ) [5] . Although mutations of relA in the Gram positive pathogen E . faecalis have been linked to vancomycin tolerance in that organism , there was no change in vancomycin susceptibility of the relA mutant JKD6301 compared to the parent strain JKD6210 demonstrating that an activated stringent response did not alter vancomycin susceptibility in this strain . Interestingly , the transcriptional profile of JKD6229 which was a hVISA , demonstrated some similarities to the transcriptional profiles of other hVISA strains , including enhanced capsule expression and reduced expression of the gene encoding protein A [30] . Finally , it is unlikely that other genomic differences were missed during our comparative genomics analysis . We performed a de novo assembly of the JKD6210 and JKD6229 sequences which revealed similar genome size ( approx 2 . 7 Mb ) , and 97 . 2% coverage of the N315 genome at a depth of ≥20 for both strains . Regions of N315 not covered in the JKD6210 and JKD6229 sequences were identical , indicating that these regions were unique to N315 . To reduce false positive SNP detection during comparative genomics analysis we set a threshold of a minimum depth of coverage at a SNP of ≥20 , and that the reads covering that position are all uniquely and unambiguously aligned to the reference genome . Although a small possibility exists that SNPs with very low read coverage or SNPs within repeat regions might be missed in out comparative genomics analysis , this is unlikely . In summary , using comparative and functional genomics to investigate the mechanisms of staphylococcal persistence in a patient with a very difficult-to-treat infection , we have detected a new mechanism of SCV S . aureus , and we have described for the first time the features of an activated stringent response in this organism . Also , a novel mechanism of reduced linezolid susceptibility has been described . Further work to determine the relationship between the stringent response and outcome of staphylococcal infections is required , as well as an exploration of the frequency of mutations in the staphylococcal gene encoding RlmN in patients treated with linezolid . This study highlights the limitations of current antimicrobial treatment strategies in patients with serious S . aureus infections .
This study was performed in accordance with Austin Health Human Research Ethics Committee guidelines . The de-identified clinical details described in this manuscript constitute a medical case report that did not require formal Human Ethics Committee approval or Informed Patient Consent . Bacterial strains and plasmids used in the study are listed in Table 1 . Staphylococcal strains were stored in glycerol broth at −80°C and subcultured twice onto Horse Blood Agar ( Oxoid ) for 48 h before being used for any experiment . Unless otherwise indicated all S . aureus isolates were grown in BHIB ( Oxoid ) , and E . coli grown in LB broth ( Oxoid ) . When required media was supplemented with the following antibiotics at the indicated concentrations: for E . coli , ampicillin 100 µg/mL; for S . aureus RN4220 , chloramphenicol 10 µg/mL; for S . aureus clinical isolates , chloramphenicol 25 µg/mL . For all DNA and RNA extractions , or for experimental inoculum preparations when the SCV strain JKD6229 was used , a subculture onto solid media was performed to confirm that the strain retained the SCV phenotype . For all phenotypic experiments growth conditions were carefully controlled , and all strains were grown to the same OD600 prior to analysis . Vancomycin MICs were determined by microbroth MIC according to CLSI criteria [61] . The detection of vancomycin hetero-resistance was performed by macromethod Etest for vancomycin and teicoplanin as well as vancomycin population analysis , as previously described [62] , [63] . A positive macromethod Etest result for hVISA was defined as vancomycin plus teicoplanin MIC≥8 µg/mL , or teicoplanin MIC≥12 µg/mL [5] . The MICs for daptomycin , gentamicin , linezolid , rifampicin and ciprofloxacin were performed by Etest ( AB Biodisk ) , according to manufacturer's instructions . For linezolid MIC testing a 2 McFarland saline suspension was used , because of previous problems in detecting linezolid resistant strains of S . aureus using standard Etest [53] . Other antibiotic susceptibilities were performed by agar dilution according to CLSI criteria [61] . Pulsed-field gel electrophoresis ( PFGE ) and multilocus sequence typing ( MLST ) were also performed as previously described [62] , [64] . Analysis of S . aureus growth rate was performed using 50 mL Muller Hinton II broth by inoculating 500 µL of an overnight broth culture . The optical density of the broth was read at 600 nm using a spectrometer . Assessment of colony size on solid media was performed by a blinded operator by measuring the size of 100 single colonies on Horse Blood Agar using callipers after 24 hours incubation . An analysis for hemin and menadione auxotrophism for the SCV strain JKD6229 was performed using chemically defined medium ( CDM ) [65] as previously described , and assessed after overnight incubation [55] . Microarray transcriptional analysis was performed with TIGR version 6 S . aureus arrays , as previously described [30] . For preparation of total RNA shaking flasks ( 50 mL BHI broth in 250 mL flasks ) were inoculated with 500 µL overnight BHI broth culture and incubated on a 225 rpm shaker at 37°C . Optical density was closely monitored , and one millilitre of sample was collected at exponential growth phase ( optical density at 600 nm of 0 . 5 ) and 0 . 5 mL RNA stabilization reagent ( RNA later , Qiagen ) was added and mixed immediately . The mixture was allowed to stand in room temperature for 10 minutes before total RNA was extracted using the RNeasy micro kit ( Qiagen ) . RNA extractions and hybridisations were performed on four different occasions , and the dye swapped with each biological replicate . The images were combined and quantified using ImaGene™ ver 5 . 1 ( Biodiscovery ) , and then imported into BASE and analyzed using Bioconductor and Limma [66] , [67] . The fold ratio of gene expression for the SCV strain ( JKD6229 ) relative to the parental MRSA ( JKD6210 ) was calculated . Using a modified t-test P-values were calculated and adjusted for multiple testing using false discovery rate ( FDR ) correction . A≥2-fold change with a P value less than 0 . 05 was considered significant and included in an analysis of differentially expressed genes . Microarray data has been submitted to GEO with accession number GSE20957 . The capsule typing ( CP5 and CP8 ) by multiplex PCR and quantification by immunoblot was performed as previously described [30] . Briefly , crude CP extracts were prepared using 10 mL of an overnight BHI broth culture adjusted to an OD600 of ∼0 . 5 . Serial two-fold dilutions of CP extracts were loaded onto a nitrocellulose membrane using a dot-blot apparatus . After blocking with 5% skim milk , the membrane was hybridised with CP5-specified rabbit antiserum , hybridised with sheep anti-rabbit IgG peroxidase conjugate ( Chemicon , Australia ) , and the image acquired and analysed using the LAS-3000 Luminescent Image Analysis System ( Fujifilm , Tokyo , Japan ) . Genome sequences for the parental strain JKD6210 and the clinical SCV strain JKD6229 were obtained from an Illumina Genome Analyzer II using 36 cycle paired-end chemistry . Reads were mapped to the reference strains S . aureus COL ( Genbank NC_002951 . 2 ) and S . aureus N315 ( Genbank NC_002745 . 2 ) using SHRiMP . SNP/DIPs were detected using Nesoni 0 . 14 , a software tool for analysing high-throughput DNA sequence data ( http://bioinformatics . net . au/software ) . Nesoni tallied the raw base counts at each mapped position in each of the reference strains , and then compared them using Fisher's Exact Test to find variable nucleotide positions in JKD6229 relative to JKD6210 . To exclude the possibility that mutations in JKD6229 may have occurred in regions not present in S . aureus COL or N315 , de novo assembly of JKD6210 and JKD6229 was performed using Velvet 0 . 7 . 55 [68] and the above read mapping and SNP/DIP detection was performed , using the resulting contigs as reciprocal reference sequences . For SNP detection a depth of coverage of ≥20 was required at the allele . The read data for JKD6210 and JKD6229 have been deposited in the NCBI Sequence Read Archive as part of Study accession number SRP001289 . Standard procedures were used for DNA manipulation , molecular techniques , PCR and sequencing [63] , [69] . The loci containing the relA nucleotide substitution and the ‘CAA’ insertion in rlmN ( from JKD6229 were amplified ( Table S2 ) , cloned with the vector pKOR1 and then generated in the parental strain JKD6210 as previously described [63] . The generation of the allele swap in JKD6210 using pJKD6318 was performed as previously described [63] , with some modifications . For the final selection step , 100 µL of a 48 hour BHI broth culture ( incubated at 30°C ) was inoculated into 10 mL BHI broth with 5% horse blood and 400 µg/mL anhydrotetracycline . The broth was incubated for 24 hours at 37°C on a shaker at 225 rpm . The culture was then diluted to 10−5 and 10 µL of a range of dilutions plated on several HBA and BHI agar plates . After 24 hours incubation at 37°C , single colonies were patched on BHI agar plates with and without chloramphenicol , and screened for the correct allele swap . The correct allele swaps were confirmed , and introduction of unwanted mutations excluded , by PCR amplification and Sanger sequencing of the whole relA and SACOL1230 locus from the mutants strains JKD6301 and JKD6300 , respectively . The presence of ppGpp was detected as previously published [42] , with some modifications . Briefly , S . aureus strains ( JKD6210 , JKD6229 and JKD6301 ) were grown in 25 mL of BHI broth at 37°C with vigorous shaking . Serine hydroxymate ( concentration 0 . 5 mg/mL ) was added to one flask of JKD6210 for 10 minutes to induce the stringent response and provide a positive control for the assay . Cells were harvested by centrifugation at OD600 of 0 . 5 . Following addition of 100% methanol , vigorous vortexing and centrifugation to pellet cellular debris , the supernatant containing ppGpp was collected and concentrated by freeze drying overnight . The dried extracts were then resuspended in 1 mM HEPES buffer , pH 7 . 4 containing 16% DMSO ( v/v ) and two-fold serial dilutions were performed in the same buffer . To each dilution , PyDPA to a final concentration of 25 µM was added . Fluorescence was observed using a hand held Wood's UV lamp ( 365 nm ) and a FLUOstar Omega microplate reader ( Ex 344 nm/Em 470 nm ) ( BMG Labtech , Offenburg , Germany ) . A HeLa cell line was used to test the invasive and intracellular persistence abilities of the clinical and mutant S . aureus strains . HeLa cells were seeded and grown in DMEM cell culture with 5% fetal bovin serum ( FBS ) in 24 well plates , and infected by the addition of approx 5×106 CFU of an overnight broth culture . The correct starting inoculum was confirmed by colony counts . After 1 hour incubation at 35°C in an incubator with 5% CO2 , the infected cells were washed with pre-warmed PBS 6 times to wash away the unattached bacteria and fresh DMEM with 5% FBS and supplemented with 400 µg/mL gentamicin and 40 µL/mL lysostaphin was added into each well and incubated for a further 72 hours . The infected HeLa cells were sampled before adding antibiotics to assess bacterial attachment/invasion , and at 1 hour post addition of antibiotics ( to assess invasion ) , and at 24 hours and 72 hours after adding antibiotics ( to assess intracellular persistence ) . The cell cultures were lysed by PBS supplemented with 0 . 05% saponin and plated on BHI agar plates . CFUs on plates were counted after 48 hr incubation at 37°C . The previously described invertebrate S . aureus infection model Galleria mellonella [44] was used to study the pathogenesis of clinical and mutant strains . G . mellonella in the final instrar larval stage were used in groups of 16 , and weighed to confirm no difference in size between groups . A HPLC syringe was used to inject 10 µL of bacterial suspension ( approx 0 . 5–1 . 0×106 CFU ) into each caterpillar via the last left proleg . Bacterial colony counts were performed to confirm consistency of inoculum and caterpillars injected with PBS and caterpillars that were not injected were included as controls . Each experiment was repeated on at least 4 different occasions . To determine the bacterial burden in infected caterpillars 48 hours after inoculation an assessment of the S . aureus CFU per caterpillar was performed on a subset of caterpillars . Non-parametric tests were used to analyse the results of colony size , bacterial attachment , invasion and persistence assays . Statistical analyses were performed using the two-tailed Mann-Whitney U test , with a p<0 . 05 set for statistical significance . Growth curves and stringent response activity were analysed using a one way analysis of variance ( ANOVA ) at each time point , and Kaplan Meier plots of G . mellonella killing results were analysed using the log rank test . All analyses were performed using Prism 4 for Macintosh ver 4 . 0 ( GraphPad Software Inc . , CA , USA ) .
|
The treatment of serious infections caused by Staphylococcus aureus is complicated by the development of antibiotic resistance , and in some cases the appearance of more persistent bacteria that have a reduced growth rate resulting in small colony variants ( SCV ) . Here we have shown using whole genome sequencing and gene replacement experiments on sequential S . aureus isolates obtained from a patient with a serious bloodstream infection , how S . aureus evolved into a multi-antibiotic resistant , persistent and almost untreatable SCV . Specifically we show that a minor DNA change in a S . aureus gene encoding an enzyme called RelA causes an accumulation of a small signalling molecule called ( p ) ppGpp , which in turn leads to persistent activation of the important bacterial stress response known as the stringent response . This is the first report of the involvement of the stringent response in S . aureus SCV formation and its association with persistent infection . Additionally , we have uncovered a novel mechanism of resistance to the new antimicrobial linezolid , caused by a mutation in a gene encoding a 23S rRNA methyltransferase . This study highlights the exquisite adaptability of this important pathogen in the face of antimicrobial treatment .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"infectious",
"diseases/nosocomial",
"and",
"healthcare-associated",
"infections",
"genetics",
"and",
"genomics/comparative",
"genomics",
"genetics",
"and",
"genomics/functional",
"genomics",
"microbiology/microbial",
"evolution",
"and",
"genomics",
"infectious",
"diseases/bacterial",
"infections",
"microbiology/cellular",
"microbiology",
"and",
"pathogenesis",
"microbiology/medical",
"microbiology",
"infectious",
"diseases/antimicrobials",
"and",
"drug",
"resistance"
] |
2010
|
Two Novel Point Mutations in Clinical Staphylococcus aureus Reduce Linezolid Susceptibility and Switch on the Stringent Response to Promote Persistent Infection
|
Understanding phylogenetic relationships within species complexes of disease vectors is crucial for identifying genomic changes associated with the evolution of epidemiologically important traits . However , the high degree of genetic similarity among sibling species confounds the ability to determine phylogenetic relationships using molecular markers . The goal of this study was to infer the ancestral–descendant relationships among malaria vectors and nonvectors of the Anopheles gambiae species complex by analyzing breakpoints of fixed chromosomal inversions in ingroup and several outgroup species . We identified genes at breakpoints of fixed overlapping chromosomal inversions 2Ro and 2Rp of An . merus using fluorescence in situ hybridization , a whole-genome mate-paired sequencing , and clone sequencing . We also mapped breakpoints of a chromosomal inversion 2La ( common to An . merus , An . gambiae , and An . arabiensis ) in outgroup species using a bioinformatics approach . We demonstrated that the “standard” 2R+p arrangement and “inverted” 2Ro and 2La arrangements are present in outgroup species Anopheles stephensi , Aedes aegypti , and Culex quinquefasciatus . The data indicate that the ancestral species of the An . gambiae complex had the 2Ro , 2R+p , and 2La chromosomal arrangements . The “inverted” 2Ro arrangement uniquely characterizes a malaria vector An . merus as the basal species in the complex . The rooted chromosomal phylogeny implies that An . merus acquired the 2Rp inversion and that its sister species An . gambiae acquired the 2R+o inversion from the ancestral species . The karyotype of nonvectors An . quadriannulatus A and B was derived from the karyotype of the major malaria vector An . gambiae . We conclude that the ability to effectively transmit human malaria had originated repeatedly in the complex . Our findings also suggest that saltwater tolerance originated first in An . merus and then independently in An . melas . The new chromosomal phylogeny will facilitate identifying the association of evolutionary genomic changes with epidemiologically important phenotypes .
Complexes of sibling species are common among arthropod disease vectors [1]–[3] . Members of such complexes are morphologically similar and partially reproductively isolated from each other . The Anopheles gambiae complex consists of seven African malaria mosquito sibling species . Anopheles gambiae and An . arabiensis , the two major vectors of malaria in Africa , are both anthropophilic and can breed in temporal freshwater pools . Anopheles gambiae occupies more humid areas , while An . arabiensis dominates in arid savannas and steppes . Anopheles merus and An . melas breed in saltwater , and the habitat of An . bwambae is restricted to mineral water breeding sites . These three species are relatively minor malaria vectors mainly due to narrow geographic distributions [4] . Anopheles quadriannulatus A and An . quadriannulatus B are freshwater breeders and , although to various degrees susceptible to Plasmodium infections , are not natural vectors of malaria mainly due to zoophilic behavior [5]–[7] . Inferring the evolutionary history of the An . gambiae complex could be crucial for identifying specific genomic changes associated with the human blood choice , breeding site preference , and variations in vector competence . However , the high degree of genetic similarity , caused by the ancestral polymorphism and introgression , complicates the use of molecular markers for the reconstruction of a sibling species phylogeny [8]–[10] . Even the most recent genome-wide transcriptome-based phylogeny reconstruction of multiple Anophelinae species could not unambiguously resolve the relationships among An . gambiae , An . arabiensis , and An . quadriannulatus [11] . An alternative approach to inferring the phylogenetic relationships among species is to analyze the distribution of fixed overlapping inversions [4] , [7] , [12] . This approach is based on the fact that species-specific inversions do not introgress [13] and that inversions are predominantly monophyletic , despite rare occurrences of breakpoint reuse [14] . In addition , chromosomal inversions are more rare events and more consistent characters as compared with nucleotide substitutions [12] , [15] . Phylogenies based on inversion data are highly congruent with phylogenies based on DNA sequence data and are shown to be more information rich than are nucleotide data [15] . Members of the An . gambiae complex carry 10 fixed inversions that can be used for a phylogeny reconstruction [7] . Five fixed inversions are present on the X chromosome , three inversions are found on the 2R arm , and one is found on each of the 2L and 3L arms ( Figure S1 ) [7] . The only nonvectors in the complex , Anopheles quadriannulatus A and B , had been traditionally considered the closest species to the ancestral lineage because they have a large number of hosts , feed on animal blood , tolerate temperate climates , exhibit disjunctive distribution , and possess a “standard” karyotype [4] , [7] , [16] , [17] . More recently , the An . arabiensis karyotype had been assumed ancestral because it has the fixed 2La inversion , which was also found in two outgroup species from the Middle Eastern An . subpictus complex [18] . Both chromosomal phylogenies assumed the most recent speciation of An . merus and an independent origin of the cytologically identical 2La′ inversion in this species [19] . A phylogenetic status of an inversion can be determined more precisely when breakpoints are identified and gene orders across breakpoints are compared between ingroup and multiple outgroup species . The genes found across inversion breakpoints in ingroup and outgroup species are expected to be in their ancestral order [12] . For example , the molecular analysis of the 2La inversion breakpoints and physical mapping of the sequences adjacent to the breakpoints in outgroup species identified the shared 2La inversion in An . gambiae , An . merus , and An . arabiensis and determined the ancestral state of the 2La arrangement [20]–[22] . Based on the X chromosome fixed inversions , three species clades can be identified in the complex: ( i ) An . bwambae , An . melas , and An . quadriannulatus A and B ( X+ ) , ( ii ) An . arabiensis ( Xbcd ) , and ( iii ) An . merus and An . gambiae ( Xag ) ( Figure 1 ) . The An . gambiae–An . merus and An . bwambae–An . melas sister taxa relationships have been supported by independent phylogenetic analyses of nuclear genes and mitochondrial DNA sequences [9] , [10] , [23] . Each clade has unique fixed inversions that can be used to unambiguously determine its phylogenetic status if compared to gene arrangements in outgroup species: X+ , 2Rm , 3La in the An . bwambae–An . melas–An . quadriannulatus clade , Xbcd in An . arabiensis , and Xag , 2Ro , 2Rp in the An . gambiae–An . merus clade . However , to efficiently pursue this research was not possible until recently when genome sequences of several outgroup mosquito species became available , including An . stephensi ( series Neocellia , subgenus Cellia , subfamily Anophelinae ) ( this paper ) , and Aedes aegypti and Culex quinquefasciatus ( both from subfamily Culicinae ) [24] , [25] . In this study , we identified genes at the breakpoints of fixed overlapping inversions 2Ro and 2Rp of An . merus and homologous sequences in An . stephensi , Ae . aegypti , and C . quinquefasciatus . We demonstrated that the “inverted” 2Ro and the “standard” 2R+p arrangements are ancestral in the complex . In addition , we found that the “inverted” 2La arrangement is present in evolutionary distant Culicinae species and , therefore , is ancestral . The inversion data support the basal position of the An . gambiae–An . merus clade and the terminal positions of the An . arabiensis and An . melas lineages . This rooted chromosomal phylogeny could be a means to examine specific genomic changes associated with evolution of traits relevant to vectorial capacity .
We mapped multiple An . gambiae DNA probes derived from the cytological breakpoints to the chromosomes of An . merus by FISH . Anopheles gambiae BAC clone 141A14 that spans the proximal 2R+o breakpoint was identified by comparative mapping with An . merus in our previous study [21] . FISH of the BAC clone to An . merus chromosomes produced two separate signals on 2R indicating an inversion . Reiteration of this procedure with PCR fragments derived from the BAC clone allowed us to localize the breakpoint region within the BAC between genes AGAP002933 and AGAP002935 . Further comparative mapping with An . merus demonstrated that the distal 2R+o breakpoint in An . gambiae is located between genes AGAP001759 and AGAP001762 ( Figure S2 ) . We also performed FISH with polytene chromosomes of An . merus using multiple probes located near the 2R+p cytological breakpoints of An . gambiae . The proximal 2R+p breakpoint was found between genes AGAP003327 and AGAP003328 , and the distal 2R+p breakpoint was localized between AGAP001983 and AGAP001984 in An . gambiae . These gene pairs were neighboring in the genome of An . gambiae , but they were mapped in separate locations in An . merus ( Figure S3 ) . To determine gene arrangements in an outgroup species , we mapped genes at the 2R+o and 2R+p breakpoints to polytene chromosomes of An . stephensi ( Figure S4 and Figure S5 ) . The FISH results showed that the “inverted” 2Ro and “standard” 2R+p arrangements are present in the outgroup species An . stephensi ( Figure 2 ) . We performed mate-paired sequencing of the An . merus genome and mapped the read pairs to the An . gambiae AgamP3 genome assembly , which has all “standard” arrangements [26] , [27] . Mate-paired sequencing is the methodology that enables the generation of libraries with inserts from 2 to 5 kb in size . The 2 kb , 3 kb , and 5 kb DNA fragments were circularized , fragmented , purified , end-repaired , and ligated to Illumina paired-end sequencing adapters . The final libraries consisted of short fragments made up of two DNA segments that were originally separated by several kilobases . These genomic inserts were paired-end sequenced using an Illumina approach . Paired-read sequences that map far apart in the same orientation delineate inversions [28] . We executed a BLASTN search to find read pairs mapped to the putative breakpoint regions in the same orientation on chromosome 2 ( Figure 3 and Table S1 ) . Alignment of the read pairs to the genome of An . gambiae identified the 2Ro breakpoints at coordinates ∼9 . 48 Mb and ∼29 . 84 Mb . We also identified the 2La breakpoints at coordinates ∼20 . 52 Mb and ∼42 . 16 Mb , which confirmed a previous study and , thus , validated the approach [20] . However , the BLASTN search did not find the paired-read sequences that map at the opposite 2Rp breakpoints in the same orientation . This approach could not detect breakpoint regions longer than 5 kb . The 2Rp breakpoint regions in An . merus likely have larger sizes caused by accumulation of repetitive sequences . We also used the Bowtie program [29] to confirm the genomics positions of the 2Ro breakpoints ( Table S2 ) . Both BLASTN and Bowtie results supported the position of the proximal 2Ro breakpoint to the region between genes AGAP001762 and AGAP002935 , and they refined the position of the distal 2Ro breakpoint to the region between AGAP001760 and AGAP002933 . The genes adjacent to the 2Ro breakpoint were used as probes to screen the genomic phage library of An . merus . Positive An . merus phage clones were confirmed to span inversion breakpoints by FISH to polytene chromosomes of An . gambiae , An . merus , and An . stephensi . For example , hybridization of Phage 6D produced only one signal in the proximal 2Ro breakpoint in An . merus but two signals at both 2Ro breakpoints in An . gambiae ( Figure S6 ) . Phage 6D hybridized to only one locus in An . stephensi , confirming the 2Ro arrangement in this species . Confirmed phage clones were sequenced , and the exact breakpoint regions were identified by aligning the An . merus sequences and An . gambiae AgamP3 , AgamM1 , and AgamS1 genome assemblies available at VectorBase [26] , [30] , [31] . Thus , distal and proximal breakpoints were identified on polytene chromosome map [7] and in the genome assembly of An . gambiae ( Figure 4 ) . In the AgamP3 assembly , the distal and proximal breakpoint regions span coordinates 9 , 485 , 167–9 , 486 , 712 , and 29 , 838 , 366–29 , 839 , 163 , respectively . The 2Ro breakpoint regions were 2 . 6 and 5 . 9 times smaller in An . merus as compared with the 2R+o breakpoint regions in An . gambiae due to accumulation of transposable elements ( TEs ) in the latter species . The presence of TEs is a common signature of inversion breakpoints , as TEs usually mark breakpoints of derived arrangements [20] , [32] . Five various DNA transposons were found at the distal 2R+o breakpoint , and one novel miniature inverted-repeat TE ( MITE ) , Aga_m3bp_Ele1 , was identified at the proximal 2R+o breakpoint in An . gambiae ( Figure 4 ) . Smaller sizes of the breakpoint regions and the lack of TEs at the breakpoints of An . merus strongly suggest the ancestral state of the 2Ro arrangement . We determined gene orders at the breakpoints of the An . merus-specific fixed overlapping inversions 2Ro and 2Rp in several outgroup species , including An . stephensi , Ae . aegypti , and C . quinquefasciatus . The genes adjacent to the 2Ro and 2Rp breakpoint were used as probes to screen the genomic BAC library of the outgroup species An . stephensi . Sequences homologous to genes from the distal 2Ro breakpoint were found in the BAC clone AST044F8 of An . stephensi . In addition , we performed sequencing of the An . stephensi genome using 454 and Illumina platforms . Sequences homologous to genes from the proximal 2Ro breakpoint were identified in scaffold 03514 of the An . stephensi genome . We also detected homologous sequences in the genome assemblies of Ae . aegypti and C . quinquefasciatus available at VectorBase [27] . The analysis demonstrated that all studied outgroup species had the gene arrangement identical to that of An . merus confirming the ancestral state of the 2Ro inversion ( Figure 5 ) . The An . stephensi sequences , which correspond to the 2Ro breakpoints , had sizes more similar to those in An . merus than in An . gambiae , and they did not display any TEs or repetitive elements , further supporting the 2Ro ancestral state . However , we found TEs in sequences corresponding to one of the 2Ro breakpoints in Ae . aegypti . Incidentally , the areas between the homologous breakpoint-flanking genes were 12 , 055 bp in Culex and 31 , 352 bp in Aedes , and this probably reflects the repeat-rich nature of the Culicinae genomes . The demonstrated conservation of gene orders between Anophelinae and Culicinae species is remarkable given the ∼145–200 million years of divergence time between these two lineages [33] . Approximate genomic positions of the 2R+p breakpoints were determined between AGAP001983 and AGAP001984 and between AGAP003327 and AGAP003328 by physical mapping of An . merus chromosomes ( Figure 2 ) . Using these genes as probes , we obtained a positive Phage 3B of An . merus that was mapped to the proximal 2Rp breakpoint in An . merus ( Figure S6 ) . Sequencing and molecular analyses of Phage 3B revealed the presence of AGAP001983 and AGAP013533 in this clone indicating that the actual distal breakpoint is located between AGAP013533 and AGAP001984 in An . gambiae . However , the available Phage 3B sequence ended at gene AGAP013533 and , thus , did not encompass the actual breakpoint sequence in An . merus . We performed the comparative analysis of gene orders at the 2Rp breakpoints in three outgroup species , An . stephensi , C . quinquefasciatus , and Ae . aegypti . The results demonstrated the common organization of the distal 2R+p breakpoint in An . gambiae and outgroup species , indicating that this arrangement is ancestral ( Figure 6 ) . Interestingly , a gene similar to AGAP013533 was absent , but genes similar to AGAP001983 and AGAP001984 were present in supercontig 3 . 153 of C . quinquefasciatus . Genes similar to AGAP003327 and AGAP003328 were found in different scaffolds and supercontigs of the outgroup species . This pattern was expected because AGAP003327 and AGAP003328 were mapped to neighboring but different subdivisions on the An . stephensi chromosome map ( Figure 2 ) . Therefore , it is possible that an additional inversion separated these two genes in the An . stephensi lineage . The highly fragmented nature of the C . quinquefasciatus and Ae . aegypti genome assemblies could also explain the observed pattern . No TEs were found in the breakpoint regions of An . stephensi and C . quinquefasciatus . However , multiple TEs were found in the intergenic regions of An . gambiae and Ae . aegypti ( Figure 6 ) . Using sequencing and cytogenetic approaches , the common 2La arrangement was previously found in An . gambiae , An . merus , and An . arabiensis [4] , [20] , as well as in several outgroup species , including An . subpictus [18] , An . nili , and An . stephensi [22] . Here , we used sequences available for breakpoints of the 2La inversion [20] to execute BLAST searches against genomes of more distantly related outgroup species C . quinquefasciatus and Ae . aegypti . BLAST results of genes adjacent to the 2La proximal breakpoint , AGAP007068 and AGAP005778 , identified orthologs CPIJ004936 and CPIJ004938 in the Culex genome as well as orthologs AAEL001778 and AAEL001757 in the Aedes genome . These genes were found within supercontig 3 . 77 in C . quinquefasciatus and within supercontig 1 . 42 in Ae . aegypti . Similarly , BLAST results of genes neighboring with the 2La proximal breakpoint , AGAP007069 and AGAP005780 , identified homologous genes CPIJ005693 and CPIJ005692 in the Culex genome ( supercontig 3 . 99 ) as well as AAEL011139 and AAEL011140 in the Aedes genome ( supercontig 1 . 543 ) . The obtained data confirmed the identical gene arrangement in distant outgroup species and the ancestry of the 2La inversion . Physical chromosome mapping and bioinformatic analyses identified the 2Ro and 2R+p arrangements in several outgroup species indicating that these arrangements are ancestral ( Figure 5 and Figure 6 ) . Because these two inversions overlap , only certain evolutionary trajectories and inversion combinations are possible ( Figure 2 ) . Specifically , the 2Rop–2Ro+p–2R+op order of inversion events is possible , while the 2Rop–2R+op–2R+op evolutionary sequence is not possible , regardless of the direction . Identification of 2Ro and 2R+p as the ancestral arrangements agrees well with this argument . We have also examined three different scenarios in reconstructing chromosomal phylogeny based on the established ancestry of 2Ro , 2R+p , and 2La and on the alternative hypothetical ancestries of X chromosomal arrangements ( X+ , Xag , or Xbcd ) using the Multiple Genome Rearrangements ( MGR ) program [34] . Three different X chromosome arrangements ( X+ , Xag , and Xbcd ) in an outgroup species were examined ( Figure S7 ) . The MGR program calculated the phylogenetic distances among species related to the ancestry of the X chromosome arrangement . Three hypothetical trees were obtained and used for interpretation of phylogenetic relationship and inversion reuse in the complex . Of the three scenarios , only the phylogeny based on the ancestry of 2Ro , 2R+p , 2La , and Xag had all inversions originating only once in the evolution of the An . gambiae complex . The other scenarios ( with X+ and Xbcd being ancestral ) had multiple origins of one of the inversions implying that they are less parsimonious ( Figure S7 ) . Because Xag uniquely characterize the An . gambiae–An . merus clade , these two species have the least chromosomal differences from the ancestral species of the complex as compared with other members ( Figure 7 ) . The ancestry of Xag can be tested by mapping of the X chromosome genome sequences from several species of the An . gambiae complex , which soon will be available [10] . Importantly , the new phylogeny is in complete agreement with the previous discoveries of 2La being the ancestral arrangement [18] , [20] . Moreover , this is the first phylogeny based on knowledge about the status of a species-specific inversion ( 2Ro of An . merus ) . Therefore , the future data on the ancestry of the X chromosome arrangement are expected to support the new phylogeny . Speciation in the An . gambiae complex has been accompanied by fixation of chromosomal inversions , except for speciation within the An . quadriannulatus lineage [7] , [35] . Therefore , the chromosomal phylogeny likely reflects the species' evolutionary history . For a long time , the An . quadriannulatus lineage had been traditionally considered ancestral [4] , [7] , [16] , [17] ( Figure 8A ) . This evolutionary history was reconstructed from an unrooted phylogeny without any knowledge about chromosomal arrangements in outgroup species . Later , the An . arabiensis lineage had been assumed basal because it has the fixed ancestral 2La inversion and based on knowledge about biogeography and ecology of An . arabiensis [18] ( Figure 8B ) . In these two scenarios , saltwater species An . merus and An . melas had been assumed the most recently originated members in the complex . However , the ancestry and the unique origin of the 2La inversion [20] imply that An . arabiensis , An . gambiae , or An . merus could be the closest to the ancestral species . The new chromosomal phylogeny led us to the substantial revision of the evolutionary history of the An . gambiae complex ( Figure 8C ) . Accordingly , the ancestral species with 2Ro , 2R+p , and 2La arrangements might have arisen in East Africa where An . merus and An . gambiae are present in sympatry . The ancestral species may have been polymorphic for the 2Rp and 2R+o inversions and one lineage or population gave rise to An . merus with the 2Rp inversion while the other gave rise to the sister species An . gambiae containing the 2R+o inversion . Otherwise one would have to postulate that An . gambiae and An . merus arose from independent ancestors . At some point in evolutionary history , An . gambiae acquired polymorphic 2La/+ inversion and entered forested regions in central Africa . Later , An . gambiae acquired multiple polymorphic inversions on 2R , which allowed this species to spread to the arid areas of West Africa [4] . A hypothetical karyotype might have originated from the An . gambiae chromosomal arrangements by acquiring X+ag inversions . This karyotype in turn gave rise to the An . arabiensis chromosomes by generating the Xbcd inversions and fixing 2La and to the An . quadriannulatus karyotype by fixing the 2L+a arrangement . The 3La inversion in An . bwambae originated from the An . quadriannulatus karyotype , followed by the origin of the 2Rm inversion in An . melas . The two major malaria vectors An . arabiensis and An . gambiae are sympatric species in most of their distribution range , allowing for introgressive hybridization between them . Available data support the hypothesis of introgression of the 2La arrangement from An . arabiensis into An . gambiae [9] , [36] , [37] . According to the new chromosomal phylogeny , introgression of 2La has been happening from the more derived karyotype of An . arabiensis to the more ancestral karyotype of An . gambiae . Therefore , the 2La arrangement in isolated An . gambiae populations must retain alleles that are more distantly related to alleles of the 2La arrangement in An . arabiensis . This hypothesis can be tested by the genomic analysis of An . gambiae island populations that do not have a history of hybridization with An . arabiensis . Because the 2La inversion in An . gambiae mainland populations has been associated with a tolerance to aridity and slightly reduced susceptibility to Plasmodium falciparum [4] , [38] , [39] , the expected differences between the “original” and “introgressed” 2La arrangements could impact our understanding of a role of the inversion polymorphism in mosquito adaptation and malaria transmission . The results of this study indicate that An . merus is closely related to an ancestral species from which the An . gambiae complex arose . Anopheles merus is a minor vector of human malaria in African mainland . A role of An . merus in malaria transmission in Madagascar has also been documented [40] . Based on the unique origin of fixed inversions and X-linked sequences , An . merus and An . gambiae are considered sister taxa [9] , [10] . Therefore , according to the new chromosomal phylogeny , these two species possess the most “primitive” karyotypes in the complex . Our data suggest that the major malaria vector in Africa An . gambiae could be more closely related to the ancestral species than was previously assumed . Unexpectedly , we found that the karyotype of nonvectors An . quadriannulatus A and B was derived from the karyotype of An . gambiae ( Figure 7 and Figure 8 ) . Anopheles quadriannulatus is not involved in malaria transmission in nature due to its strong preference for feeding on animals [7] . Anopheles melas has the most recently formed karyotype and is a malaria vector in West Africa [41] , [42] . The new chromosomal strongly suggests that vectorial capacity evolved repeatedly in the An . gambiae complex . Increased anthropophily could not have evolved in An . gambiae and An . arabiensis before humans originated and evolved to high enough densities . Therefore , the ability to effectively transmit human malaria must be a relatively recent trait in the complex . If An . quadriannulatus were the ancestral species , as it was assumed earlier [4] , [7] , then vectorial capacity could have originated only once when all other members split from the An . quadriannulatus lineage ( Figure 8A ) . However , if the An . gambiae–An . merus clade is ancestral , as we demonstrated here , then vectorial capacity must have arisen independently in different lineages after the species were diversified . The available data cannot clearly delineate between the loss of vectorial capacity in An . quadriannultus and its subsequent reappearance in An . bwambae and An . melas with a possible alternative that vectorial capacity in present day An . quadriannulatus was only lost after An . bwambae and An . melas split from the An . quadriannulatus lineage . Depending on when the phenotypic change occurred ( before or after An . bwambae/An . melas split from the An . quadriannulatus lineage ) different scenarios are possible . However , even if a zoophilic behavior was acquired by An . quadriannulatus after the split from An . bwambae and An . melas , one still has to assume repeated origin of vectorial capacity . In this case , it originated independently in An . gambiae , An . merus , An . arabiensis , and the lineage that led to An . quadriannulatus/An . bwambae/An . melas . This alteration of the phylogeny of the An . gambiae species complex will likely have direct impact on studies aimed at understanding the genetic basis of traits important to vectorial capacity . The chromosomal phylogeny also supports the idea of multiple origins of similar ecological adaptations in the complex . An early cytogenetic and ecological study postulated the repeated evolution of saltwater tolerance in the complex [4] . Anopheles melas and An . merus breed in saltwater pools in western and eastern Africa , respectively . Our finding revealed that the physiological adaptation to breeding in saltwater originated first in An . merus and then independently in An . melas . Because of the high degrees of genetic similarities among sibling species , attempts to use molecular markers to reconstruct phylogenetic trees often fail [10] . Our study provides the methodology for rooting chromosomal phylogenies of sibling species complexes , which are common among disease vectors , including blackflies , sandflies , and mosquitoes [1]–[3] . The robustness of this methodology is supported by the agreement between the two alternative approaches to breakpoint mapping ( cytogenetics and sequencing ) and by the consensus among the three inversions in the phylogenic analysis ( 2Ro , 2Rp , and 2La ) . As we demonstrated , inversion breakpoints can be physically mapped on polytene chromosomes by FISH and identified within genomes by mate-pair and clone sequencing . Importantly , the increasing availability of sequenced and assembled genomes provides an opportunity for identification of gene orders in multiple outgroup species for rooting chromosomal phylogenies . The high genetic similarity among the species of the An . gambiae complex suggests their recent evolution [10] , [18] . The identified chromosomal relationships among the species demonstrate rapid gains and losses of traits related to vectorial capacity and ecological adaptations . This study reinforces the previous observations that vectors often do not cluster phylogenetically with nonvectors [1] , [10] . The genome sequences for several members of the An . gambiae complex are soon to be released [10] , and the new chromosomal phylogeny will provide the basis for proposing hypotheses about the evolution of epidemiologically important phenotypes . An intriguing question is whether or not evolution of independently originated traits , such as anthropophily and salt tolerance , is determined by changes of the same genomic loci in different species . In addition , the revised phylogeny will affect the interpretation of results from population genetics studies such as shared genetic variation and the detection of signatures of selection . Specifically , variations shared with An . merus but not with An . quadriannulatus would be interpreted now as ancestral . Knowledge about how evolutionary changes related to ecological and behavioral adaptation and how susceptibility to a pathogen in arthropod vectors had happened in the past may inform us about the likelihood that similar changes will occur in the future .
The OPHASNI strain of An . merus , the Indian wild-type laboratory strain of An . stephensi , and the SUA2La strain of An . gambiae were used for chromosome preparation . To obtain the polytene chromosomes , ovaries were dissected from half-gravid females and kept in Carnoy's fixative solution ( 3 ethanol: 1 glacial acetic acid ) in room temperature overnight . Follicles of ovaries were separated in 50% propionic acid and were squashed under a cover slip . Slides with good chromosomal preparations were dipped in liquid nitrogen . Then cover slips were removed , and slides were dehydrated in a series of 50% , 70% , 90% , and 100% ethanol . Multiple An . gambiae DNA probes derived from the cytological breakpoints of An . gambiae were physically mapped to the chromosomes of An . merus and An . stephensi . DNA probes obtained from PCR products were labeled by the Random Primers DNA Labeling System ( Invitrogen Corporation , Carlsband , CA ) , and phage clones were labeled by the Nick Translation Kit ( Amersham , Bioscience , Little Chalfont Buckinghamshire , UK ) . DNA probes were hybridized to chromosome slides overnight at 39°C . Then chromosomes were washed with 1× SSC at 39°C and room temperature . Chromosomes were stained with 1 mM YOYO-1 iodide ( 491/509 ) solution in DMSO ( Invitrogen Corporation , Carlsbad , CA , USA ) and were mounted in DABCO ( Invitrogen Corporation , Carlsbad , CA , USA ) . Images were taken by a laser scanning microscope and by the fluorescent microscope . Location of the signals was determined by using a standard photomap of An . stephensi [43] and An . gambiae [44] . Mate-paired whole genome sequencing was done on genomic DNA isolated from five adult males and females of An . merus . Genomic DNA of An . merus was isolated using the Blood and Cell Culture DNA Mini Kit ( Qiagen Science , Germantown , MD , USA ) . Three libraries of 2 kb , 3 kb , and 5 kb were obtained . These libraries were used for 36 bp paired-end sequencing utilizing the Illumina Genome Analyzer IIx at Ambry Genetics Corporation ( Aliso Viejo , CA , USA ) . The 16× coverage genome assembly for An . stephensi was obtained by sequencing genomic DNA isolated from Indian wild-type laboratory strain . The sequencing was done using Illumina and 454 platforms at the Core Laboratory Facility of the Virginia Bioinformatics Institute , Virginia Tech . Screening the An . merus Lambda DASH II phage library with genes adjacent to standard 2R+o and 2R+p was performed . To prepare probes for screening phage and BAC libraries , genomic DNA of An . gambiae was prepared using the Qiagen DNeasy Blood and Tissue Kit ( Qiagen Science , Germantown , MD , USA ) . Primers were designed for genes adjacent to breakpoints using the Primer3 program [45] . PCR conditions were the following: 95°C for 4 min; 35 cycles of 94°C for 30 s , 55°C for 30 s , and 72°C for 30 s; and 72°C for 5 min . All PCR products were purified from the agarose gel using GENECLEAN III kit ( MP Biomedicals , Solon , OH , USA ) . DNA probes were labeled based on random primer reaction with DIG-11-dUTP from DIG DNA Labeling Kit ( Roche , Indianapolis , IN , USA ) . Anopheles merus Lambda DASH II phage library and An . stephensi BAC library ( Amplicon Express , Pullman , WA , USA ) were screened . Library screening was performed using the following kits and reagents ( Roche Applied Science , Indianapolis , IN ) according to protocols supplied by the manufacturer: Nylon Membranes for Colony and Plaque Hybridization , DIG easy Hyb , DIG Wash and Block Buffer Set , Anti-Dioxigenin-AP , and CDP Star ready to use . Positive phages were isolated with Qiagen Lambda midi Kit ( Qiagen Science , Germantown , MD , USA ) , and positive BAC clones were isolated using the Qiagen Large Construct Kit ( Qiagen Science , Germantown , MD , USA ) . Primers 1760RCL ( 5′AGCAACAGGGACGATTTGTT3′ ) and 2933RCL ( 5′CTCGCTTTGGTTTGTGCTTT3′ ) were designed based on AGAP001760 and AGAP002933 sequences , and they were used to obtain the distal 2Ro breakpoint from Phage 7D DNA . The PCR conditions with Platinum PfX DNA polymerase ( Invitrogen , Carlsbad , CA , USA ) were: 94°C for 2 min; 35 cycles of 94°C for 15 s , 55°C for 30 s , and 68°C for 2 min; and 68°C for 10 min . Sanger sequencing of Phage 7D was performed using an ABI machine at the Core Laboratory Facility of the Virginia Bioinformatics Institute , Virginia Tech . Other positive phage and BAC clones were completely sequenced by the paired-end approach using an Illumina platform . Libraries of phages and BAC clones were made using Multiplex Sample Preparation Oligonucleotide Kit and Paired End DNA Sample Prep Kit ( Illumina , Inc . , San Diego , CA ) . Paired-end sequencing was performed on the Illumina Genome Analyzer IIx using 36 bp paired-end processing at Ambry Genetics Corporation ( Aliso Viejo , CA , USA ) . Phage clone of An . merus , BAC clone of An . stephensi , and genome sequences of An . merus , An . stephensi , An . gambiae , C . quinquefasciatus , and Ae . aegypti were analyzed with BLASTN , TBLASTX , and BLAST2 using the laboratory server and the Geneious 5 . 1 . 5 software ( www . geneious . com ) , a bioinformatics desktop software package produced by Biomatters Ltd . ( www . biomatters . com ) . Identification of the accurate breakpoint was performed by aligning the An . merus sequences and An . gambiae AgamP3 , AgamM1 , and AgamS1 genome assemblies available at VectorBase [27] . The DNA transposons and retroelements were analyzed by using the RepeatMasker program [46] and by comparing to Repbase [47] and TEfam ( http://tefam . biochem . vt . edu/tefam/ ) databases . To characterize novel TEs in the breakpoint , each candidate sequence was used as a query to identify repetitive copies in the genome using BLASTN searches . These copies , plus 1000 bp flanking sequences , were aligned using CLUSTAL 2 . 1 to define the 5′ and 3′ boundaries . Using this approach , a novel MITE was discovered in the An . gambiae breakpoint . According to the TEfam naming convention , this MITE was named Aga_m3bp_Ele1 because it was associated with a 3 bp target site duplication . All sequence data have been deposited at the National Center for Biotechnology Information short read archive ( www . ncbi . nlm . nih . gov/Traces/sra/sra . cgi ) as study no . SRP009814 of submission no . SRA047623 and to the GenBank database ( http://www . ncbi . nlm . nih . gov/Genbank/ ) as accession nos . : JQ042681–JQ042688 .
|
Malaria causes more than one million deaths every year , mostly among children in Sub-Saharan Africa . Anopheles mosquitoes are exclusive vectors of human malaria . Many malaria vectors belong to species complexes , and members within these complexes can vary significantly in their ecological adaptations and ability to transmit the parasite . To better understand evolution of epidemiologically important traits , we studied relationships among nonvector and vector species of the African Anopheles gambiae complex . We analyzed gene orders at genomic regions where evolutionary breaks of chromosomal inversions occurred in members of the complex and compared them with gene orders in species outside the complex . This approach allowed us to identify ancient and recent gene orders for three chromosomal inversions . Surprisingly , the more ancestral chromosomal arrangements were found in mosquito species that are vectors of human malaria , while the more derived arrangements were found in both nonvectors and vectors . Our finding strongly suggests that the increased ability to transmit human malaria originated repeatedly during the recent evolution of these African mosquitoes . This knowledge can be used to identify specific genetic changes associated with the human blood choice and ecological adaptations .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"organismal",
"evolution",
"genome",
"evolution",
"microbiology",
"parasitic",
"diseases",
"phylogenetics",
"molecular",
"genetics",
"infectious",
"diseases",
"biology",
"evolutionary",
"systematics",
"evolutionary",
"genetics",
"tropical",
"diseases",
"(non-neglected)",
"vector",
"biology",
"genetics",
"malaria",
"genomics",
"evolutionary",
"biology",
"cytogenetics",
"computational",
"biology",
"genetics",
"and",
"genomics"
] |
2012
|
A New Chromosomal Phylogeny Supports the Repeated Origin of Vectorial Capacity in Malaria Mosquitoes of the Anopheles gambiae Complex
|
Controlling infectious disease without inducing unwanted inflammatory disease requires proper regulation of the innate immune response . Thus , innate immunity needs to be activated when needed during an infection , but must be limited to prevent damage . To accomplish this , negative regulators of innate immunity limit the response . Here we investigate one such negative regulator encoded by an alternative splice form of MyD88 . MyD88 mRNA exists in two alternative splice forms: MyD88L , a long form that encodes a protein that activates innate immunity by transducing Toll-like receptor ( TLR ) signals; and a short form that encodes a different protein , MyD88S , that inhibits the response . We find that MyD88S levels regulate the extent of inflammatory cytokine production in murine macrophages . MyD88S mRNA levels are regulated by the SF3A and SF3B mRNA splicing complexes , and these mRNA splicing complexes function with TLR signaling to regulate MyD88S production . Thus , the SF3A mRNA splicing complex controls production of a negative regulator of TLR signaling that limits the extent of innate immune activation .
The innate immune response plays a key role in fighting infection [1] . Innate immune signaling regulates the process of inflammation , which involves the secretion of cytokines and chemokines and the resulting recruitment and activation of innate and adaptive immune cells [1] . Thus , the activation of the innate immune response is an important positive step in the response to infection . However , an acutely overactive innate immune response or a chronically activated innate immune response can contribute to the pathogenesis of many diseases including sepsis , atherosclerosis , Crohn's disease , and cancer [2]–[5] . Thus it is critical that innate immunity be tightly controlled , activated when necessary and kept inactivate when not . A complex system of receptors and signal transduction molecules control the activation of the innate immune response induced by numerous stimuli . One key class of innate receptors is the Toll-like receptor ( TLR ) family; different TLRs recognize different pathogen-associated molecular patterns ( PAMPs ) . For example , TLR4 is responsible for the response to lipopolysacharide ( LPS ) from Gram negative bacteria while TLR2 is responsible for the response to various lipopeptides present in Gram positive bacteria [6] , [7] . In addition to the complex regulatory mechanism that controls innate immune activation , there are many negative regulators of innate immunity that limit the response , thereby limiting potential damage due to overactive or chronic inflammation [8]–[13] . Many such negative regulators of innate immunity have been described , including proteins that bind to and inactivate TLR signaling components [8]–[13]; deubiquitinases that inactivate ubiquitinated TLR signaling components [14]; microRNAs that regulate expression of TLR signaling genes [15]; and alternate mRNA splice forms of innate immunity genes , some of which are known to inhibit TLR signaling [16]–[22] . One such alternatively spliced TLR signaling gene is MyD88 [23]–[26] . MyD88 is a TLR signaling adaptor that acts downstream of most but not all TLRs , and that acts as a positive regulator of innate immunity [6] , [7] . In response to stimulation with PAMPs , TLRs dimerize and recruit MyD88 . This activates MyD88 , which in turn recruits and activates several IL-1 receptor-associated kinases ( IRAKs ) . This complex signal transduction cascade continues , ultimately leading to the production of inflammatory cytokines . MyD88 is encoded by an mRNA with five exons ( long form or MyD88L ) . However , a shorter MyD88 mRNA ( MyD88S ) also has been described in both mice and humans [23]–[27]; this mRNA is missing the 135 base pair second exon . Overexpression studies have demonstrated that MyD88S is a negative regulator of TLR signaling that fails to recruit and phosphorylate the IRAKs [23] , [24] , [26] . MyD88S mRNA levels are drastically increased in monocytes from septic patients suggesting that alterations in MyD88 mRNA splicing could play an important role in human disease [27] . However , thus far , the MyD88S loss of function phenotype has not been reported , and the mechanisms controlling MyD88 alternative mRNA splicing have not been investigated . Using RNAi screens in mouse macrophage cell lines , we previously identified two members of the SF3A mRNA splicing regulatory complex as regulators of the innate immune response to LPS [28] . The SF3A complex is composed of three proteins ( SF3A1 , SF3A2 , and SF3A3 ) that interact with the U2 snRNP ( small nuclear ribonucleoprotein ) [29] . The U2 snRNP interacts with the pre-mRNA branch point near the 3′ splice site in pre-mRNA [30] and facilitates mRNA splicing in conjunction with the rest of the spliceosome [31]–[34] . All three SF3A subunits are required for mRNA splicing [29] , [35]–[39] . Here we investigate the innate immune regulatory function of the SF3A mRNA splicing complex and the related splicing factor , SF3B1 which is part of the SF3B complex that functions at a similar step of mRNA splicing to SF3A [40]–[42] . We find that SF3A and SF3B are both required for a robust innate immune response to LPS and other TLR agonists . SF3A and SF3B do so in conjunction with TLR signaling , in part , by regulating the production of the alternate inhibitory splice form MyD88S . We also show that changing MyD88S mRNA levels can significantly impact the strength of the innate immune response .
We previously found that inhibition of either Sf3a1 or Sf3a2 by RNAi strongly diminished LPS-induced inflammatory cytokine production in either of two mouse macrophage cell lines , RAW264 . 7 and J774A . 1 [28] . To confirm that all three SF3A subunits ( SF3A1 , SF3A2 , and SF3A3 ) regulated the LPS response , we used siRNAs to inhibit each Sf3a subunit in the RAW264 . 7 macrophage cell line and then monitored LPS-induced production of inflammatory cytokines . Inhibition of each Sf3a subunit led to a strong decrease in IL-6 protein production and a more moderate decrease in TNFα protein production ( Figure 1A , B ) . The effect on IL-6 roughly correlated with the extent of knockdown of each subunit as measured by qPCR; siRNA directed against either Sf3a1 or Sf3a3 exhibited the strongest gene knockdown ( Figure 1C ) and the strongest IL-6 phenotypes ( Figure 1A ) . The effect on IL-6 occurred at both the protein ( Figure 1A ) and mRNA level , as the amount of IL-6 mRNA also was strongly diminished by Sf3a1 or Sf3a3 inhibition ( Figure 1D ) . In prior control experiments using RNAi in mouse macrophage cell lines , we found that inhibition of control genes such as TLR4 and MyD88 led to a stronger IL-6 than TNFα phenotype [43] , suggesting that the differing extent of inhibition of IL-6 and TNFα production when SF3A is inhibited could be due to differences in the effect of SF3A or could be due to differing sensitivities of the two cytokine promoters to perturbation of signaling . Because SF3A regulates mRNA splicing , an essential process , it was formally possible that the defects in LPS-induced cytokine production were caused by an overall non-specific decrease in mRNA splicing or fitness caused by Sf3a inhibition . However , as outlined below , several experiments argue against this possibility and argue for some specificity . First , other macrophage functions were not affected by Sf3a inhibition , including phagocytosis of FITC-labeled E . coli particles ( Figure 1E ) . Second , cell viability was not altered by Sf3a inhibition ( Figure 1F ) . Third , tests of several other mRNA splicing events indicated that many other mRNA splicing events were not affected when Sf3a1 was inhibited . For example , we monitored βactin mRNA levels when Sf3a1 was inhibited by RNAi , comparing expression by qPCR using primers that both annealed to exon 4 or primers that annealed to exons 3 and 4 ( thus crossing intron 3 ) ; we observed no significant difference between the two primer sets ( Figure S1 ) . Similarly , using primers bracketing intron 6 of the Macf1 gene ( another innate immune regulator [28] ) , we observed no change when Sf3a1 was inhibited by RNAi ( 101±13% of control , mean±SEM ) . Finally , we also monitored alternative mRNA splicing of a TLR regulatory gene known to be alternatively spliced , MD-2 . MD-2 exists in two isoforms , MD-2 , which along with TLR4 is involved in LPS recognition , and MD-2B , which lacks part of exon 3 and acts as a negative regulator of TLR4 signaling [21] . We observed no significant alteration in production of MD-2 or MD-2B mRNA when Sf3a1 was inhibited by RNAi ( Figure S2 ) . The fact that inhibition of any of the three Sf3a subunits diminished LPS-induced cytokine production suggested that the effect of SF3A on innate immunity was due to its mRNA splicing function . To further test this hypothesis , we used RNAi to inhibit the SF3B1 mRNA splicing factor . RNAi-mediated inhibition of Sf3b1 also strongly reduced LPS-induced IL-6 production ( Figure 1G ) and , as expected , diminished Sf3b1 mRNA levels ( Figure 1H ) . Thus , both the SF3A and SF3B complexes are required for a robust innate immune response to LPS , as inhibition of either diminished that response . The effects of SF3A1 and SF3B1 were not unique to mouse macrophages; we also found that RNAi-mediated inhibition of Sf3a1 or Sf3b1 greatly diminished LPS-induced IL-6 production in human THP1 differentiated macrophages while having only a moderate ( SF3B1 ) or no ( SF3A1 ) effect on viability in these cells ( Figure S3 ) . As a second method to confirm that SF3B1 was required for LPS-induced cytokine production , we used a known pharmacological inhibitor of SF3B1 , spliceostatin A ( SSA ) [44]–[46] , to inhibit SF3B1 and then monitored LPS-induced cytokine production . SSA at doses greater than 3 ng/ml diminished overall survival of RAW264 . 7 cells; these high doses of SSA also diminished the cells' ability to phagocytose FITC-labeled E . coli particles ( Figure S4 ) . However , at lower SSA doses that did not diminish survival or phagocytic ability , treatment of RAW264 . 7 macrophages with SSA led to a profound decrease in LPS-induced IL-6 production ( Figure 1I , S4 ) . Thus , inhibition of SF3B1 by RNAi or with a pharmacological agent strongly inhibited the innate immune response to LPS . To determine if these mRNA splicing regulators affected other innate immune stimuli , we also monitored the effect of SF3A1 and SF3B1 when cells were stimulated with the TLR2/1 agonist PAM3CSK4 [47] . Inhibition of either Sf3a1 or Sf3b1 by RNAi led to a strong decrease in IL-6 protein , IL-6 mRNA , and TNFα levels ( Figure 2 ) . The effect of SF3A1 and SF3B1 did not extent to all stimuli , however , as inhibition of these genes by RNAi did not inhibit the response to the TLR3 agonists poly ( I:C ) ( Figure S5 ) or poly ( A:U ) ( data not shown ) [we monitored production of TNFα rather than IL-6 in these assays because poly ( I:C ) induced little IL-6] . TLR4 uses two signaling adaptors , MyD88 and TRIF , to control the response to LPS . SF3A1 and SF3B1 likely regulate MyD88 signaling , because they affect LPS and PAM3CSK4-induced production of IL-6 and TNFα . To determine if SF3B1 affects the TRIF-dependent arm of the TLR4 pathway , we monitored production of IFNβ by qPCR when SF3B1 was inhibited by SSA; we found that SSA treatment diminished both IL-6 and IFNβ production ( Figure S6 ) , indicating that SF3B1 has both MyD88-dependent and MyD88-independent effects downstream of TLR4 . To investigate the relationship between SF3A1 and TLR signaling further , we used RNAi to inhibit Sf3a1 in cells that expressed activated TLR signaling components ( Figure 3A ) . These activated constructs included a constitutively active IKK construct containing two mutations in the active site [IKK-2S177ES181E [48]] and an inducibly active MyD88 construct [49] . MyD88 was rendered inducibly active in a construct in which full length MyD88 is fused to the effector domain of subunit B of E . coli DNA gyrase [49]; treatment of cells with the antibiotic coumermycin [49] leads to dimerization of DNA gyrase B and thus dimerization and activation of MyD88 . As a negative control , we also inhibited Sf3a1 by RNAi in macrophages expressing chloramphenicol acetyltransferase ( CAT ) , which should not alter innate immunity . As expected , cells expressing the negative control protein CAT produced IL-6 in the presence but not the absence of LPS , and further inhibition of Sf3a1 in these cells led to a strong decrease in IL-6 production ( Figure 3B ) . Cells overexpressing the MyD88-gyrB fusion produced IL-6 in the absence of LPS , and this was enhanced by the addition of coumermycin , as expected ( Figure 3B ) . The MyD88-gyrB fusion expresses full length MyD88 protein . MyD88 mRNA levels were 162±24 ( mean±SEM ) -fold higher than normal ( determined by qPCR ) in cells overexpressing MyD88-gyrB , and this high level of full length MyD88 may be able to activate signaling even in the absence of the dimerizing agent . Nevertheless , Sf3a1 siRNA diminished IL-6 production when MyD88-gyrB was overexpressed ( Figure 3B ) . However , Sf3a1 inhibition did not prevent IL-6 production induced by overexpression of the constitutively activated IKK construct ( Figure 3B ) . These data are consistent with SF3A1 exerting its effect on TLR signaling pathways , acting downstream of MyD88 and upstream of IKK . Because multiple SF3A subunits and SF3B1 all regulate LPS-induced cytokine production , we hypothesized that these mRNA splicing factors were regulating the splicing of a TLR-regulatory gene ( s ) . Moreover , this gene likely acts downstream of MyD88 and upstream of IKK . One candidate that fits these data is MyD88 itself , as the alternate splice form MyD88S inhibits IRAK activation downstream of MyD88 and upstream of IKK [23] , [24] , [26] . We therefore chose to monitor MyD88 mRNA splicing by qPCR using primers that can distinguish between the five exon MyD88L splice form and the four exon MyD88S splice form ( Figure 4A ) . For the qPCR studies , we detected MyD88L using a primer that spanned exons 2 and 3 and a second primer in exon 3 ( Figure 4A ) . We detected MyD88S using a primer that spanned exons 1 and 3 and a second primer in exon 3 ( Figure 4A ) . Inhibition of Sf3a1 in either the presence or absence of LPS did not alter MyD88L mRNA levels substantially but did increase the MyD88S shorter splice form ( Figure 4B ) . Both LPS and Sf3a1 inhibition contributed to this increase in MyD88s mRNA ( Figure 4B ) . To test if SF3B1 , like SF3A1 , regulated MyD88S mRNA levels , we inhibited SF3B1 using either RNAi or SSA treatment and monitored MyD88L and MyD88S mRNA by qPCR . Inhibition of Sf3b1 by RNAi , like inhibition of Sf3a1 , did not significantly alter MyD88L mRNA levels in the presence of LPS but did significantly increase MyD88S mRNA levels in the presence of LPS ( Figure 4C ) . Similarly , inhibition of SF3B1 by SSA had at most a moderate effect on MyD88L mRNA levels while leading to a substantial increase in MyD88S mRNA levels ( Figure 4D ) . As a control to confirm that not all siRNA treatments altered MyD88 mRNA splicing , we found that RNAi-mediated inhibition of the 26S proteasome subunit Psmd3 greatly diminished LPS-induced IL-6 production [43] ( Figure S7A ) without significantly altering production of MyD88L or MyD88S ( Figure S7B , C ) . The qPCR data indicated that one of the wild type functions of SF3A1 and SF3B1 is to inhibit production of MyD88S , as MyD88S levels are increased when either mRNA splicing factor is inhibited . To confirm these MyD88 mRNA qPCR data , we monitored MyD88L and MyD88S mRNA levels using semi-quantitative reverse transcription-PCR followed by agarose gel elecrophoresis . For these experiments , we used two sets of primers , one set designed to specifically monitor MyD88S levels and one set designed to monitor both MyD88L and MyD88S simultaneously ( Figure 4A ) . For the MyD88S-specific primers , we used a reverse primer that spanned exons 3 to 1 and a forward primer that annealed to exon 1 ( Figure 4A ) ; these primers generate a 124 bp product when MyD88S is present . For primers that amplify both MyD88L and MyD88S , we used primers that annealed to exons 1 and 3 ( Figure 4A ) ; these generate a 370 bp band corresponding to MyD88L and a 235 bp band corresponding to MyD88S . Using the MyD88S-specific RT-PCR primers ( Figure 4A ) , we found that treatment of cells with either LPS or Sf3a1 siRNA alone had a fairly moderate effect on MyD88S mRNA levels ( agarose gel in Figure 5A , quantitation from three independent experiments in Figure 5B ) . However , cells treated with both LPS and Sf3a1 siRNA exhibited a substantial increase in MyD88S mRNA ( Figure 5A , B ) . As a control , we found that these treatments did not alter production of βactin ( Figure 5A , C ) . Using the reverse transcription primers that amplified both MyD88L and MyD88S simultaneously ( Figure 4A ) , we were able to visualize MyD88L and MyD88S ( Figure 5D ) . Consistent with the qPCR data , treatment of cells with LPS and Sf3a1 siRNA either alone or together did not significantly alter MyD88L mRNA levels ( agarose gel in Figure 5D , quantitation from three independent experiments in Figure 5E ) . However , treatment of cells with LPS and Sf3a1 siRNA did significantly enhance MyD88S mRNA levels ( Figure 5D , F and S8 ) . The RT-PCR experiments using primer sets that amplified both MyD88L and MyD88S allowed us to estimate the ratio of MyD88L to MyD88S . In the absence of treatment , this ratio was roughly 20∶1; in the presence of LPS and Sf3a1 siRNA , the MyD88L to MyD88S ratio increased significantly to approximately 5∶1 . This raised the question of whether this change in MyD88S was sufficient to overcome the greater MyD88L level and alter innate immunity significantly . To test this directly , we engineered a siRNA that spanned the exon 1–3 boundary in MyD88S ( and would thus not be present in MyD88L ) with the goal of designing an siRNA that specifically inhibits MyD88S but not MyD88L . We tested two siRNAs in this fashion that differed in their start location by only one base; one did not affect MyD88S levels significantly ( not shown ) but the other did , as described below . Treatment of macrophages with the MyD88S-specific siRNA led to a roughly 75% decrease in MyD88S mRNA levels while having a more moderate effect on MyD88L mRNA ( Figure 6A ) , indicating some degree of efficacy and specificity . As a control , treatment of cells with a pool of four siRNAs targeting total MyD88 led to an 80% decrease in both MyD88L and MyD88S levels , as expected ( Figure 6A ) . We therefore used these siRNAs to monitor the effect of changes in total MyD88 or MyD88S levels on LPS-induced cytokine production . Inhibition of total MyD88 ( MyD88L+MyD88S ) decreased LPS-induced IL-6 production ( Figure 6B ) , as expected . In contrast , inhibition of MyD88S using the MyD88S-specific siRNA led to significantly increased LPS-induced IL-6 production ( Figure 6B ) . This near doubling in cytokine production was impressive as the knockdown of MyD88S using this siRNA was incomplete and there was also some effect on MyD88L , both of which could allow us to underestimate the true scope of the effect of MyD88S . It was possible that all of the effects of SF3A1 on innate immunity could be mediated by changes in MyD88S levels; alternatively , it was possible that SF3A1 affects production of several regulators of TLR signaling including MyD88S . To distinguish between these possibilities , we treated cells with two siRNAs simultaneously: siRNA targeting Sf3a1 and siRNA targeting MyD88S . Inhibition of Sf3a1 , as described above , strongly diminished LPS-induced IL-6 production ( Figure 6C ) . Inhibition of Sf3a1 and MyD88S simultaneously partially restored IL-6 production ( Figure 6C ) . Thus , at least some of the effect of Sf3a1 inhibition is mediated by increases in MyD88S levels . As a control , qPCR used to monitor gene knockdown demonstrated that the various siRNA treatments were acting as expected ( Figure S9 ) . However , the small effect of the MyD88S-specific siRNA on MyD88L makes it difficult to determine with certainty if this incomplete rescue is due to limitations of the RNAi experiment or because other TLR regulators are also affected by SF3A1 . Regardless , it is clear that changes in MyD88S levels account for at least part of the effect of SF3A1 on innate immunity .
MyD88S has been observed in multiple mouse and human cells , cell lines , and tissues [23]–[25] , [27] , [50] , [51] . Prior studies investigating MyD88S used overexpression or reintroduction strategies to demonstrate that MyD88S was a TLR signaling inhibitor that functioned by inhibiting IRAK phosphorylation [23] , [24] , [26] . By developing a siRNA that targets the unique splice junction in MyD88S , we have now been able to demonstrate in a MyD88S loss-of-function experiment that MyD88S is , as demonstrated in the published overexpression studies , an inhibitor of the innate immune response . Moreover , we show that while there is far more MyD88L than MyD88S in macrophages , changes in the amount of the minor MyD88S splice form are sufficient to overcome the much larger pool of MyD88L and affect inflammatory cytokine production . This is consistent with published overexpression data that indicate that MyD88S is able to inhibit a large pool of MyD88L [24] . We have found that inhibition of the SF3A or SF3B complexes by RNAi or with a pharmacological agent leads to a strong decrease in production of the pro-inflammatory cytokine IL-6 and a more moderate decrease in production of the pro-inflammatory cytokine TNFα without affecting macrophage viability or phagocytosis . Other reports indicate that RNAi-mediated knockdown of Sf3a subunits can affect cell survival in HeLa cells [38]; moreover , a knockout in Sf3b1 in mice is lethal , although heterozygous Sf3b1 mice develop largely normally [52] . The difference in our data may be due to incomplete but still very strong knockdown in macrophages or other cell-type-specific differences . One of the innate immune targets of SF3A and SF3B is production of the alternate splice form of MyD88 , MyD88S ( Figure 7 ) . The spliceosome is a large multi-subunit protein and RNA complex that facilitates intron removal in two catalytic steps . First , the 5′ splice site is cleaved resulting in the formation of a lariat structure . Second , the 3′ splice site is cleaved and the exons are ligated together [29] , [32] , [33] . The SF3A and SF3B complexes in conjunction with the U2 snRNP bind to the branch site near the 3′ splice site to facilitate mRNA splicing [30] , [35]–[42] , . These mRNA splicing complexes play an important role in proper 3′ splice site recognition; this is evidenced by the frequent observation of altered mRNA splicing observed when SF3B1 is inhibited or mutated [44] , [54]–[56]; in many cases , inappropriate exon skipping is observed . This phenomenon of altered splicing and exon skipping is also consistent with the effect of SF3A1 or SF3B1 inhibition on MyD88S production; MyD88S is produced if the 3′ splice site at the end of intron 1 is skipped and the 3′ splice site at the end of intron 2 is used instead ( Figure 7 ) . It is intriguing to speculate that the MyD88 splice site choice evolved to be exquisitely sensitive to cellular conditions because of its functional significance , and may be a key point of regulation to limit inflammation . While our data indicate the importance of MyD88S in mediating the innate immune effects of SF3A/SF3B , our data also suggest that other regulator ( s ) of TLR signaling also are affected by these mRNA splicing regulators . Inhibition of MyD88S using our MyD88S-specific siRNA is only able to partially rescue the innate immune defect caused by inhibition of Sf3a1 . It is unclear if this incomplete rescue is due to limitations of the RNAi experiment or because another gene ( s ) are also regulated by SF3A1 , although we favor the latter possibility . Several other pieces of data argue that SF3A/SF3B are affecting other genes besides MyD88 to regulate innate immunity , including the observation that SF3B1 inhibition can affect LPS-induced IFNβ production . Moreover , we did not observe significant inhibition of IRAK1 activation when SF3a1 is inhibited ( data not shown ) ; while the regulation of IRAK1 by MyD88S has not been studied in a loss-of-function context , these data also are consistent with the possibility that SF3a1 regulates innate immunity using both MyD88S-dependent and independent means . By inhibiting MyD88S using a MyD88S-specific siRNA , we demonstrated a significant increase in inflammatory cytokine production . Even a moderate increase in inflammation could have a significant impact on disease . Adib-Conquy et al . [27] observed that there was a roughly 10-fold increase in MyD88S levels in monocytes from patients with sepsis , which could explain the immunosuppressed phenotype of these cells . The SF3B1 and SF3A1 mRNA splicing factors have also been implicated in the pathogenesis of numerous hematologic malignancies . In particular , Sf3b1 mutations are prevalent in a wide range of hematologic malignancies , associated with 5% of acute myeloid leukemia cases , 10–15% of chronic lymphocytic leukemia cases , and 60–80% of the myelodysplastic syndrome subtype Refractory Anemia with Ring Sideroblasts ( MDS-RARS ) [57]–[68] . Chronic inflammation has been implicated in the pathogenesis of many solid and hematologic malignancies [4] , [69]–[73]; conceivably , altered innate immunity signaling could be one of the factors involved in the pathogenesis of these malignancies . MyD88S inhibits TLR signaling at the level of the IRAK kinases [23] , [24] , [26] ( Figure 7 ) . We have now demonstrated that the SF3A and SF3B complexes inhibit production of this alternative MyD88S splice form ( Figure 7 ) . Prolonged LPS exposure is reported to enhance MyD88S production [24] , and our data also indicates that LPS can enhance MyD88S levels ( Figure 7 ) . It is possible that SF3A1 could act either in parallel to or downstream of TLR signaling to control MyD88S production . How might the TLR pathway interact with the SF3A mRNA splicing complex ? Some intriguing published protein interaction studies raised the possibility that MyD88 itself could directly regulate the SF3A complex to modulate its own mRNA splicing . Human SF3A3 has been reported to bind to MyD88 in liver cells using an immunoprecipitation-mass spectrometry assay [74] . The C . elegans SF3A1 ortholog has been reported to bind to the sole C . elegans MyD88 family member TIR-1 in a yeast 2 hybrid assay [75] . TIR-1 is most homologous to mammalian SARM , a negative regulator of mammalian innate immunity [76] , [77] , but functionally behaves most like MyD88 , in that it is required for host defense to many classes of pathogens and acts upstream of the p38 MAPK pathway [78]–[80] . Finally , Drosophila SF1 ( another mRNA splicing factor that interacts with the U2 snRNP ) has been reported to interact with Drosophila MyD88 in a yeast two hybrid assay [81] . While the SF3A complex functions in the nucleus to control mRNA splicing , it is assembled in the cytoplasm [82] , [83] and could be available for modification by MyD88 , at least transiently . Future studies will be needed to determine the biological significance of this interaction . However , these data raise the possibility of a MyD88-mediated negative feedback loop that ensures that innate immunity is self limiting ( Figure 7 ) ; this could be relevant to sepsis , cancer , and the myriad of other diseases with an inflammatory component [84] .
RNAi using RAW264 . 7 cells was performed largely as described [43] . In brief , pools of siRNA duplexes ( Dharmacon ) targeting the indicated genes were transfected into the mouse macrophage cell line RAW264 . 7 using the Amaxa 96-well nucleofector shuttle . Cells were then either plated in 100 , 000 cells per well in 96-well format for subsequent ELISA assays or 200 , 000 cells/well in 24-well format for subsequent qPCR analysis . The MyD88S-specific siRNA sequence was 5′-GAAGTCGCGCATCGGACAA-3′ . We also tested a second siRNA that was shifted one base pair 3′; this siRNA did not significantly inhibit MyD88S mRNA levels . Negative control siRNAs were Dharmacon's non-targeting siRNA pool #1 and in some cases non-targetting siRNA #1 . Twenty-four hours after siRNA transfection , cells were stimulated with the indicated PAMPs for six hours . Doses used were 20 ng/ml LPS ( List Biological Labs ) , 1 . 5 µg/ml PAM3CSK4 ( Invivogen ) , or 6 µg/ml poly ( I:C ) ( Invivogen ) . Several different assays were then performed . In some cases , cell supernatants were collected and cytokine production was monitored by ELISA ( R&D Biosystems ) . Viability of the remaining adherent cells was monitored using fluorescein diacetate , which is cleaved into a fluorescent form in intact live cells [85] . In other experiments , RNAi-treated cells were analyzed for their ability to phagocytose FITC-labeled E . coli particles using the Vybrant Phagocytosis assay kit ( Molecular Probes ) . In other experiments , RNAi-treated cells were lysed in RLT buffer ( Qiagen ) and used to prepare RNA for qPCR or RT-PCR . In the experiments using two different siRNAs at the same time in RAW264 . 7 cells , the siRNAs were transfected simultaneously with an equal volume of each . In these dual transfection experiments , when only a single siRNA was used , the volume of siRNA was made up with an equal volume of Dharmacon non-targetting siRNA pool #1 . RNAi in the human THP1 cell line was performed by first transfecting pools of siRNAs targeting either SF3A1 or SF3B1 ( and control non-targeting siRNA pool ) using the Amaxa 96-well nucleofector shuttle . Cells were then plated at 200 , 000 cells per well in 96-well format . 8 hours later , 50 ng/ml phorbol 12-myristate 13-acetate ( PMA ) was added . 24 hours later , the cells were exposed to 50 ng/ml LPS for six hours , and then IL-6 production and viability were monitored . In the experiments in which both plasmids and siRNAs were delivered to RAW264 . 7 macrophages , cells were first transfected in 12 well-format with the indicated plasmids ( 1 . 6 µg each ) using 0 . 7% ( v/v ) Fugene HD ( Roche ) for transfection . 24 hours later , cells were transfected with siRNA in 96 well-format using the Amaxa system . 24 hours later , cells were exposed to either of 0 . 1 µM Coumermycin A ( Sigma ) or LPS for six hours as indicated , and then cytokine production was monitored by ELISA . Transfection efficiency using Fugene HD was roughly 40% ( determined using a plasmid expressing GFP and fluorescence microscopy ) and was not affected by the different siRNA treatments . RNA for analysis was prepared by lysing cells in RLT buffer and using the Qiagen RNAeasy kit for RNA purification . qPCR was performed on an ABI 7900 using the Qiagen Quantitect SYBR-green assay kit . Data was normalized using βactin as a control . Because we were monitoring the effect of known mRNA splicing regulators , we tested primers that were entirely internal to exon 4 and primers that crossed intron 3; both gave similar results in all experiments . mRNA levels were also analyzed in semi-quantitative fashion using RT-PCR followed by agarose gel electrophoresis . 500 ng total RNA prepared as described above was first subjected to reverse transcription using Superscript III reverse transcriptase ( Invitrogen ) . The reverse transcribed cDNA was then subjected to PCR using Taq DNA polymerase ( Invitrogen ) , PCR products were subjected to electrophoresis in 2% agarose gels , and images were captured using a UV box and a CCD camera . The sequences of all primers are listed in Table S1 . We were unable to visualize MyD88S protein by western blot using three different commercial sources of MyD88 antisera; presumably , this is reflective of the large ratio of MyD88L∶MyD88S that we observed using RT-PCR ( Figure 5D ) . This also is consistent with prior published studies in which MyD88S protein could be monitored by western blot in RAW264 . 7 cells in which the entire pool of MyD88L is artificially converted to MyD88S using antisense oligonucleotides [86] , but not in otherwise wild-type cells [24] . Cells were treated with the indicated doses of SSA ( diluted in methanol from a 100 µg/ml stock in methanol ) for six hours . Methanol was kept at less than <0 . 5% total volume , was matched in control cells , and didn't alter cytokine production or viability . After the six hour SSA exposure , LPS was added to the media containing SSA for an additional six hours . Then viability , phagocytosis , cytokine production , and various mRNA levels , were analyzed as outlined above . All data are from a minimum of three biological replicates . Data were graphed and analyzed using Graphpad Prism 5 . Statistically significant differences in all experiments were considered p<0 . 05 and were determined using t-tests . Bands on agarose gels were quantified using Image J [87] and subsequently analyzed for significance in Graphpad Prism 5 . While we only display representative images of agarose gels from one experiment , the analyzed data and statistics are from three independent experiments .
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In response to infection , the body induces the process of inflammation , which is critical to combating the pathogen . However , it also is critical that this inflammatory response be tightly regulated , because overactive or chronically activated inflammation can contribute to a myriad of diseases including sepsis , atherosclerosis , cancer , and Crohn's Disease . Many genes have been identified that either turn on inflammation in response to infection ( positive regulators ) or turn off the response to ensure that it is limited ( negative regulators ) . Understanding how these negative regulators act may open the door to new therapies to limit inflammation and prevent inflammatory diseases . In the current study , we investigate one such negative regulator called MyD88S . We provide a framework to understand how MyD88S is produced , how the body's response to infection alters its production , and how it might be manipulated , which could provide a new means of attack for some of these inflammatory diseases .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2013
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Limiting of the Innate Immune Response by SF3A-Dependent Control of MyD88 Alternative mRNA Splicing
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We have previously reported that mutations in the polymerase proteins PB1 , PB2 , PA , and the nucleocapsid protein NP resulting in enhanced transcription and replication activities in mammalian cells are responsible for the conversion of the avian influenza virus SC35 ( H7N7 ) into the mouse-adapted variant SC35M . We show now that adaptive mutations D701N in PB2 and N319K in NP enhance binding of these proteins to importin α1 in mammalian cells . Enhanced binding was paralleled by transient nuclear accumulation and cytoplasmic depletion of importin α1 as well as increased transport of PB2 and NP into the nucleus of mammalian cells . In avian cells , enhancement of importin α1 binding and increased nuclear transport were not observed . These findings demonstrate that adaptation of the viral polymerase to the nuclear import machinery plays an important role in interspecies transmission of influenza virus .
The natural host of influenza A viruses is waterfowl where these agents occur in large variety defined by 16 hemagglutinin and 9 neuraminidase subtypes . Avian influenza viruses are the source of devastating outbreaks in poultry . Moreover , because of their potential to cross species barriers , to adapt to new hosts , and to cause on rare occasions pandemics , they are also a constant threat to human health [1] . As members of the Orthomyxoviridae family influenza A viruses have a segmented RNA genome of negative polarity . The eight segments are present in enveloped virus particles as ribonucleoprotein ( RNP ) complexes with the nucleocapsid protein ( NP ) and the three subunits of the RNA-dependent RNA-polymerase ( PB1 , PB2 , PA ) . In the infected cell , the polymerase is responsible for transcription and replication of the viral genome [2 , 3] . Evidence is increasing that the viral polymerase plays a major role in host adaptation . Thus , in a comparative study of the avian strain SC35 ( H7N7 ) and its mouse-adapted variant SC35M we showed that adaptation to mice was the result of seven mutations in the polymerase proteins , six of which ( L13P and S678N in PB1 , D701N and S714R in PB2 , K615N in PA , and N319K in NP ) were responsible for enhanced polymerase activity in mammalian cells . In avian cells , replication and transcription of SC35M were reduced , whereas both activities were increased with SC35 . Furthermore , the differences in polymerase activity were paralleled by differences in pathogenicity: SC35 was highly pathogenic for chickens and had reduced pathogenicity in mice , whereas the opposite was the case with SC35M . Thus , the efficiency of the viral polymerase is a determinant of both host specificity and pathogenicity [4 , 5] . PB2 mutation D701N has also been implicated in the adaptation of H5N1 viruses to mammalian hosts [6 , 7] but other mutations may be involved , too , notably PB2 mutation E627K [8–13] . All of these findings support the concept that adaptation of the polymerase to host factors is an important mechanism underlying interspecies transmission [5] . The influenza virus polymerase is active in the nucleus of the infected cell where cytoplasmicly expressed PB1 and PA appear to be imported as a subcomplex which then assembles with separately imported PB2 [14] . There is evidence that the different polymerase subunits use the classical import pathway of the host cell depending on the recognition of a nuclear localization signal ( NLS ) of the cargo protein by an importin α/β dimer as well as non-classical pathways that rely on direct interaction of the cargo with an importin β homologue receptor [15] . Thus , PB1-PA dimers enter the nucleus via a non-classical transport pathway by binding to RanBP5 [16] . NP , in contrast , binds to importin α1/α2 [17] indicating that it uses the classical pathway . The same route is used for the nuclear transport of PB2 as demonstated by a recent crystallographic study showing that the C-terminus of this protein forms a complex with importin α5 [18] . Interestingly , the authors of this study hypothesized that PB2 mutation D701N which is also a host range determinant as pointed out above , may affect the binding of importin α5 to PB2 . These observations suggest that importins belong to the host factors to which the polymerase adapts during interspecies transmission . To test this hypothesis we have compared now in avian and mammalian cells the interaction of the polymerase complex of SC35 and SC35M with importin α1 , which not only binds to NP , but is also the most abundant importin in a variety of human cells [19] and may function as an interchangeable housekeeping transport factor [20] . We show that adaptative mutations D701N and N319K improve binding of PB2 and NP , respectively , to importin α1 in mammalian , but not in avian cells . As a result , the efficiency of the transport of these proteins into the nucleus of mammalian cells is enhanced . These data support the notion that the interaction of PB2 and NP with importin α1 plays an important role in determining host range and pathogenicity of influenza A viruses .
To test the hypothesis that the polymerase proteins of SC35 and SC35M differ in their interaction with the nuclear import machinery of mammalian and avian cells we have analyzed the binding of PB2 and NP to importin α1 in co-immunoprecipitation experiments . Cultures of human 293T cells and quail embryo cells ( CEC-32 ) were transfected with plasmids encoding PB2 or NP . Importin α1 complexed with PB2 or NP was precipitated from lysates of transfected and mock transfected cells using specific antibodies against PB2 or NP , which were covalently coupled to an amine-reactive gel . Bound proteins were eluted three times from the columns using acidic elution buffer to allow quantitative estimation of interaction partners . All three eluates were used to detect importin α1 , PB2 and NP , respectively , by Western blot analysis . In 293T cells transfected with PB2 of SC35M or PB2 D701N , 4 to 7 times more importin α1 was bound than in cells transfected with PB2 of SC35 ( Figure 1A and 1C ) . Likewise , NP derived from SC35M precipitated 2 times more importin α1 from 293T cells than SC35 NP ( Figure 1B and 1D ) . In contrast , SC35 PB2 and SC35M PB2 bound similar amounts of importin α1 when CEC-32 cells were transfected ( Figure 2A and 2C ) . There was also no difference in importin binding efficiency when SC35 NP and SC35M NP were expressed in avian cells ( Figure 2B and 2D ) . These observations indicate that the adaptive mutations PB2 D701N and NP N319K specifically improve the binding of PB2 and NP to mammalian importin α1 adaptor protein . It was now of interest to find out if increased binding of NP and PB2 to importin α1 affected nuclear transport in mammalian cells . First , we have carried out Western blot experiments to determine importin α1 in nuclear and cytoplasmic fractions prepared from infected cells early and late in the replication cycle . Since replication kinetics were different in avian and mammalian cells , time points with comparable virus titres were selected ( 6 h and 12 h p . i . in 293 T cells , 9 h and 18 h p . i . in CEC32 cells ) ( Figure S1 ) . Early after infection of 293T cells with SC35M , we found a distinct accumulation of importin α1 as well as importin ß1 and NP in the nucleus . This phenomenon was not observed with SC35 ( Figure 3A ) . Late in infection nuclear accumulation of these proteins was seen neither with SC35 nor with SC35M ( Figure 3B ) . Nuclear accumulation of importin α1 was also not detected in avian cells early or late after infection with either virus . Furthermore , the expression levels of SC35 and SC35M NP were similar in the nuclear and cytoplasmic fractions of CEC-32 cells at both time points ( Figure 3C and 3D ) . When unfractionated cell lysates were analyzed , no differences in the amounts of importin α1 were detected , irrespective of cell type , virus strain , and time after infection ( Figure S2 ) . This observation indicates that the increased amount of importin α1 seen in the nuclei of 293T cells early after infection with SC35M was the result of increased transport into the nucleus and did not reflect up-regulated importin α1 synthesis . We have then determined the kinetics of nuclear accumulation of importin α1 . 293T cells were infected with SC35M or SC35 , and the intracellular localization of importin α1 was determined at different intervals by immuno-fluorescence analysis ( Figure 4 ) . In cells infected with SC35M , importin α1 was gradually shifted from the cytoplasm to the nucleus where it was almost exclusively present 6 h p . i . Later in infection it was detected again in the cytoplasm . In cells infected with SC35 , importin α1 was equally distributed between cytoplasm and nucleus throughout the replication cycle . Taken together , these results demonstrate that SC35M induces specifically in mammalian cells a transient accumulation of importin α1 in the nucleus with a peak at 6 h p . i . which presumably coincides with the maximal replication rate of the virus . To identify the mutations in the polymerase proteins of SC35M responsible for the nuclear accumulation of importin α1 , we have first analyzed single gene reassortant ( SGR ) viruses containing one of the polymerase genes of SC35M in a SC35 background . Cells infected with SGR viruses were separated into nuclear and cytoplasmic fractions , and importin α1 and importin ß1 localization was determined ( Figure 5 ) . Only SGR viruses SC35-PB2SC35M and SC35-NPSC35M containing the PB2 or the NP gene of SC35M showed enhanced importin α1 and importin ß1 levels in the nuclear fractions , although the increase was not as distinct as with the parental SC35M virus ( Figure 3 ) . With the SGR viruses containing PB1 or PA of SC35M , there was no importin accumulation in the nucleus ( Figure 5 ) . Since SC35M NP differs from SC35 NP only by one amino acid substitution ( N319K ) , it can be concluded that this mutation contributes to nuclear accumulation of importin . SC35 PB2 displays two amino acid substitutions contributing to increased mouse virulence ( D701N and S714R ) . To determine which of these mutations controls nuclear transport of importin , we infected cells with single point mutant ( SPM ) viruses SC35-PB2701N and SC35-PB2714R containing only one of these mutations . Nuclear accumulation of importin α1 was observed in SC35-PB2701N infected , but not in SC35-PB2714R infected cells ( Figure 5 ) . These findings indicate that mouse adaptation mutations PB2 D701N and NP N319K promote nuclear accumulation of importin α1 in mammalian cells . Some of the data described so far suggested already that nuclear accumulation of importins in SC35M infected mammalian cells is accompanied by increased NP transport into the nucleus . To further analyze the effect of the adaptive mutations in NP and PB2 on the intracellular localization of these proteins , we have performed immunofluorescence assays in mammalian cells . While PB2 of SC35M was predominantly located in the nucleus of human lung cells ( A549 ) , most of the cells infected with SC35 showed a nuclear and cytoplasmic distribution of PB2 ( Figure 6A ) . This observation indicates that SC35M PB2 is transported into the nucleus more efficiently than SC35 PB2 . Increased nuclear transport of SC35M PB2 correlated with the nuclear accumulation of importin α1 as indicated by a distinct co-localization of PB2 and importin α1 in the nucleus . On the other hand , in cells infected with SC35 , importin α1 was present throughout cytoplasm and nucleus as was the case with PB2 ( Figure 6A ) . When A549 cells were infected with SGR virus SC35-PB2SC35M and SPM virus SC35-PB2701N , PB2 was also concentrated in the nucleus where it co-localized with importin α1 ( Figure 6A ) . Nuclear accumulation of PB2 was not observed in cells infected with SC35-PB2714R ( data not shown ) . We have then analyzed the nuclear import of NP by immunofluorescence ( Figure 6B ) . NP of SC35M and SC35-NPSC35M was located predominantly in the nucleus , whereas a large part of SC35 NP was found in the cytoplasm . In cells infected with SC35M and SC35-NPSC35M , importin α1 was concentrated in the perinuclear region where it partly co-localized with NP . In SC35 infected cells importin α1 prevailed in the cytoplasm . Similar results have been obtained when the intracellular localization of these proteins was analyzed by immunofluorescence in 293T human kidney cells ( Figure S3 ) . Taken together , these observations indicate that , in mammalian cells , mutations PB2 D701N and NP N319K enhance the efficiency of the nuclear import of PB2 and NP as well as importin α1 . Intracellular localization of NP , PB2 and importin α1 has also been analyzed in CEC-32 cells . With both viruses , PB2 was clearly present in the nucleus , but it was also detected in the cytoplasm . Importin α1 co-localized with PB2 in the cytoplasm as well as the nucleus ( Figure 7A ) . NP displayed a similar intracellular distribution pattern . Again , there was co-localization with importin α1 in the nucleus and in the cytoplasm , and there were no differences between SC35 and SC35M ( Figure 7B ) . Thus , it appears that PB2 and NP of the avian and the mouse-adapted virus are transported with the same efficiency into the nucleus of avian cells .
We show here that mutations D701N in PB2 and N319K in NP responsible for mouse adaptation of the avian influenza virus SC35 enhance binding of these proteins to importin α1 of mammalian origin and , thus , improve the efficiency of their transport into the nucleus of mammalian cells . Increased transcription and replication activities in mammalian cells [4 , 5] are therefore , at least in part , the result of facilitated recruitment of polymerase subunits into the nucleus . In avian cells , neither enhancement of importin binding and nuclear transport nor increased polymerase activity [5] were observed . The differences in the nuclear transport of PB2 and NP were reflected by the efficiency of virus replication . In human lung cells SC35M grew to virus titres 2 logs higher than SC35 . The SGR virus SC35-NPSC35M grew as well as SC35M , whereas titres of SGR virus SC35-PB2 SC35M were slightly reduced . In avian cells , parental and SGR viruses grew to equally high titres ( Figure S5 ) . These findings demonstrate that adaptation of PB2 and NP to importin α1 plays an important role in interspecies transmission . It has to be pointed out , however , that adaptive mutations different from PB2 D701N and NP N319K have been described in SC35M as well as numerous other viruses [4 , 6 , 7 , 21 , 22] . Thus , host adaptation is clearly a multifactoral process . Importin α is the receptor for NLS-bearing cargo proteins . PB2 was first shown to contain NLSs at residues 449–495 and 736–739 [23] . The recent crystallographic analysis by Tarendeau and coworkers ( 2007 ) revealed that the latter sequence was part of a classical bipartite NLS comprising residues 738–755 which has to be unfolded by release of a salt bridge between aspartate 701 and arginine 753 to allow binding to importin α5 . These authors also suggested that the adaptive mutation D701N observed in PB2 of SC35M might affect binding to importin α5 in different species . By showing that this mutation , indeed , improves importin α binding and nuclear transport of PB2 in mammalian cells we now confirm this concept . It has to be pointed out , however , that importin α5 used for the crystallographic analysis and importin α1 identified as a binding partner of PB2 in the present study differ significantly from each other in tissue specificity and cargo selectivity [24 , 25] . There are also large variations in amino acid sequence , but tryptophan residues 149 , 191 , 234 and 360 in importin α5 , shown to be directly involved in the binding of the bipartite NLS of PB2 [18] , are highly conserved and present in importins α5 as well as α1 ( Figure S4 ) indicating that the crystallographic data obtained with importin α5 are also relevant for importin α1 . However , additional structural and functional studies are clearly needed to assess the role of individual members of the importin α group in host adaptation . More detailed structural analysis of PB2 binding to importin α1 may also help to explain why adaptive PB2 mutation S714R did not affect in our study importin α1 binding and nuclear transport , even though it has also been implicated in PB2 binding to importin α5 [18] . Considerably less is known about the mechanism by which mutation N319K improves importin α1 binding and nuclear transport of NP in mammalian cells . Several NLSs have been identified on NP . An unconventional NLS located between amino acid residues 1–13 was shown to be involved in NP binding to importin α1 and importin α2 [17] . The second NLS is a bipartite signal located in the middle of NP between residues 198–216 which contributes less to the nuclear localization of NP than the unconventional NLS at the amino-terminus [26] . Furthermore , a nuclear accumulation site has been attributed to residues 336–345 in microinjection studies employing Xenopus oocytes and cells of rodent and primate origin [27 , 28] . None of these sites includes amino acid 319 . A mutation in this position may therefore modulate one of the NLSs identified on NP by an allosteric mechanism . Interestingly , we did not see differences in importin α1 binding and nuclear localization of PB2 and NP when we compared SC35 and SC35M in avian cells . Thus , while up-regulating nuclear transport in mammalian cells , the adaptive mutations did not interfere with it in avian cells albeit 82% homology between the avian and the human importin α1 ( data not shown ) . This observation supports the concept that the virus when crossing the species barrier , goes through a phase that allows gradual acquisition of adaptive mutations without loosing fitness for the old host [5] . NLSs have also been identified in PB1 [29] and PA [30] , but there is no apparent link between these signals and adaptation mutations L13P and S678N in PB1 and K615N in PA . Furthermore , neither importin binding nor nuclear localization of PB1 and PA have been analyzed in the present study , but the observation that PB1 and PA of SC35M did not induce nuclear accumulation of importin α1 ( Figure 5 ) is compatible with the view that these proteins enter the nucleus via a non-classical pathway [16] . Altogether , however , it remains to be seen whether the adaptive mutations observed in PB1 and PA up-regulate polymerase activity in mammalian cells also by increased nuclear transport or by another mechanism . All cellular proteins using the classical nuclear import pathway have to compete with each other for importin α , and there is evidence that the equilibrium of these transport events which is necessary for the functional integrity of the cell is unbalanced when nuclear accumulation of importin α is excessive . This has been observed under various stress conditions , such as heat shock , UV irradiation and oxidative stress [31 , 32] . The cytoplasmic depletion of importin α1 as occurring in SC35M infected mammalian cells may therefore interfere with the nuclear transport of cellular proteins needed for the initiation of an antiviral status or for other vital functions and , thus , represent a new pathogenetic mechanism .
293T ( human embryonic kidney cells ) and A549 ( human lung carcinoma ) cells were grown in DMEM ( Dulbecco's minimal essential medium ) supplemented with 10% FCS ( fetal calf serum; Gibco ) . CEC-32 quail embryo fibroblasts [33] were grown in RPMI-1640 ( Gibco ) supplemented with 5% FCS and 2% chicken serum ( Sigma ) . Influenza A viruses were propagated in 11 day old embryonated chicken eggs . Growth curves were determined in three independent experiments by plaque titration [34] . The recombinant viruses SC35 and SC35M and their mutants have been described before . Briefly , the chicken adapted virus SC35 was originally derived from the seal isolate A/Seal/Mass/1/80 ( H7N7 ) by 35 passages in chicken embryo cells . SC35M was obtained from SC35 by sequential passages in mouse lung [35 , 36] . Monolayers of 293T , A549 and CEC-32 cells were infected with recombinant virus and incubated for 30 min for absorption at 37°C . Cells were washed twice with phosphate-buffered saline ( PBS ) and incubated for 6 h , 12 h and 18 h at 37°C in appropriate medium containing 0 . 2% bovine serum albumin ( MP Biomedicals ) . For transfection , we seeded the cells in 100-mm-dishes and used 10μg pHW2000-SC35-NP , 10 μg pHW2000-SC35M-NP , 30 μg pHW2000-SC35-PB2 , or 30 μg pHW2000-SC35M-PB2 plasmid [4] using LipofectamineTM 2000 ( Invitrogen ) according to the manufacturers protocols . The medium was replaced with fresh growth medium at 6 h posttransfection and incubated for further 48 h for immunoprecipitation assays . 293T , A549 and CEC-32 cells were inoculated with virus at a multiplicity of infection ( MOI ) of 2 for single cycle replication and at an MOI of 10−4 for multicycle replication . Virus inoculum was removed after 30 min of incubation at 37°C , and cells were washed two times with PBS pH5 . Cells were then incubated in the appropriate medium containing 0 . 2% bovine serum albumin at 37°C . At time points 0 , 3 , 6 , 9 , 12 , 15 , 18 , and 24 h for single cycle replication and at time points 0 , 24 , 48 , 72 , and 96 h for multicycle replication , we collected supernatants and determined plaque titers on MDCK cells . The growth curves shown are the average result of two independent experiments . 60-mm-dishes of 293T and CEC-32 cells were infected with a MOI of 2 . At the indicated time points , cells were washed twice with PBS and fractionated in 1ml PBS by using a Mixermill MM301 homogenizer ( Retsch ) at 20 Hz for 20 min . Lysates were mixed with 1% NP40 and separated into a nuclear ( bottom ) and a cytoplasmic ( upper ) fraction by centrifugation on a 20% sucrose cushion at 3000 rpm for 20 min . Nuclear fractions were sonicated for 15 min . Whole lysates and cell fractions were subjected to SDS-polyacrylamide gel electrophoresis followed by Western blot analysis as described [37] . Monoclonal antibodies specific for importin α1 ( BD Biosciences ) were used to detect the importin α1 distribution . As an internal standard , β-actin was determined with specific antibodies ( Abcam ) . The results shown are representatives of three independent experiments . 293T , A549 or CEC-32 cells were grown on glass cover slips and infected at a MOI of 2 with recombinant virus . At the indicated time points after infection , cells were fixed with PBS containing 2% paraformaldehyde and permeabilized with PBS containing 0 . 1% Triton-X-100 . After blocking fixation with 3% BSA in PBS , we incubated the cells for 1h with monoclonal antibodies specific for importin α1 ( BD Biosciences ) , PB2 ( Santa Cruz ) or NP ( kindly provided by M . Schwemmle , Freiburg ) . After incubation with primary antibodies we washed the cells three times with PBS and incubated for further 30 min with either FITC-coupled goat anti-rabbit ( 1/200; Jackson ImmunoResearch Laboratories ) , FITC-coupled goat anti-mouse ( 1/200; Jackson ImmunoResearch Laboratories ) , Rhodamine-coupled donkey anti-goat ( 1/200; Jackson ImmunoResearch Laboratories ) or Rhodamine-coupled goat anti-mouse ( 1/200; Jackson ImmunoResearch Laboratories ) secondary antibodies . Cells were washed three times with PBS and coverslips were mounted on glass plates . Cells were observed in an Axiovert 200M microscope equipped with an ApoTome device ( Zeiss ) . Localization of importin α1 , PB2 , and NP in nucleus , nucleus/cytoplasm and cytoplasm was determined using the microscope by counting cells ( n = 100 ) infected with recombinant viruses . The results shown represent three independent experiments . Transfected cells were washed twice with PBS and collected by centrifugation . Cell pellets were resuspended in 1 ml PBS and sonicated for 15 min . Complexes of importin α1 and viral proteins were determined by co-immunoprecipitation using the ProFoundTM Co-Immunoprecipitation Kit ( PIERCE ) according to the protocols provided by the manufacturer . Briefly , the antibodies specific for PB2 ( Santa Cruz ) or NP ( polyclonal serum raised against A/FPV/Rostock/34 ( H7N7 ) [37] ) were coupled covalently to an amine-reactive gel ( PIERCE ) using the provided coupling buffer ( 0 . 14M sodium chloride , 0 . 008M sodium phosphate , 0 . 002 potassium phosphate , 0 . 01M KCl; pH7 . 4 ) . Cell lysates were added to the antibody-coupled columns and incubated with gentle end-over-end mixing for 2 h at room temperature . Columns were then washed several times with coupling buffer to remove non-specifically bound material and finally eluted using the provided elution buffer ( pH2 . 8 ) . Protein complexes generally eluted in the first three fractions . Eluted immunoprecipitation complexes were then separated by SDS-polyacrylamide gel electrophoresis followed by Western blot analysis . For detection of the PB2 protein in Western blot we used the monoclonal anti-PB2 antibody which was kindly provided by Juan Ortin , Madrid [38] . For the detection of the NP protein we used polyclonal serum raised against A/FPV/Rostock/34 ( H7N7 ) . The results shown represent two independent experiments .
|
The natural hosts of influenza A viruses are aquatic birds . On rare occasions these viruses may be transmitted to humans and then give rise to an influenza pandemic . Human influenza is therefore a typical re-emerging infection . Evidence is increasing that the viral polymerase , an enzyme that has to enter into the nucleus of the infected cell in order to promote replication and transcription of the viral genome , is a major determinant of host range . Thus , in a comparative study of an avian influenza strain and its mouse adapted variant we have previously shown that adaptation to mice depended exclusively on mutations in the polymerase proteins . These findings supported the concept that adaptation of the polymerase to host factors is an important mechanism underlying interspecies transmission . In the present study , we have identified importin α1 , a component of the nuclear pore complex , as such a host factor . We show that adaptive mutations in polymerase subunits improve binding to importin α1 in mammalian , but not in avian cells . As a result , nuclear transport of these proteins and efficiency of replication are enhanced in mammalian cells . These observations demonstrate that the interaction of the viral polymerase with the nuclear import machinery is an important determinant of host range .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"viruses",
"virology"
] |
2008
|
Interaction of Polymerase Subunit PB2 and NP with Importin α1 Is a Determinant of Host Range of Influenza A Virus
|
DNA methylation is an evolutionarily conserved epigenetic modification that is critical for gene silencing and the maintenance of genome integrity . In Arabidopsis thaliana , the de novo DNA methyltransferase , DOMAINS REARRANGED METHYLTRANSFERASE 2 ( DRM2 ) , is targeted to specific genomic loci by 24 nt small interfering RNAs ( siRNAs ) through a pathway termed RNA–directed DNA methylation ( RdDM ) . Biogenesis of the targeting siRNAs is thought to be initiated by the activity of the plant-specific RNA polymerase IV ( Pol-IV ) . However , the mechanism through which Pol-IV is targeted to specific genomic loci and whether factors other than the core Pol-IV machinery are required for Pol-IV activity remain unknown . Through the affinity purification of NUCLEAR RNA POLYMERASE D1 ( NRPD1 ) , the largest subunit of the Pol-IV polymerase , we found that several previously identified RdDM components co-purify with Pol-IV , namely RNA–DEPENDENT RNA POLYMERASE 2 ( RDR2 ) , CLASSY1 ( CLSY1 ) , and RNA–DIRECTED DNA METHYLATION 4 ( RDM4 ) , suggesting that the upstream siRNA generating portion of the RdDM pathway may be more physically coupled than previously envisioned . A homeodomain protein , SAWADEE HOMEODOMAIN HOMOLOG 1 ( SHH1 ) , was also found to co-purify with NRPD1; and we demonstrate that SHH1 is required for de novo and maintenance DNA methylation , as well as for the accumulation of siRNAs at specific loci , confirming it is a bonafide component of the RdDM pathway .
Epigenetic modifications , including DNA methylation , play important roles in gene regulation and are critical for proper development in most eukaryotic organisms . In Arabidopsis thaliana , DNA methylation commonly occurs in all sequence contexts , CG , CHG , and CHH ( H = T , A , C ) . Methylation in the CG context is present in the coding regions of some genes , while methylation in all contexts is present at transposons and other repetitive DNA elements [1] . The de novo methyltransferase , DOMAINS REARRANGED METHYLTRANSFERASE 2 ( DRM2 ) , is required to establish DNA methylation in all sequence contexts . However , three largely distinct pathways function to maintain DNA methylation in each context [1]: CG methylation is maintained by DNA METHYLTRANSFERASE 1 ( MET1 ) , likely during DNA replication in a manner analogous to the mechanism described for CG methylation maintenance in mammals [1]–[3] , CHG methylation is maintained by CHROMOMETHYLASE 3 ( CMT3 ) through a reinforcing loop of histone 3 lysine 9 ( H3K9 ) and DNA methylation [1] , and CHH methylation is maintained by continual de novo methylation by DRM2 in a process termed RNA-directed DNA methylation ( RdDM ) [1] , [4] . Over the last several years many proteins required for RdDM have been identified and characterized , leading to an emerging view of the RdDM pathway [1] , [4] . Biogenesis of the targeting siRNAs requires the plant specific Pol-IV polymerase , which is proposed to generate single stranded RNA transcripts [5] . These transcripts are then processed by RNA-DEPENDENT RNA POLYMERASE 2 ( RDR2 ) and DICER-LIKE 3 ( DCL3 ) to generate 24 nt siRNAs that are methylated on their 3′ ends by HUA ENHANCER 1 ( HEN1 ) [6] and loaded into the ARGONAUTE 4 ( AGO4 ) , AGO6 and AGO9 effector proteins [1] , [4] , [7]–[9] . CLASSY 1 ( CLSY1 ) , a putative chromatin remodeling factor , is also thought to act in this siRNA generating portion of the pathway [10] . In addition to siRNAs , RdDM is also associated with the presence of intergenic noncoding ( IGN ) RNA transcripts [11] . The accumulation of IGN transcripts depends on another plant specific RNA polymerase , Pol-V [11] , and these transcripts are proposed to act as scaffolds to recruit downstream RdDM effector proteins , which in turn directly or indirectly aid in the recruitment of DRM2 to loci that produce both siRNAs and IGN transcripts . Indeed , both AGO4 and SUPPRESSOR OF TY INSERTION 5-LIKE ( SPT5-Like ) , an AGO4 interacting protein [12] , [13] , interact with IGN transcripts in vivo [12] , [14] , and INVOLVED IN DE NOVO 2 ( IDN2 ) , a protein shown to bind double stranded RNA with a 5′ overhang , is also proposed to act in this downstream portion of the RdDM pathway [15] . Despite these advances in our understanding of the RdDM pathway , the mechanism ( s ) through which the two plant specific RNA polymerases , Pol-IV and Pol-V , are targeted to specific genomic loci remain largely unknown [5] , [16] . Recently , some mechanistic insight into the targeting of Pol-V was provided by the identification a protein complex termed DDR [17] that contains three proteins critical for the production of Pol-V dependent IGN transcripts [11] , [14] , [17] , [18] . This complex is proposed to function at the level of recruitment and/or activation of Pol-V at chromatin and contains three stably associated subunits [17]: DEFECTIVE IN RNA-DIRECTED DNA METHYLATION 1 ( DRD1 ) , a putative chromatin remodeling protein [19] , DEFECTIVE IN MERISTEM SILENCING 3 ( DMS3 ) /INVOLVED IN DE NOVO 1 ( IDN1 ) , a protein with homology to the hinge region of structural maintenance of chromosome ( SMC ) proteins [15] , [20] , and RNA-DIRECTED DNA METHYLATION 1 ( RDM1 ) [17] , [18] . In addition to the three DDR complex components , two other proteins affect the accumulation of some Pol-V dependent transcripts and siRNAs . The first , termed RNA-DIRECTED DNA METHYLATION 4 ( RDM4 ) /DEFECTIVE IN MERISTEM SILENCING 4 ( DMS4 ) , is a protein similar to the yeast protein termed Interacts with Pol II 1 ( Iwr1 ) [21] , [22] , and the second , termed NUCLEAR RNA POLYMERASE B2 ( NRPB2 ) , is a Pol II specific subunit [23] . However , the mechanisms through which these additional factors influence Pol-IV and Pol-V targeting and/or activity awaits further investigation . To determine whether Pol-IV interacts with any accessory proteins or transcription factors , which may shed light on the mechanism ( s ) through which it is targeted to transposons and other repetitive DNA elements within the genome , we utilized an epitope tagged version of the largest Pol-IV subunit , NUCLEAR RNA POLYMERASE D1 ( NRPD1 ) , to affinity purify the Pol-IV polymerase . In addition to the previously identified Pol-IV subunits [24] , we identified several known RdDM components , including RDR2 , CLSY1 , and RDM4 in our NRPD1 purification , as well as a new RdDM component , SAWADEE HOMEODOMAIN HOMOLOG 1 ( SHH1 ) . SHH1 contains a cryptic homeodomain and a SAWADEE domain of unknown function and is required for the accumulation of siRNAs at some loci as well as for both de novo and maintenance DNA methylation .
To determine whether SHH1 is required for DNA methylation , a T-DNA insertion mutant , shh1-1 ( Salk_074540C ) , was obtained and the SHH1 transcript levels in this mutant were assessed by semi-quantitative Reverse Transcriptase PCR assays ( Figure 2 ) . In the mutant line , the abundance of transcripts corresponding to the 5′ and 3′ portions of the SHH1 gene were reduced and the full-length transcript was undetectable , suggesting that no wild-type SHH1 protein is produced in this mutant ( Figure 2B ) . This allele was then used to assess the levels of DNA methylation relative to several known DNA methylation mutants at loci controlled by each of the three Arabidopsis DNA methyltransferases ( DRM2 , CMT3 , and MET1 ) by Southern blotting , bisulfite sequencing and methyl-sensitive PCR cutting assays . At a DRM2 controlled locus , MEA-ISR , mutation of SHH1 causes a strong decrease in DNA methylation , reducing the level of methylation to near the level observed in the drm2 mutant ( Figure 3A ) . At a CMT3 controlled locus , Ta3 , mutation of SHH1 had no effect on DNA methylation ( Figure 3B ) . However , at a locus controlled by both DRM2 and CMT3 , AtSN1 , mutation of SHH1 again resulted in reduced DNA methylation ( Figure 3D ) . At the FWA locus , which is controlled by MET1 , the level of CG methylation was not reduced in the shh1 mutant , however , like observed in drm2 and other RdDM mutants , the levels of non-CG methylation were reduced ( Figure 3C ) . To confirm that the decreases in DNA methylation observed in the shh1 mutant were indeed due to disruption of the SHH1 locus , shh1 plants were transformed with a construct containing the SHH1 gene , including its upstream promoter region , and DNA methylation was assessed at the MEA-ISR locus . In the majority of the resulting T1 plant lines DNA methylation was restored to the wild-type level ( Figure 2C ) . Together , these DNA methylation analyses demonstrate that SHH1 is required for DNA methylation and , consistent with its co-purification with NRPD1 , it appears to be specific for the DRM2-mediated DNA methylation pathway . In Arabidopsis , the DRM2 pathway is also required for de novo DNA methylation . To assess de novo DNA methylation , an FWA transgene transformation assay is often employed [28] , [29] . In this assay , an FWA transgene , the expression of which is controlled by DNA methylation , is stably introduced into the Arabidopsis genome . If de novo methylation occurs the transgene is silenced , but if the de novo methylation pathway is impaired the transgene is expressed , leading to a delay in flowering that can be scored as an increase in the number of rosette leaves produced prior to flowering . Upon introduction of an FWA transgene , shh1 mutant plants flowered an average of seven leaves later than untransformed plants ( Figure 3E ) , demonstrating that SHH1 is required to silence the incoming transgene . Furthermore , bisulfite sequencing of the FWA transgene from several wild type Col and shh1 transformants in the T2 generation confirmed that de novo methylation was impaired in the shh1 mutant ( Figure 3F ) . However , consistent with the partial phenotype observed for maintenance methylation ( Figure 3A , 3C , 3D ) , flowering was not as delayed in the shh1 mutant as was observed for the drm2 mutant ( Figure 3E ) . To gain insight into where in the RdDM pathway SHH1 functions , the production of siRNAs and Pol-V dependent noncoding RNA transcripts were assessed in the shh1 mutant . Consistent with the co-purification of SHH1 with the NRPD1 subunit of Pol-IV , siRNAs levels at some loci were significantly reduced in the shh1 mutant ( Figure 4A ) , as was previously observed for clsy1 [10] , another weak DNA methylation mutant [30] . These findings demonstrate that SHH1 plays an important role in the accumulation of siRNAs . To determine whether SHH1 also functions in the accumulation of Pol-V dependent IGN transcripts , the levels of such transcripts at the MEA-ISR and IGN5 loci were assessed . In the clsy1 and shh1 mutants the levels of Pol-V dependent transcripts were unaffected in three biological replicates ( Figure 4B , 4C ) , suggesting that these RdDM components may be specific to the siRNA generating portion of the RdDM pathway . Through the affinity purification of the NRPD1 subunit of the Pol-IV polymerase we were able to further refine the subunit composition of Pol-IV and identify two putative additional components , NRPB9A/D9A/E9A and NRPD5B/E5B . In addition to Pol-IV subunits , our purification also yielded peptides corresponding to several known RdDM components , which like Pol-IV are thought to function in the upstream , siRNA generating portion of the RdDM pathway . These proteins include the RDM4 transcription factor , the CLSY1 putative chromatin remodeling protein , and RDR2 , the RNA-dependent RNA polymerase shown previously to be required for siRNA biogenesis . The finding that these upstream RdDM components co-purify with Pol-IV suggests that this portion of the pathway may be more physically coupled than previously envisioned . Indeed , the approximate stoichiometry of NRPD1 and RDR2 is near 1∶1 ( Table 1 ) and it is likely that tight coupling of the activities of Pol-IV and RDR2 is biologically relevant . For example , this could restrict the activity of RDR2 to transcripts being produced specifically by Pol-IV , thereby reducing the chances that transcripts from other polymerases would be copied into double stranded RNA and channeled into the siRNA-directed DNA methylation pathway , which could lead to off-target DNA methylation and gene silencing . Our affinity purification of NRPD1 also led to the identification of a new component of the RdDM pathway , SHH1 . Mutations in SHH1 result in decreased DNA methylation at loci controlled by the RdDM pathway and in reduced levels of siRNAs , suggesting that SHH1 may function early in the RdDM pathway . Although it is tempting to speculate that SHH1 may be involved in the targeting and/or recruitment of the Pol-IV polymerase to chromatin , as it possesses both a homeodomain and a SAWADEE domain , further experiments will be required to determine whether SHH1 interacts with chromatin and whether it plays a role in the recruitment of Pol-IV to silenced loci .
Plants were grown under long day conditions and the following previously characterized T-DNA insertion mutant lines in the Col ecotype were utilized: cmt3-11 ( SALK_148381 ) [31] , drm2-2 ( SALK_150863 ) [31] , rdr2-2 ( SALK_059661 ) [32] , nrpd1-4 ( SALK_083051 ) [33] , nrpe1-12 ( SALK_033852 ) [34] , clsy1-7 ( SALK_018319 ) [35] . Characterization of the Col shh1-1 ( SALK_074540C ) T-DNA insertion allele is described in Figure 2 . DNA fragments containing the NRPD1 , RDR2 , CLSY1 , or SHH1 genes , including their endogenous promoter regions , were amplified by PCR using the primers listed in Table S2 . For NRPD1 , a pEarlyGate302 plasmid [36] containing the NRPD1 gene and promoter [37] was used as the DNA template while for RDR2 , CLSY1 , and SHH1 genomic DNA isolated from the Col ecotype served as the DNA template . PCR products were cloned into the pENTR/D-TOPO vector ( Invitrogen ) per manufacturer instructions . For NRPD1 , SHH1 and RDR2 , carboxy-terminal tags ( Table S1 ) were inserted into a 3′ Asc I site present in the pENTR/D-TOPO vector . For CLSY1 , an amino-terminal BLRP-3×HA tag ( Table S1 ) was inserted into a Kpn I restriction site engineered into the CLSY1 genomic sequence upstream of the start codon through quickchange site directed mutagenesis ( Stratagene ) per manufacturer instructions . The described pENTR/D constructs were digested with the Mlu I restriction enzyme and then recombined into one of two modified gateway destination vectors , which differ only in their plant drug resistance gene , using LR Clonase ( Invitrogen ) per manufacturer instructions . For the NRPD1 constructs the destination vector used contains a gene conferring resistance to the BASTA herbicide and for the RDR2 , SHH1 and CLSY1 constructs the destination vector used contains a gene conferring resistance to Hygromycin . Both destination vectors are based on the pEarleyGate302 vectors described in [36] but were modified as previously described [38] , [39] , such that they contain the BirA gene , the product of which transfers a biotin group onto a lysine residue present in the BLRP epitope tag , under the control of an ACTIN promoter . These destination vectors were then transformed into the AGLO strain of Agrobacterium by electroporation . Arabidopsis plants carrying the nrpd1-4 , shh1-1 , rdr2-2 , or clsy1-7 mutant alleles were transformed with the various NRPD1 , SHH1 , RDR2 , or CLSY1 epitope tagged constructs , respectively , by the floral dip method as described in [40] . Transformed plants were selected using either BASTA or hygromycin and transformants containing only a single insertion site were determined by segregation analysis in the subsequent generation . Approximately 10 g of flower tissue from NRPD1-3×Flag and NRPD1-3×Flag-BLRP transgenic T4 plants , or from Col plants as a negative control , were ground in liquid nitrogen , and resuspended in 50 mL of lysis buffer ( LB: 50 mM Tris pH7 . 6 , 150 mM NaCL , 5 mM MgCl2 , 10% glycerol , 0 . 1% NP-40 , 0 . 5 mM DTT , 1 µg/µL pepstatin , 1 mM PMSF and 1 protease inhibitor cocktail tablet ( Roche , 14696200 ) ) . The tissue was then homogenized by douncing and centrifuged at 4°C in an SS34 rotor for 25 minutes at 12 , 500 rpm . Each supernatant was incubated at 4°C for 2 . 5 hours with 200 µL of Dynabeads ( M-270 Epoxy , Invitrogen , 143 . 01 ) conjugated with a Flag antibody ( Sigma F 3165 ) according to manufacturer instructions . The Flag beads were then washed twice with 40 mL of LB and five times with 1 mL of LB . For each wash , the beads were rotated at 4°C for 5 minutes . Proteins were then released from the Flag beads during five room temperature incubations with 150 µL of 3×Flag peptide ( Sigma , F 4799 ) at a concentration of 100 µg/mL . Mass spectrometric analyses were conducted as described in [17] . For comparison with the previously published Pol-IV affinity purification and MS analyses [24] , peptide coverage maps ( Figure S1 ) were generated and the percent coverage ( Table 1: “% Coverage” ) of each Pol-IV subunit was calculated using only the uniquely mapping peptides recovered from the MS analysis , as was done in Ream et al . [24] . For the co-IP experiments between NRPD1 and RDR2 , CLSY1 , and SHH1 , 0 . 5 g–1 g of tissue from each parental line as well as F1 plants expressing complementing , epitope tagged versions of both proteins were used . For the co-IP between NRPD1 and RDM4 , 1 g of tissue from either Col plants or plants expressing a complementing , epitope tagged version of NRPD1 was used . For each experiment , the tissue as ground in liquid nitrogen with lysis buffer ( LB ) ( 2 . 5 mL per 0 . 5 g of tissue ) and the lysate was cleared by centrifugation at 13 , 200 rpm in microfuge tubes for 10 minutes at 4°C . The supernatants were incubated with 100 µL of either Myc agarose ( 50% slurry Covance AFC-150P ) or M2 Flag agarose ( 50% slurry , Sigma A2220 ) beads for 2 hours at 4°C with rotation . The beads were then washed 5 times , for 5 minutes , with 1 mL of LB and resuspended in 50 µL of SDS-PAGE loading buffer . 35 µL or 9 µL of input and bead eluate were run on 4–12% SDS-PAGE gels in Figure 1D–1F or Figure 1C , respectively , and the various proteins were detected by western blotting using either ANTI-FLAG M2 Monoclonal Antibody-Peroxidase Conjugate ( Sigma A 8592 ) at a dilution of 1∶5000 , c-Myc 9E10 mouse monoclonal antibody ( Santa Cruz Biotechnology , sc-40 ) at a dilution of 1∶5000 , or anti-RDM4 at a dilution of 1∶2500 . Goat anti-mouse IgG horseradish peroxidase ( Thermo scientific , 31430 ) or goat anti-rabbit IgG horseradish peroxidase ( Thermo scientific , 31460 ) was used at a dilution of 1∶5000 as the secondary antibody . All westerns were developed using ECL Plus Western Blotting Detection System ( GE healthcare RPN2132 ) . Genomic DNA isolation and Southern blot analyses at the MEA-ISR and Ta3 loci were conducted as described in [38] . Bisulfite treatment of genomic DNA , amplification of the FWA endogene , cloning and sequencing of the resulting PCR products were as described in [38] . For the Col control and each mutant ∼10–15 clones were analyzed . For bisulfite analysis of the FWA transgene , genomic DNA was extracted from pooled T2 plants from individual T1 transformants and digested with the Bgl II restriction enzyme , which specifically cuts within the FWA endogene , prior to bisulfite conversion . The AtSN1 cutting assay was conducted as described in [41] except the uncut samples were amplified for 25 cycles , the cut samples for 32 cycles , and the amplification products were visualized by agarose gel electrophoresis . FWA transformation , T1 selection and flowering time analysis were as describe in [15] . siRNAs for northern blotting were isolated as follows: 1 g of flower tissue from each genotype was ground in liquid nitrogen with a mortar and pestle , incubated with 10 mL of trizol reagent ( Invitrogen 15596-026 ) at room temperature for 10 minutes , and mixed with 2 mL of chloroform . The samples were then centrifuged at 13 , 000 rpm for 30 minutes at 4°C and the supernatants were mixed with one volume of cold isopropanol . Samples were then centrifuged at 13 , 000 rpm for 30 minutes at 4°C and the pelleted RNA was resuspended in 500 µL of DEPC-treated water . These total RNA preparations were then enriched for small RNAs through a polyethelene glycol ( PEG ) precipitation step . One volume of a 20% PEG 8000/2M NaCl solution was added to each RNA preparation and then centrifuged at 13 , 000 rpm for 15 minutes at 4°C . The supernatant , containing the small RNA molecules , was collected and precipitated with 0 . 8 volumes of cold isopopanol as described above . ∼30 µg of the resulting small RNA samples were run on 15% polyacrlyamide-7M Urea gels and transferred to Hybond-NX membranes ( Amersham RPN303T ) . Membranes were blocked using 10 mL of ULTRhyb-Oligo buffer ( Ambion AM8663 ) and probed with 5′ end radiolabeled oligos as described in [42] . SHH1 expression was assessed by Reverse Transcriptase PCR using total RNA extracted from 100 mg of flower tissue using the Trizol reagent and cDNAs were synthesized using Super ScriptII ( Invitrogen ) per manufacturer instructions . Detection of Pol-V dependent transcripts at the MEA-ISR and IGN5 loci were conducted as described in [17] . The data represents three biological replicates with standard errors . To quantify the levels of each transcript the signal from the ACTIN , MEA-ISR , and IGN5 primer pairs were determined relative to a standard curve generated using sonicated DNA from Col plants . The levels of the MEA-ISR and IGN5 transcripts where then normalized to the level of the ACTIN transcript . Since a different standard curve was used for each of the three different biological replicates , the values for MEA-ISR/ACTIN and IGN5/ACTIN for each genotype within a single biological replicate were normalized to the signal of MEA-ISR/ACTIN and IGN5/ACTIN observed for the Col sample from the same biological replicate ( with this signal being set to 100 ) , allowing comparison of the three different sets of data .
|
In eukaryotic organisms many systems have evolved to ensure the proper expression of genetic information within each cell , and when these systems malfunction genes can be mis-expressed and cause numerous diseases . One such system involves cytosine DNA methylation , an epigenetic modification that is commonly associated with the repression of transcription and is critical for genome integrity and proper development . In the plant model organism Arabidopsis thaliana , DNA methylation is catalyzed by DOMAINS REARRANGED METHYL-TRANSFERASE 2 , a homolog of the mammalian de novo DNA methyltransferase family , and is targeted to specific loci by small interfering RNAs ( siRNAs ) through a pathway termed RNA–directed DNA methylation ( RdDM ) . Here we present analysis of our purification of RNA polymerase IV , the polymerase thought to initiate biogenesis of the targeting siRNAs . In addition to the previously identified polymerase IV subunits , we found that several other proteins required for RdDM also co-purify with RNA polymerase IV . Furthermore , we identified a new component required for RdDM , SAWADEE HOMEODOMAIN HOMOLOG 1 ( SHH1 ) . Together these findings serve to increase our understanding of DNA methylation by further expanding our knowledge regarding the initial siRNA generating phase of the RdDM pathway .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"genetics",
"plant",
"genetics",
"epigenetics",
"biology",
"dna",
"modification",
"genetics",
"and",
"genomics"
] |
2011
|
SHH1, a Homeodomain Protein Required for DNA Methylation, As Well As RDR2, RDM4, and Chromatin Remodeling Factors, Associate with RNA Polymerase IV
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Blinding trachoma is targeted for elimination by 2020 using the SAFE strategy ( Surgery , Antibiotics , Facial cleanliness , and Environmental improvements ) . Annual mass drug administration ( MDA ) with azithromycin is a cornerstone of this strategy . If baseline prevalence of clinical signs of trachomatous inflammation – follicular among 1-9 year-olds ( TF1-9 ) is ≥10% but <30% , the World Health Organization guidelines are for at least 3 annual MDAs; if ≥30% , 5 . We assessed the likelihood of achieving the global elimination target of TF1-9 <5% at 3 and 5 year evaluations using program reports . We used the International Trachoma Initiative’s prevalence and treatment database . Of 283 cross-sectional survey pairs with baseline and follow-up data , MDA was conducted in 170 districts . Linear and logistic regression modeling was applied to these to investigate the effect of MDA on baseline prevalence . Reduction to <5% was less likely , though not impossible , at higher baseline TF1-9 prevalences . Increased number of annual MDAs , as well as no skipped MDAs , were significant predictors of reduced TF1-9 at follow-up . The probability of achieving the <5% target was <50% for areas with ≥30% TF1-9 prevalence at baseline , even with 7 or more continuous annual MDAs . Number of annual MDAs alone appears insufficient to predict program progress; more information on the effects of baseline prevalence , coverage , and underlying environmental and hygienic conditions is needed . Programs should not skip MDAs , and at prevalences >30% , 7 or more annual MDAs may be required to achieve the target . There are five years left before the 2020 deadline to eliminate blinding trachoma . Low endemic settings are poised to succeed in their elimination goals . However , newly-identified high prevalence districts warrant immediate inclusion in the global program . Intensified application of the SAFE strategy is needed in order to guarantee blinding trachoma elimination by 2020 .
Trachoma remains the world’s leading infectious cause of blindness , although it has disappeared from much of the developed world due to advances in hygiene and sanitation . The World Health Organization ( WHO ) has classified it amongst the neglected tropical diseases ( NTDs ) , as where it remains , it is concentrated among the world’s poorest populations . These communities live “at the end of the road , ” beyond the reach of development infrastructure , and lack access to the basic sanitation measures that prevent disease transmission . Currently , WHO estimates that 232 million people live in endemic areas , 21 . 4 million have active trachoma , and 7 . 3 million suffer from trachomatous trichiasis ( TT ) and are at immediate risk of becoming blind [1–3] . However , through implementation of the SAFE strategy ( Surgery , Antibiotics , Facial cleanliness , and Environmental improvements ) , we hope to reduce active disease , defined as trachomatous inflammation—follicular among children aged 1–9 ( TF1–9 ) [4] to below 5% prevalence in every endemic district by 2020 . As over 100 repeated infections are required to cause the scarring that leads to blindness [5] , this will ensure that no one accrues sufficient infections to progress to the disease’s blinding end stages , thus accomplishing elimination of blinding trachoma . In order to achieve sustainable elimination , effective implementation of each component of the SAFE strategy is essential . Treatment with Zithromax ( azithromycin ) successfully clears individual infections [6 , 7] , but many factors affect the impact of mass drug administration ( MDA ) at the population level , such as MDA coverage [8 , 9] and concurrent implementation of environmental improvements and hygiene education [10 , 11] . Current recommendations from WHO are to perform at least three annual MDAs prior to an impact survey when baseline TF1–9 prevalence is 10–29% , and at least five MDAs before an impact survey when baseline TF1–9 prevalence is ≥30% [12] . These benchmarks were instituted in 2010 as an update to the original guidelines from 2006 [13] , which proved insufficient for some high endemic areas . Many perceive these benchmarks to suggest that a certain number of years of treatment “guarantee” elimination , but this may be incorrect . Even in relatively low-endemic regions , elimination may take more than three annual MDAs [14 , 15] . Three treatment rounds were also not sufficient for sustained elimination at roughly 30% baseline TF1–9 prevalence [16] . Modeling suggests that where TF1–9 prevalence is ≥50% , five years of annual treatment is likely not enough [17 , 18] . Indeed , 7–10 MDAs may be necessary [9] . Given the increase in available research and programmatic data , these recommendations can be assessed and refined to allow trachoma control programs to appropriately plan and budget for elimination . In this study , we used a global dataset of baseline and impact surveys to assess the evidence base for the effect of MDA on trachoma prevalence , with the goal of determining whether improved recommendations can be developed in order to improve programmatic efficiency and ensure continuous progress towards elimination .
In order to effectively coordinate the Zithromax donation on behalf of Pfizer , the International Trachoma Initiative ( ITI ) maintains a comprehensive database of trachoma prevalence and Zithromax treatments performed around the world . This database allows ITI to effectively allocate drugs , and conduct forecasting and planning of programmatic scale-up [19 , 20] . Data sources include published literature reports and annual applications for Zithromax submitted to ITI , personal communication with national program staff and researchers , and targeted review of other sources . This study includes database updates through February 2014 . Each observation in the database includes the following information , if available: active trachoma prevalence and the clinical sign used as an active indicator ( TF or TF/TI ) , trachomatous trichiasis ( TT ) prevalence , age range of individuals surveyed for TF and TT , survey location , survey year , survey design and sampling methodology , and data source . Where multiple surveys were conducted at a given location , they were coded to indicate if they preceded or followed treatment . Where treatment was conducted , some entries include estimates of district population , reported antibiotic distribution in doses , and coverage ( estimated as doses distributed divided by total population ) . There is substantial variation between some of the surveys represented in the database . For example , the indicator used for active trachoma is a measure of circulating disease in a community . Though the WHO standard is to measure trachomatous inflammation—follicular ( TF ) among children aged 1–9 years ( TF1–9 ) , some surveys assessed TF among school-aged children or children under 6 years old . All surveys included in the database used the simplified clinical grading system for trachoma [4] , but some measured TF as an indicator for active trachoma and others used a combination of TF and TI ( trachomatous inflammation , intense ) . While cross-sectional population-based prevalence surveys ( PBPS ) are considered the gold standard for assessing trachoma prevalence at a given location [19 , 21] , data from trachoma rapid assessments ( TRAs ) and acceptance sampling trachoma rapid assessments ( ASTRA ) were reported from some locations . The trachoma community experimented over several years with alternative methods for providing evidence to start programmatic implementation , however , neither have been routinely adopted [21] . TRAs are designed to provide biased prevalence estimates , as they prioritize finding trachoma where it exists [22 , 23] . In most cases , these TRAs were used to determine areas where a PBPS should be implemented . Prevalence surveys are intended to take place using the district as the implementation unit ( where district is defined as an administrative unit of 100 , 000–250 , 000 people ) , but are sometimes performed at a larger geographic area , such as the zonal level , if trachoma is expected to be hyperendemic [12] . Sub-district analyses are also required if TF1–9 prevalence is below 10% at district level [12] . We assessed the factors affecting change in prevalence over time in pairs of surveys collected at the same location . The database initially contained 2365 surveys . These represented 29 countries and were performed between the years 1992–2013 . We censored 156 TRAs and 46 ASTRAs . Of the 2157 remaining surveys , 353 represented follow-up after treatment , 1318 represented baseline that preceded treatment , and the remaining 486 represented surveys that did not prompt treatment . All 1671 surveys that preceded or followed treatment were assigned unique IDs by location and matched . Matches were parsed into pairs corresponding to two prevalence surveys in the same location and ordered chronologically . Matched pairs were merged with data on treatment and coverage that used the same unique IDs by location . In areas where follow-up assessment was conducted at a smaller implementation level than the baseline survey ( e . g . district surveys following a zonal survey ) , the follow-up data was averaged across the original unit of implementation to allow comparison . We investigated adjustment factors where active disease prevalence was not measured as TF1–9 . In settings with TF prevalence exceeding 20% , the age-prevalence peak may shift such that younger individuals are more likely to have a greater share of disease burden [5 , 24–26] . However , data from the PRET trial showed a very high level of correlation between active disease among children 0–5 and 1–9 years old [27 , 28] . Thus , we did not apply a scaling factor where TF prevalence was assessed among children under six . As the only surveys in the dataset that sampled children aged 6–15 were conducted in Vietnam , where school attendance is high and prevalence peaks among school-aged children [29] , no adjustment was applied . If TF/TI was used as an active indicator rather than TF alone , it was adjusted by a factor of 0 . 87 . This was calculated as an average of the relative difference between TF and TF/TI prevalences in published studies [30–33] . Finally , among surveys for which a year range was specified , the survey year was coded as the median of that range or the most recent year of a two-year range . Pairs were identified as representing MDA if any treatment was recorded between the survey dates , or if ITI coding indicated that MDA had taken place . All other pairs were considered to represent “background” prevalence change . Variables were created representing annual MDAs between treatment ( number of MDAs that took place between baseline and follow-up surveys ) , number of years between surveys , number of years before treatment ( years between baseline survey and first MDA ) , number of years since treatment ( years between first MDA and follow-up survey ) , total annual MDAs ( number of MDAs before the follow-up survey , regardless of whether they took place after the baseline survey ) , skips between ( “treatment holiday , ” or skipped years between annual MDAs ) , and total skipped years ( any years without treatment before the follow-up survey and after the beginning of treatment ) . See Fig . 1 for a representation of this coding scheme . As all temporal information in the database is based on calendar years , discrimination between time intervals smaller than a year was not possible . Thus , a given “year” could be as short as 12 months or as long as 23 ( e . g . , if a baseline survey took place at the beginning of one calendar year and an MDA took place at the end of the next calendar year ) . Coding proceeded on the assumption that baseline surveys would be followed by treatment , while impact surveys followed treatment . Instances of anomalous code were manually inspected and cleaned . The final dataset had 170 pairs of surveys corresponding to baseline and follow-up after MDA , and 112 pairs that did not correspond to MDA . All of these represented population-based prevalence surveys . In order to perform ordinal logistic regression modeling ( described below ) , we created a categorized ordinal variable for TF1–9 . TF1–9 categories were specified based on the thresholds that define current WHO recommendations for treatment [12] . An additional category , in which prevalence exceeded 50% , was added to represent hyperendemic settings where trachoma is entrenched ( see Fig . 2 ) . These thresholds correlate with number of rounds MDA applied , and often years between surveys , and thus categorize the data into similar groups . Coverage data , applicable only to the treatment dataset ( since the background dataset did not by definition involve MDA ) , was only reported in 2010–2012 . Therefore , coverage data was available for the end of the treatment cycle for only those survey pairs whose treatment interval included at least one of these years: this was true of just 52 ( approximately 31% ) of the survey pairs in the treatment dataset . We therefore omitted this variable from modeling . The final dataset contained 282 pairs of surveys , which were conducted between 1996–2013 . We used SAS 9 . 4 ( SAS Institute , Cary , NC , USA ) to produce descriptive statistics of the dataset ( Table 1 ) . Generalized linear models were fit to the “background” dataset , which represented change in prevalence in the absence of MDA , and the “treatment” dataset , which represented MDA’s effect on prevalence . The outcome variable for each was defined as TF1–9 prevalence at follow-up . Stepwise selection and backwards elimination strategies , with entry and stay criteria of α = 0 . 10 , respectively , were used for model building , with all possible variables included at the outset . Aikake Information Criterion ( AIC ) was used to compare models . The assumption of linearity was confirmed using an overall F test , as well as by plotting the residuals of the explanatory variables . Univariate and multivariate logistic regression models were fitted to banded TF1–9 prevalence at follow-up ( see Fig . 2 for categories ) to demonstrate the odds of reduction to lower categories of follow-up TF1–9 prevalence . Stepwise selection and backwards elimination were again used to determine final model candidates . Maximum likelihood was used to estimate the coefficients for model predictors [34] . Collinearity was assessed for linear modeling using variance inflation factors , and for logistic modeling using condition indices and variable decomposition factors , calculated with a SAS macro [35] . Given a condition index of ≥30 , we investigated variables associated with decomposition factors ≥0 . 5 [34] . In the treatment dataset , 28 observations coded as representing MDA but missing data on treatment were dropped from the linear and logistic models due to missing predictor values . Pairs dropped included data from Ghana , Nigeria , Tanzania , The Gambia , and Vietnam .
Using several selection strategies in generalized linear modeling , we included the following variables in the final model for the treatment dataset: baseline TF1–9 prevalence ( 0 . 13 , 95% CI: -0 . 17 , 0 . 43 ) , rounds of MDA ( -2 . 59 , 95% CI: -4 . 47 , -0 . 71 ) , years since treatment began ( 1 . 80 , 95% CI: 0 . 67 , 2 . 93 ) , years before treatment began ( -0 . 94 , 95% CI: -1 . 79 , -0 . 17 ) , and the interaction between rounds of MDA and baseline TF1–9 prevalence ( 0 . 062 , 95% CI: 0 . 003 , 0 . 12 ) . These were significant at the 0 . 05 level , with the exception of baseline prevalence , which also exhibited collinearity with the interaction term but had to be retained for a hierarchically well-formulated model . The final multivariate model , specified below , had an r2 value of 0 . 40: TFPr2 = 3 . 22 + 0 . 13 * TFPr1–2 . 59 * Rounds MDA + 1 . 80 * Years Since Treatment Start - 0 . 94 * Years Before Treatment + 0 . 062 * ( TFPr1 * Rounds MDA ) In contrast , the best model fit to the background dataset ( without MDA ) accounted for only about 8% of the variation in the data , demonstrating that these model parameters do not do a good job of accounting for TF1–9 prevalence change in the absence of treatment . Univariate ordinal logistic regression performed on the treatment dataset ( Table 2 ) demonstrated that increased baseline TF1–9 prevalence was significantly associated with reduced likelihood of achieving lower categories of follow-up TF1–9 prevalence . Years since treatment began and total skipped years since treatment began were also significant . Increased number of annual MDAs and years skipped between annual MDAs also showed a non-significant trend towards association with reduced likelihood of reduction . A multivariate ordinal regression model fitted to the treatment dataset was used to model the odds of reduction to a lower category of follow-up TF1–9 prevalence . The proportional odds assumption was satisfied for this model . An increase in the following was associated with significantly lower odds of TF1–9 prevalence reduction ( see Fig . 3 ) : increased baseline TF1–9 prevalence ( OR = 0 . 92 , 95% CI 0 . 89–0 . 94 ) , and years since treatment began ( 0 . 77 , 95% CI = 0 . 61–0 . 97 ) . However , an increase in annual MDAs ( OR 1 . 56 , 95% CI 1 . 16 , 2 . 10 ) and years before treatment ( OR 1 . 30 , 95% CI = 1 . 08 , 1 . 57 ) were associated with significantly increased odds of TF1–9 prevalence reduction . Censoring of the “super-district” observations , which used mean follow-up TF1–9 prevalence to account for baselines measured at the zonal level , did not have a significant effect on these ORs . The unmodeled data demonstrated a general trend of reduction from baseline to follow-up in the treatment dataset , though this was more pronounced at lower baseline prevalence levels ( see Fig . 4 ) . Correspondingly , there was a significantly greater probability of reduction to a lower prevalence category at lower TF1–9 prevalence levels in the multivariate logistic model ( see Fig . 5 ) . While the model predicted a 75% probability of reduction to below 10% given 3 treatment annual MDAs at 20% baseline TF1–9 prevalence , the probability of reduction to below 10% given a 30% baseline TF1–9 prevalence was 56% . At higher baseline endemicities , the point estimate for probabilities became lower , and the error increased . So while a 56% probability of reduction was predicted for a baseline TF1–9 prevalence of 30% given 3 annual MDAs , this was not statistically significant . As number of MDAs increased , the confidence interval narrowed , such that a 64% chance of reduction from 30% baseline was predicted for 5 treatment rounds . Even if the number of MDAs was increased to 10 for an area at 50% endemicity , the probability of reduction ( estimated at 42% ) was non-significant . Although various simple measures of skipped years were not significant in the multivariate model , an increase in years since treatment began was significantly associated with reduced odds of prevalence reduction , such that adding a year to the treatment cycle ( without a corresponding increase in treatment rounds ) led to about a 5% reduction in the probability of success achieving reduction below 10% . The model also predicts increasing success with a waiting period before implementing treatment .
In this study , using data collected in a programmatic context over ITI’s 15-year history , we have demonstrated that the context in which mass drug administration for trachoma is conducted may be as important as the number of annual rounds implemented . Hyperendemic districts ( baseline TF1–9 prevalence >50% ) should implement at least seven MDAs before considering an impact survey , while relatively low-endemic districts ( <20% baseline TF1–9 prevalence ) likely could resurvey after three annual MDAs . However , our models are built using data that represents the imperfect world in which trachoma control programs have operated , with skipped treatment years and little data on antibiotic coverage and improvements in hygiene and sanitation . The context in which MDA is implemented is also crucial , and is likely key to successful elimination of trachoma . Some of the principles demonstrated by our models regarding treatment context are well recognized . Trachoma tends to decline slowly on its own , probably due to the effects of gradual development and improvements in hygiene and sanitation [36 , 37] . This is likely represented by the variable for years before treatment , which predicts that in the absence of treatment ( or before treatment ) , there is a modest decrease in prevalence at follow-up . Furthermore , trachoma is more likely to reemerge after treatment in higher prevalence settings [8 , 18 , 38 , 39] , while in lower prevalence settings it disappears after treatment [40 , 41] . The variable for baseline TF1–9 prevalence demonstrates that the effect of MDA varies at different endemicities . We had limited ability to investigate interactions between variables due to insufficient power and a small number of potential variables . As such , although the interaction term in the linear models shows that a higher baseline prevalence is less responsive to treatment , neither this term nor a potentially interesting interaction between baseline prevalence and skipped years could be included in the logistic models due to unacceptable levels of multicollinearity . However , in all the models , skipped years , or additional years since treatment began made reduction less likely . We see this effect despite the fact that a single “year” in our data may represent anywhere from 12 to 23 months , given that reporting is agnostic to timing of surveys and treatment during the calendar year . We assessed the combined effects of these variables by generating predictions for various treatment schemes . The multivariate logistic model predicts that increasing the number of annual MDAs leads to a higher probability of TF1–9 prevalence reduction . No matter how many continuous MDAs are conducted , achievement of the elimination target levels becomes less likely as baseline prevalence increases . Of the ten districts in the treatment dataset with baseline TF1–9 prevalence >50% , none showed reduction to below 5% , and only one achieved reduction to below 10% , despite the application of up to seven annual MDAs ( see Fig . 4 ) . This limits the capacity of the model to predict successful reduction in hyperendemic conditions . Even at TF1–9 prevalences between 30–50% , only about half of the districts achieved reduction below 10% . The model suggests , therefore , that low endemic districts ( <20% ) are likely to achieve reduction to below 10% after three annual MDAs , and should be resurveyed at that time . However , at 30% baseline TF1–9 prevalence , the model predicts a 56% chance of reduction to below 10% . This probability dwindles as baseline TF1–9 prevalence increases . From the limited available evidence , even 7 annual MDAs were insufficient in hyperendemic districts ( >50% TF1–9 prevalence ) to make a meaningful public health difference . In such programmatic contexts , over 7 annual MDAs may be necessary to achieve the target . These findings are supported by other studies: in a programmatic context in Mali , three annual rounds of MDA were not sufficient at baseline prevalences of close to 30% [16] , while seven to ten years of annual treatment were also suggested by a research study in a hyperendemic setting in Tanzania [9] . Once again , our models do not represent the effect of MDA conducted in controlled conditions . It is likely that many of the districts in our dataset did not achieve their prevalence reduction goals due to inconsistent application of the SAFE strategy . For example , most of the high endemic districts experienced discontinuous treatment . As described , skipped treatment years significantly decrease the probability of TF1–9 prevalence reduction . Our models also omit data on other factors known to influence the effect of MDA , such as treatment coverage [8] . Coverage data was available in such a small subset of surveys that it could not be included in our models; less than half of the districts surveyed in 2010–12 reported any kind of MDA coverage measures to ITI . However , even if more programs provided these estimates , the quality of coverage data currently collected by trachoma control programs is known to vary greatly [42] . We also lack measures of hygiene and environmental factors , the F and E components of the SAFE strategy . Reduction in trachoma has been associated with clean faces and hygiene indicators [43] , latrine provision [24 , 44] , and insecticide spraying to control flies , which can act as trachoma vectors where they are prevalent [45 , 46] . Direct causative evidence is lacking to guide the development of metrics that could be used by control programs . Nonetheless , the endemic equilibrium that leads to reemergence of trachoma is likely dependent on environmental factors [5 , 17 , 39] . If the setting in which antibiotic treatment is applied is unchanged , “elimination” will be transient at best . Despite these omissions , our results are valuable precisely because they represent the effect of MDA as it is conducted by trachoma control programs . Although low endemic districts are likely to succeed in their elimination goals under the current WHO recommendations , we must consider carefully how to support the remaining districts with baseline TF1–9 prevalence over 30% . With just under five years left before the 2020 elimination goal , those districts must plan for intensified treatment programs . They may consider alternatives such as targeted treatment [47] or biannual treatment [8 , 48] . There may be substantial cost savings associated with proposed integration of efforts to survey and distribute treatment with programs for other NTDs [49–51] . Most importantly , we must recognize that in the imperfect context in which programs on the ground operate , adding more annual MDAs without regard to coverage , programmatic continuity , and underlying environmental context will not guarantee trachoma elimination . In order to continue our progress towards trachoma elimination , we must emphasize the WHO recommendations that call for programmatic continuity , which should be attainable even in countries where program implementation is difficult , given increased donor support . We must also emphasize the importance of antibiotic coverage , hygiene education , and sanitation improvements . This should start at the level of the data we collect . We cannot track progress , measure success , or even understand what success looks like for variables we do not measure . Trachoma serves as an object lesson that antibiotic interventions , such as azithromycin mass treatment , can only go so far in the context of poor development . With increasing rounds of MDA , we may eventually reduce TF1–9 prevalence to below 5% , even in the most high-endemic districts remaining . Our data suggests that such districts ought to prepare for extended MDA timelines . However , we should not rely on antibiotics alone to achieve trachoma elimination . The most effective and efficient solution is likely to implement all aspects of the SAFE strategy , which recognizes that though high-coverage , continuous MDAs are essential , clean water and good hygiene may be as important . For programs seeking real and sustainable elimination , it may be that no amount of time is long enough to achieve trachoma elimination without lasting change of the environment in which it persists .
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Trachoma , the world’s leading infectious cause of blindness , is scheduled for elimination by 2020 . Reaching this elimination target depends on successful implementation of the SAFE strategy ( Surgery , Antibiotics , Facial cleanliness , and Environmental improvements ) . Annual mass antibiotic distributions are key to breaking the cycle of transmission in a community . However , it is not clear how many annual mass treatments need to be carried out in order to achieve elimination . Our study analyzes the effect of mass antibiotic distribution on different baseline prevalence levels of trachoma , in order to assess factors that affect the success of reaching elimination goals . We find that the prevailing belief , which suggests that 3 annual mass treatments can achieve local elimination of trachoma at prevalences between 10–30% , and 5 annual mass treatments for districts above this benchmark , is probably incorrect . In fact , much longer intervals may be required with “business as usual” programmatic strategies , which often include skipped years of treatment . Districts with high prevalence levels may require more intense treatment strategies to eliminate trachoma . Intensified recommendations must be implemented without delay in order to reach the 2020 elimination deadline .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Mass Drug Administration for Trachoma: How Long Is Not Long Enough?
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Pemphigus vulgaris ( PV ) is a life-threatening autoimmune mucocutaneous blistering disease caused by disruption of intercellular adhesion due to auto-antibodies directed against epithelial components . Treatment is limited to immunosuppressive agents , which are associated with serious adverse effects . The propensity to develop the disease is in part genetically determined . We therefore reasoned that the delineation of PV genetic basis may point to novel therapeutic strategies . Using a genome-wide association approach , we recently found that genetic variants in the vicinity of the ST18 gene confer a significant risk for the disease . Here , using targeted deep sequencing , we identified a PV-associated variant residing within the ST18 promoter region ( p<0 . 0002; odds ratio = 2 . 03 ) . This variant was found to drive increased gene transcription in a p53/p63-dependent manner , which may explain the fact that ST18 is up-regulated in the skin of PV patients . We then discovered that when overexpressed , ST18 stimulates PV serum-induced secretion of key inflammatory molecules and contributes to PV serum-induced disruption of keratinocyte cell-cell adhesion , two processes previously implicated in the pathogenesis of PV . Thus , the present findings indicate that ST18 may play a direct role in PV and consequently represents a potential target for the treatment of this disease .
Pemphigus refers to a group of autoimmune blistering disorders which affect mucocutaneous tissues [1 , 2] . Pemphigus vulgaris , the most common subtype of the disease , is estimated to have a worldwide annual incidence of 0 . 76–6 . 7 new cases per million [1] and is between 4- to 10-fold more common among Jews as compared with other populations [3] . The disease is characterized by the development of flaccid blisters over the skin and mucosal surfaces , which rupture easily to form large painful erosions with little tendency to heal and which , if left untreated , increase the probability of life-threatening complications [1] . Since the advent of corticosteroid treatment , mortality has dropped to 10% , though morbidity is still considerable [1] . PV is traditionally considered to result from abnormal desmosome function caused by circulating auto-antibodies ( auto-Abs ) directed against desmosomal antigens , mainly desmoglein ( Dsg ) 3 and Dsg1 [2] , which in turn leads to loss of adhesion ( acantholysis ) between keratinocytes . More recently , additional pathogenetic mechanisms , not directly involving desmosome destabilization , have also been suggested to be operative in PV IgG-induced blister formation , such as activation of apoptosis; increased pro-inflammatory cytokine secretion; aberrant cell-cell signaling; and activation of muscarinic receptors uniquely expressed by basal keratinocytes [4] . The propensity to develop the disease is believed to be to a large extent genetically determined as attested by familial occurrence of PV , the presence of circulating PV IgG Abs in healthy first-degree relatives of PV patients and ethnic clustering [3 , 5–7] . This in turn offers the possibility to identify elements of importance to PV etiology through a genetic approach . We recently conducted a genome wide association study ( GWAS ) in a genetically homogenous population of Jewish extraction , followed by replication in two cohorts , and identified an association between PV and the ST18 gene locus [8] . Although ST18 encodes a transcription factor possibly regulating apoptosis and inflammation [9] , two processes of potential relevance to PV [10 , 11] , it is not clear whether this genetic association reflects causal involvement of ST18 in PV pathogenesis . In the present study , we examined the possibility that ST18 plays a direct role in PV pathogenesis .
Given the fact that a previous GWAS demonstrated an association between PV and variants in the vicinity of the ST18 gene locus [8] , we aimed at characterizing this risk region and therefore performed targeted deep sequencing of the ST18 locus in 16 Jewish PV patients , initially comparing the sequencing results to the 1000 Genomes Project ( 1000GP ) data ( http://www . 1000genomes . org ) . Since PV is a complex disease , our primary targets were common single nucleotide polymorphisms ( SNPs ) that were enriched in the sequenced cohort as compared with controls . We therefore examined all SNPs with non-zero frequencies in the public databases that were not in repetitive regions , totaling 789 SNPs ( Fig 1 ) . A case-control association analysis for each SNP , using chi-square and permutation test , led to the identification of a genomic haplotype block strongly associated with the propensity to develop PV ( p<0 . 001 ) ( Fig 1 and S1 Fig ) . We discovered that this risk haplotype harbors two variants previously found to be most significantly associated with PV in the original GWAS , rs4074067 and rs2304365 [8] . Collectively , the SNPs found within the risk haplotype block had a frequency of 50% in the sequenced cohort and of only 8% in the total 1000GP population . Within the risk haplotype block , we identified a genetic variant , rs17315309 ( Fig 1 ) , which displayed significant association to PV based on the deep sequencing data . We then replicated this association in an independent set of 185 Jewish PV patients compared with 183 population-matched healthy controls ( p<0 . 001; S1 Table ) . A number of bioinformatic analyses suggested that this variant may be of functional importance and possibly up-regulate ST18 promoter activity . First , using HMR Conserved Transcription Factor Binding Site database , implemented in the UCSC Genome Browser ( https://genome . ucsc . edu/ ) , this variant was found to reside within a p53 transcription factor binding site consensus sequence ( Fig 2a ) . The p53 binding motif consists of two very similar , closely located , half-sites , each 10 bp long [12 , 13] , although it has been shown that one decamer is sufficient for p53 or p63 binding and activity [14–19] . Second , the binding motif harboring rs17315309 is located in an intron of ST18 , upstream to the gene coding sequence and inside a 170 bp long DNAse hypersensitivity cluster ( chr8:53207581–53207750 , ENCODE; http://genome . ucsc . edu/ENCODE/ ) , lending further support to the possibility that this region plays a regulatory role . Of note , p53 is known to recognize consensus binding motifs located proximal to the transcription start site of target genes , either within the promoter region or a gene intron [20] . Third , using the 100 Vertebrae Conservation by PhastCons , implemented in the UCSC Genome Browser ( http://compgen . cshl . edu/phast/ ) , we found that both rs17315309 and the p53/p63 binding motif are highly conserved with a maximum conservation score of 1 ( range 0 to 1 ) . Similarly , using Biobase Transfac Matrix Database ( v7 . 0 ) , implemented in the UCSC Genome Browser ( http://www . gene-regulation . com/pub/databases . html ) , the 10 bp long binding motif containing rs17315309 was found to be remarkably conserved ( computed score: 992; maximal score: 1000 ) , supporting the possibility that it represents a biologically functional binding site . Lastly , as rs17315309 results in a T to C substitution at position 6 of the p53/p63 binding motif , we wished to examine the conservation of this nucleotide in the binding site consensus sequence . Both MotifMap ( http://motifmap . ics . uci . edu ) and Jasper ( http://jaspar . genereg . net ) databases indicated that position 6 in the half-binding site consensus sequence of both p53 and p63 is highly conserved and consists usually of a T nucleotide with a minimum to no abundance of a C nucleotide ( Fig 2a ) . Taken collectively , these data suggested that modification of the wild type rs17315309 allele within the p53/p63 binding site may be of biological significance . To examine this possibility , we transfected normal human keratinocytes ( NHEKs ) with a PGL4 . 17 luciferase reporter construct under the regulation of a 282 bp fragment spanning the p53/p63 binding motif containing either the wild type ( T ) or the risk ( C ) rs17315309 allele . The C allele was found to induce a more than 5-fold increase in luciferase activity ( p<0 . 001 ) ( Fig 2b ) . Moreover , when the construct was co-transfected with p53- or p63-specific siRNAs ( S2a and S2b Fig ) , this effect was markedly attenuated ( Fig 2b ) , indicating that the PV-associated rs17315309 risk allele increases ST18 promoter activity in a p53-/p63-dependent manner . These results are in line with previous data showing that a single nucleotide change in a canonical p53/p63 binding sequence is enough to affect p53 or p63 binding [21] . Given these data , the physiological roles of ST18 and the fact that ST18 is markedly overexpressed in the non-lesional epidermis of PV patients [8] , we sought to ascertain the consequences of ST18 overexpression on pathophysiological hallmarks of the disease . We first examined the effect of ST18 on keratinocyte secretion of pro-inflammatory cytokines which are believed to contribute to PV disease phenotype [1 , 4 , 11] . Overexpression of ST18 ( S2c Fig ) in the presence of normal serum or control IgG did not affect the secretion of either TNFα , IL-1α or IL-6 ( Fig 3 ) . In contrast , when overexpressed in the presence of PV serum , ST18 was found to drive the secretion of all three cytokines ( Fig 3a–3c ) , indicating that ST18 functions by promoting PV-induced keratinocyte secretion of pro-inflammatory cytokines . This effect was seen early with TNFα and IL-1α but late with IL-6 ( Fig 3a–3c ) . We then repeated the same experiments , comparing the effect of control and PV sera to the effect of control IgG and PV IgG . Overexpression of ST18 was found to increase PV serum-induced and PV IgG-induced secretion of TNFα , IL-1α and IL-6 , to the same extent , while not affecting the secretion of these cytokines in the presence of control serum or control IgG ( Fig 3d–3f ) . As disruption of epidermal cell-cell adhesion is a pathogenic hallmark of PV [1] , we investigated ST18 effect on PV serum-induced cell-cell disadhesion . For this purpose , we used the dispase-based dissociation assay . In this system , PV serum destabilizes intercellular bonds , compromising epidermal sheet resilience to mechanical stress [22] ( Fig 4a ) . NHEKs overexpressing ST18 and exposed to PV serum exhibited a more than 2-fold decrease in cell-cell adhesion , as compared to cells exposed to PV serum and transfected with an empty vector ( p<0 . 05 ) ( Fig 4b ) or with a vector overexpressing a non-relevant gene ( S3 Fig ) . The deleterious effect of ST18 overexpression on cell-cell adhesion was similar when cells were exposed to pooled PV sera or to PV IgG ( Fig 4b ) . Taken together , these results demonstrate that ST18 may also contribute to PV pathogenesis by potentiating PV IgG-induced acantholysis .
Despite a large body of epidemiological evidence supporting a role for genetic elements in determining the propensity to develop the disease [3 , 5–7] , little is currently known about the genetic basis of PV . Using a GWAS approach , we previously identified an association between PV and a genomic segment on chromosome 8q11 spanning the ST18 gene [8] . ST18 encodes the suppression of tumorigenicity 18 ( ST18 ) , a 115kD member of the myelin transcription factor 1 ( MyT1 ) family of transcription factors containing several zinc-finger DNA-binding domains [23] . ST18 is constitutively expressed in the brain , and less so in the heart , liver , kidney , skeletal muscle , pancreas , testis , ovary and prostate [24] . ST18 is undetectable in normal skin , but is significantly expressed in the epidermis of PV patients [8] . Two recent studies [9 , 25] demonstrated the role of ST18 in apoptosis and inflammation , two processes of direct relevance to the pathogenesis of PV [10 , 11] . ST18 was shown to mediate TNFα-induced transcription of pro-apoptotic and pro-inflammatory genes in fibroblasts , including TNFα , IL-1α and IL-6 [9] . In the present study , using targeted deep sequencing of the ST18 locus , we identified within the ST18 promoter region a PV-associated genetic variant , rs17315309 , which was shown to drive gene transcription in a p53/p63-dependent fashion . Of interest PV serum was previously found to induce p53 expression [26] and p63 is overexpressed in the skin of pemphigus foliaceus patients [27] . Together with the fact that ST18 expression is up-regulated in the skin of PV patients [8] , these data suggested that ST18 overexpression may be directly contributing to the disease pathogenesis . And indeed , ST18 up-regulation was found to induce the secretion of TNFα , IL-1α and IL-6 in the presence of PV serum as well as in the presence of PV IgG antibodies . The level of all three cytokines has been previously reported to be increased in the serum as well as in the lesional skin and blister fluid of PV patients [11 , 28–34] . In addition , serum levels of TNFα and IL-6 were shown to negatively influence PV outcome [28 , 35] . Finally , both TNFα and IL-1α have been reported to be up-regulated by PV IgG and to contribute to PV IgG-induced acantholysis and apoptosis in keratinocytes [32 , 36] . Most importantly , ST18 was found to potentiate PV IgG-induced cell-cell disadhesion . The mechanism of action of ST18 in inducing cell-cell disadhesion remains to be fully elucidated but may involve some of the cytokines whose secretion was found to be increased in the presence of ST18 overexpression [32 , 36] . Clearly , other pro-inflammatory factors may also contribute to keratinocyte dissociation . The fact that PV IgG cause secretion of cytokines and loss of cell adhesion to a comparable extent as PV serum demonstrates that ST18 promotes the effect of autoantibodies rather than serum factors on the secretion of cytokines and on loss of cell adhesion . Taken collectively , our data indicate that a PV-associated risk allele at the ST18 gene locus may drive ST18 up-regulation which in turn could contribute to PV pathogenesis by stimulating keratinocyte-derived cytokine release and by compromising epidermal cell-cell adhesion . Thus , ST18 is likely to contribute to PV pathogenesis by increasing keratinocytes susceptibility to the deleterious effects of PV-associated autoantibodies rather than by affecting the production of these antibodies . Supporting this possibility , we did not detect any effect of ST18 genotype on anti-Dsg3 ELISA status in a series of PV patients ( S4 Fig ) . The present results therefore underscore the importance of genetic variations affecting target tissues in the pathogenesis of inflammatory diseases as previously shown for other skin disorders [37 , 38] .
The study was conducted according to a protocol approved by our institutional review board and the National Committee for Genetic Studies of the Israeli Ministry of Health in accordance with the Declaration of Helsinki Principles ( 102-2006/TLV-0537-15 ) . All family members provided written informed consent to participate in this study All family members provided written informed consent to participate in this study . Blood samples were obtained from all participants according to a protocol approved by our institutional review board and the National Committee for Genetic Studies of the Israeli Ministry of Health in accordance with the Declaration of Helsinki Principles . The diagnosis of PV was posed based upon clinical features , suprabasal separation on histology , positive direct and indirect immunofluorescence microscopy , and/or ELISA detection of anti-Dsg Abs . Genomic DNA was extracted from peripheral blood leukocytes using the 5 Prime ArchivePure DNA Blood kit ( 5 Prime Inc . , Gaithersburg , MD , USA ) . We used two different mixes of pooled sera from newly diagnosed PV patients ( n = 3 and 4 ) with active disease and an anti-Dsg3 titer above122 relative units/ml , as measured by the anti-desmoglein 3 ELISA ( IgG ) test kit ( Euroimmune AG , Luebeck , Germany ) . The sera were obtained prior to the initiation of any systemic immunosupressive treatment . PV IgGs were purified as previously described [39] and used at a final concentration of 65 μg/ml . DNA enrichment was performed using HaloPlex kit ( Agilent Technologies , Santa Clara , CA , USA ) and sequencing was conducted on a MiSeq system sequencer ( Illumina , San Diego , CA , USA ) with 150 bp paired-end reads . A total of 463407 bp were included in the capture design , covering the entire ST18 gene ( chr8: 53 , 023 , 399–53 , 373 , 519 , GRCh37/hg19 assembly ) as well as 10 kb downstream and 50 kb upstream to the gene and an additional 2 Mb located upstream and downstream to the gene and predicted to harbor putative regulatory regions ( https://www . encodeproject . org ) . The sequencing data were processed using MiSeq Reporter 2 . 0 . 26 and Casava softwares ( Illumina , San Diego , CA , USA ) and analyzed for quality control using FastQC software ( http://www . bioinformatics . babraham . ac . uk/projects/fastqc ) . Reads were aligned to the Genome Reference Consortium Human Build 37 ( GRCh37/hg19 ) using Burrows-Wheeler Aligner [40] and variant detection was achieved using The Genome Analysis Toolkit [41] . Variants were annotated by ANNOVAR [42] and the frequency of each variant was determined using data from dbSNP138 , the 1000 Genome Project and an in-house database . Case-control association test for variants was performed with chi-square , and permutation test , using the Caucasian population from the 1000 Genome Project data ( http://www . 1000genomes . org ) as a control . To screen for the rs17315309 allele , we PCR-amplified a 317 bp fragment , with ReddyMix PCR Master Mix ( Thermo scientific , NH , USA ) and the following primers 5`- TGCTTGCCGTTTGTAAGATG-3`and 5`-AGCCTGGTTCAAGAGCCTTC-3` . Cycling conditions were as follows: 94°C , 4min; 94°C , 30 sec; 61°C , 30 sec; 72°C 30 sec , for 2 cycles , 94°C , 30 sec; 59°C , 30 sec; 72°C 30 sec , for 2 cycles , 94°C , 30 sec; 57°C , 30 sec; 72°C 30 sec , for 38 cycles , 72°C for 10 min . The T allele is associated with the presence of a recognition site for endonuclease NspI ( New England Biolabs , Hitchin , UK ) . After incubation at 37°C for 16 hours followed by 20 min of inactivation at 65°C , the digested PCR products were electrophoresed in ethidium bromide-stained 3% agarose gels . NHEKs were extracted from skin discarded during plastic surgery procedures , after written informed consent had been obtained as previously described [43] . The keratinocytes were seeded on feeder plates containing 3T3-J2 fibroblasts and were grown in medium Green containing 42 . 5% DMEM ( Biological Industries , Beit-Haemek , Israel ) , 42 . 5% DMEM/F12 ( Biological Industries , Beit-Haemek , Israel ) , 10% FCII serum , 1% penicillin-streptomycin , 1mM L-glutamine , 1mM sodium pyruvate , 5 μg/mL Insulin , 0 . 2 mM adenine , 0 . 5 μg/mL hydrocortisone , 2nM Triiodothyronine , 0 . 1 nM cholera toxin and 10 ng/mL EGF , and were frozen upon 90% confluence . Cell were then thawed and cultured in KGM media ( Lonza , Basel , Switzerland ) . For the dispase-based dissociation assay , NHEKs were extracted from foreskin using the same conditions and were thawed and cultured in M154 media ( Life Technologies , Carlsbad , CA ) . A 8 . 0 kb-clone containing the ST18 open reading frame in a pCMV6-Entry vector ( 4 . 9kb ) was purchased from Origene Technologies Company ( Rockville , MD , USA ) . The empty pCMV6-Entry was used as a control . Additionally , a 6 . 6 kb-clone containing the CNBD2 open reading frame in a pCMV6-Entry vector ( 4 . 9kb ) was purchased from Origene Technologies Company ( Rockville , MD , USA ) and used a negative control for protein overexpression . NHEKs were cultured to 80% confluence and subjected to a transient transfection using lipofectamine2000 ( Life Technologies , Carlsbad , CA ) . A 282 bp ST18 gene fragment spanning rs17315309 was PCR-amplified using ReddyMix PCR Master Mix ( Thermo scientific , NH , USA ) , primers 5’-AAAATTAGGTACCGCGTTCAAGCACTCTATTACCT-3’ and 5’-AAAAGGACTCGAGGCTTGCCGTTTGTAAGATGA-3’ , and DNA extracted from two patients homozygous for rs17315309 wild-type allele T , and for rs17315309 minor allele C , respectively . Cycling conditions were as follows: 94°C , 4 min; 94°C , 30 sec; 61°C , 30 sec; 72°C 30 sec , for 2 cycles , 94°C , 30 sec; 59°C , 30 sec; 72°C 30 sec , for 2 cycles , 94°C , 30 sec; 57°C , 30 sec; 72°C 30 sec , for 38 cycles , 72°C for 10 min . The resulting amplicons were cloned into pGL4 . 17 vector ( Promega , Madison , WI , USA ) . NHEKs were co-transfected with the various pGL4 . 17 vectors and Renilla expression vector and control siRNAs ( Life Technologies , Carlsbad , CA ) or p53 specific siRNA ( Santa Cruz Biotechnology , Santa Cruz , CA ) or p63 specific siRNA ( Dharmacon , Inc . , Lafayette , CO ) with lipofectamine2000 and Opti-MEM medium ( Life Technologies , Carlsbad , CA ) . Efficiency of gene knock down was assessed by qRT-PCR ( S2 Fig ) . Cells were grown in KGM medium ( Biological Industries , Beit-Haemek , Israel ) . Twenty-four hours post transfection , cells were harvested and luciferase expression was evaluated using the Dual-Luciferase Reporter Assay System ( Promega , Madison , WI , USA ) and Tecan Infinite M200 device ( Tecan Group Ltd , Männedorf , Switzerland ) Supernatant collected from NHEKs was evaluated using Elisa assays specific for IL-1α ( Human IL-1 alpha/IL-1F1 DuoSet , R&D systems , Minneapolis , MN , USA ) , TNF-α ( Human TNF-alpha Quantikine HS ELISA , R&D systems , Minneapolis , MN , USA ) and IL-6 ( Human IL-6 DuoSet , R&D systems , Minneapolis , MN , USA ) . All ELISA assays were read and quantified using Tecan Infinite M200 device ( Tecan Group Ltd , Männedorf , Switzerland ) . For IL-6 , a Human Cytokine Array / Chemokine Array 41-Plex ( Eve Technologies Corporation , Calgary , Alberta , Canada ) was additionally used using a Millpore MILLIPLEX kit ( Merck KGaA , Darmstadt , Germany ) read by BioPlex 200 ( Bio-Rad , Hercules , CA , USA ) NHEKs were grown to confluence in triplicates on 6-well plates and exposed to PV or normal serum in a 1:10 dilution or to PV or control IgG antibodies in a final concentration of 65 μg/ml . After 24h the cells were washed twice with PBS , incubated in 2 ml of dispase II ( 2 . 4 units/ml , Roche Diagnostics , Basel , Switzerland ) at 37°C for 40 minutes and detached from the plate as monolayers . Cell sheets were carefully transferred to 15 ml tube containing 5 ml PBS and subjected to mechanical stress using 5 inversions . The number of fragments was counted by two independent evaluators . All pairwise comparisons were performed using the 2-tailed Student’s t test , unless otherwise indicated . Differences were considered significant if the P value was less than 0 . 05 .
|
Pemphigus vulgaris is a life-threatening autoimmune skin blistering disease . A large body of evidence indicates that the propensity to develop this condition is in part genetically determined . Using a genome wide association approach , we recently identified pemphigus vulgaris-associated genetic variations in the vicinity of the ST18 gene . In the present study , we identify a risk variant residing within the ST18 promoter region which drives ST18 gene promoter activity in a p53/p63-dependent manner , which is in line with the fact that ST18 is up-regulated in the skin of PV patients . Using functional assays , we show that ST18 overexpression increases PV serum-induced expression of pro-inflammatory mediators , as well as augments PV serum-induced disruption of keratinocyte cell-cell adhesion , which are hallmarks of pemphigus pathogenesis . Our findings therefore support a direct role for ST18 in the pathogenesis of pemphigus vulgaris , and position ST18 as a new molecular target of potential interest for the treatment of disease . From a broader perspective , these observations underscore the importance of genetic variations affecting the susceptibility of target tissues to autoimmunity .
|
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2016
|
Identification of a Functional Risk Variant for Pemphigus Vulgaris in the ST18 Gene
|
To better understand the initiation of CD8+ T cell responses during infection , the primary response to the intracellular parasite Toxoplasma gondii was characterized using 2-photon microscopy combined with an experimental system that allowed visualization of dendritic cells ( DCs ) and parasite specific CD8+ T cells . Infection with T . gondii induced localization of both these populations to the sub-capsular/interfollicular region of the draining lymph node and DCs were required for the expansion of the T cells . Consistent with current models , in the presence of cognate antigen , the average velocity of CD8+ T cells decreased . Unexpectedly , infection also resulted in modulation of the behavior of non-parasite specific T cells . This TCR-independent process correlated with the re-modeling of the lymph node micro-architecture and changes in expression of CCL21 and CCL3 . Infection also resulted in sustained interactions between the DCs and CD8+ T cells that were visualized only in the presence of cognate antigen and were limited to an early phase in the response . Infected DCs were rare within the lymph node during this time frame; however , DCs presenting the cognate antigen were detected . Together , these data provide novel insights into the earliest interaction between DCs and CD8+ T cells and suggest that cross presentation by bystander DCs rather than infected DCs is an important route of antigen presentation during toxoplasmosis .
Toxoplasma gondii is an intracellular protozoan parasite that induces a type 1 immune response characterized by the production of IFN-γ from CD4+ and CD8+ T cells [1] , [2] , [3] . The generation of this protective T cell response is dependent on the early synthesis of IL-12 by innate immune cells such as DCs , macrophages and neutrophils [4] , [5] . Of these populations , DCs appear to have a central role in bridging innate and adaptive responses and mice depleted of DCs are more susceptible to T . gondii [6] . This phenotype has been linked to the reduced IL-12 production in these mice , although DCs also act as antigen presenting cells for T cell priming . Indeed infection with T . gondii , results in an increase in the total numbers of DCs , their activation status ( increase in levels of MHC I , MHC II , CD80 and CD86 ) and changes in subset composition [7] . It is unclear from the earlier studies whether the depletion of DCs increases susceptibility to acute toxoplasmosis primarily through reduced IL-12 synthesis or by secondary effects on antigen presentation and T cell priming [6] . In addition , non-hematopoietic cells are also infected by T . gondii and can prime CD8+ T cells [8] . This observation has led to questions about the relative contribution of DCs and other antigen presenting cells in shaping the early T cell response during infection with Toxoplasma . While there is considerable evidence that CD8+ T cells and DCs are required for the control of T . gondii [3] , [9] , the actual interactions between these cells in vivo during toxoplasmosis have not been characterized . Live imaging by 2-photon microscopy combined with the generation of transgenic mice expressing fluorescent tags specific for different immune cell populations , has enabled the visualization and tracking of these cells in real time within primary and secondary lymphoid organs [10]–[16] . The dynamics of T cell movement within the lymph nodes have been extensively characterized using 2 photon microscopy [17]–[22] . This has led to a model whereby naïve T cells survey lymph nodes , guided by fibroblastic reticular cell networks and localized expression of chemokines which promote the chances of interaction between a rare antigen specific T cell and an APC carrying its cognate antigen [10] , [18] . However , many of the pioneering studies using intravital imaging , that have been used as a benchmark for understanding T cell behavior , have largely been based on non-infectious models [17] , [19]–[24] . More recent studies have imaged the response of immune cells to pathogens [25]–[30] and some differences have emerged between the infectious and non-infectious systems . For example , when antigen pulsed DCs were used to prime adoptively transferred T cells , the T cells and DCs were largely limited to the T cell zones of the lymph node [11] , [17] , [20] . In contrast , challenge with vaccinia or vesicular stomatitis virus has shown the presence of viral antigens , dendritic cells and T cells within the sub-capsular and interfollicular regions of the lymph nodes [29] , [30] . Thus there is value to being able to compare the mechanics of these events using reductionist approaches and models of infection . One of the obstacles to understanding the early events during toxoplasmosis has been the inability to reliably identify the cells responding to T . gondii in tissues . The availability of transgenic parasites that express model antigens and the use of TCR transgenic adoptive transfer systems has now improved our ability to track the antigen specific CD8+ T cell response during various infections including those caused by Toxoplasma , Listeria and Leishmania [8] , [31]–[34] . Recently the dynamics of activated OT1GFP cells responding to Toxoplasma expressing ovalbumin , has been characterized in the brain by live imaging [35] but these approaches have not yet been applied to understand the early events of T cell priming during this infection [32] . As a part of studies to better understand how T cell mediated immunity to T . gondii is initiated , transgenic Toxoplasma parasites and fluorescent immune cells were combined to enable live imaging by 2-photon microscopy of parasite specific CD8+ T cells and their interactions with DCs . These studies show that early during infection there was significant recruitment of dendritic cells and T cells to the sub-capsular region of the lymph node and that DCs were required for the expansion of T cells . In the presence of cognate antigen there was a significant reduction in the CD8+ T cell velocity , however infection by itself also had a non-specific effect on T cell movement . These latter events correlated with alterations in lymph node architecture and reduced expression of CCL21 , a chemokine that provides motogenic signals that underlie T cell movement in lymphoid tissues . Infection also led to a significant increase in CD8+ T cell-DC contacts in the presence of cognate antigen; however , sustained interactions were limited to a very early time point during infection , which correlated with the presentation of antigen by DCs . While infected DCs were rare at these early time points , DCs that were capable of presenting the cognate antigen were detected . Together , these studies reveal several novel aspects of CD8+ T cell and dendritic cell behavior and suggest that cross-presentation has a role in the development of protective T cell responses during toxoplasmosis .
In order to visualize the CD8+ T cell response during Toxoplasma infection , a model was used in which naive T cells from OT1GFP mice [36] were transferred into recipients , which were then infected with a genetically modified strain of T . gondii expressing ovalbumin ( PruOVA ) . As a first step in these studies , we quantified the OT1GFP response during the course of infection by flow cytometry . In uninfected mice , the transferred OT1GFP cells were present in all tissues except the brain ( Figure 1A ) . As expected , infection with PruOVA resulted in an expansion of these cells over the first 14 days in all compartments ( Figure 1B ) . The response was followed over a period of 28 days and the OT1GFP cells showed a gradual contraction in the spleen , mesenteric lymph nodes and liver following the initial expansion . Our studies did not reveal any difference between the mesenteric , mediastinal and parathymic lymph nodes either in numbers of OT1 T cells recovered or their activation phenotypes , consistent with recent reports which indicate that all of these lymph nodes can drain the peritoneal cavity [37] . The only site that displayed a differential kinetics was the brain , where there was a delay in the appearance of the OT1GFP cells . The response was maintained in the brain over the time frame analyzed consistent with parasite persistence at this site ( data not shown ) . The numbers of cells that were detected at various time points by 2-photon microscopy within the mesenteric lymph node was consistent with the kinetics established by flow cytometry ( Figure 1C ) . As an integral part of these studies , it was important to determine whether infection on its own affected the phenotype and behavior of the transferred cells . Therefore , mice adoptively transferred with OT1GFP cells were infected with the parental strain of Toxoplasma ( Pru ) or with the ovalbumin expressing strain ( PruOVA ) and the phenotype of the OT1GFP cells was compared . The OT1GFP cells imaged by 2-photon microscopy within the lymph nodes of uninfected or Pru infected mice showed a naive phenotype based on their smaller size and total numbers ( Figure 1D ) . The mice challenged with PruOVA however showed clonal expansion of the transferred OT1GFP cells and these cells showed a 30–40% increase in cellular volume over OT1GFP cells in the uninfected or Pru infected mice ( Figure 1D ) . Analysis of activation markers revealed that the OT1GFP cells in Pru infected mice retained their naive phenotype ( CD62Lhi CD127hi CD44lo CD25lo ) comparable to the OT1GFP cells in uninfected mice ( Figure 1E ) . In contrast , OT1GFP cells from the PruOVA infected mice ( day 7 post infection ) displayed an activated phenotype ( CD62Llo CD127lo CD44hi CD25hi ) . The chemokine receptor expression on the surface of these cells also changed upon activation . The OT1GFP cells in the PBS and Pru infected mice were CCR7hi CCR5lo in contrast to OT1GFP cells in PruOVA infected mice , which were CCR7lo CCR5hi . To determine whether these transferred cells acquire effector functions typical of the CD8+ T cell response to T . gondii , a 5-hour ex-vivo restimulation assay was performed . In the infected mice ( day 7 post infection ) , upon restimulation with SIINFEKL peptide , the OT1GFP cells synthesize effector cytokines such as IFN-γ , TNF-α and expressed increased levels of granzyme-B indicating that they are poised for cytolysis ( Figure 1F ) . The OT1 cells in the Pru infected mice did not synthesize any of these effector cytokines during ex-vivo restimulation with SIINFEKL ( Figure S1 ) . These data show that the OT1GFP cells that expanded in the lymph nodes in response to infection with PruOVA were antigen specific and fully functional effectors . Having established that ova-expressing parasites induce a relevant response in OT1GFP cells , live imaging by 2-photon microscopy was used to visualize the behavior of these CD8+ T cells . Following T cell transfer , mice were either infected with PruOVA or left uninfected . Mesenteric lymph nodes were isolated from the mice at different times post-infection and explanted lymph nodes were imaged using a temperature controlled , perfused imaging chamber . Tracking of individual T cells was performed to determine how infection-induced activation affects cell velocity , displacement and meandering index . The tracks of naive and activated OT1GFP cells at various time points ( 0 s , 155 s , 330 s , 525 s , 675 s and 755 s ) during an imaging session ( day 3 post infection ) is shown in Figure 2 ( A&B ) . Analysis of the mean migratory velocities of the T cells during the entire imaging period revealed differences between the naive and activated OT1GFP cells ( Video S1 ) . Naive T cells moved with an average velocity of 8 . 7 µm/min and as early as 3 days post-infection with PruOVA , there was a reduction in the average velocity of the population to 4 . 49 µm/min ( Figure 2C ) . A similar reduction was also seen at days 7 and 14 post infection ( 4 . 18 µm/min and 4 . 75 µm/min respectively ) , however at the later time points ( day 21 and day 28 ) the average velocities increased to 7 . 5 and 6 . 7 µm/min respectively . While infection resulted in a statistically significant reduction in the average velocity of the transferred T cells , it was apparent that at all time points examined , there was a large range in motility: fast ( 15–20 µm/min ) and slower moving cells ( 5–10 µm/min ) and a population with a highly constrained phenotype ( 0–2 µm/min ) . To provide a more complete analysis of the changes in T cell behavior , the frequencies of cells that move at different speeds within the given imaging session are shown in Figure 2D . Presenting the data in this fashion revealed that by day 3 following challenge with PruOVA , the reduction in the average T cell velocity was largely a function of the increased proportion of cells that were moving at less than 2 µm/min . At day 7 and 14 , this population remains the largest fraction , but by day 21 the distribution of T cell velocities starts to revert back to the normal distribution seen in uninfected mice . Thus , during the early stages of infection within the lymph node , there is an increase in the proportion of stationary cells , which is reversed at later time points . In other models , pausing and stalling of T cells is associated with recognition of cognate antigen and activation . Since T . gondii infects DCs and macrophages and disseminates widely throughout the host , it seemed likely that antigen availability contributed to the changes observed in T cell behavior . Parasites can be visualized , albeit at low numbers , by immuno-histochemical staining within the lymph node ( Figure 3A ) and measurement of parasite DNA by real time PCR revealed an initial increase followed by a decline in the parasite DNA levels ( Figure 3B ) . Interestingly , while the decrease in T cell velocities was inversely correlated with parasite burden , the maximal reduction in the T cell velocities preceded the peak of parasite burden in these tissues ( Figure 3B ) . In order to determine whether infection on its own affects T cell movement in the absence of antigen , OT1GFP cells from uninfected , Pru and PruOVA infected mice were compared . The virulence of the two different strains were comparable as noted in previous studies [38] and as shown by the parasite DNA levels measured in the lymph nodes of mice infected with either Pru or PruOVA ( Figure S1B ) . Analysis of OT1GFP cells in Pru infected mice ( no cognate antigen ) revealed a modest and transient reduction in the average velocity in comparison to OT1GFP cells in uninfected mice ( Figure 3C ) . However , unlike the OT1GFP cells in the PruOVA infected mice , the reduction in the average velocity of the population was not due to a preponderance of cells that had stopped , but due to an increase in the proportion of slower moving cells ( Figure 3D ) . These latter data indicate that while antigen availability plays a vital role in CD8+ T cell movement within the lymph node , there are antigen independent effects on T cell motility during this infection . In order to understand the antigen independent modulation of T cell movement during infection , studies were performed to determine if there were any changes in the microenvironment of the infected lymph node and the localization of OT1GFP cells . Collagen fibrils have been shown previously to underlay the conduit system formed by the fibroblastic reticular cell networks within the lymph node [17] and collagen is known to generate second harmonic signals during imaging by multiphoton microscopy . To visualize these structures , lymph node sections were exposed to polarized laser light ( 930 nm ) and the second harmonic structures were detected using non-descanned detectors with barrier filters in the 457–487 nm range . In response to infection , there was a marked increase in the second harmonic structures within the lymph node ( Figure 4A ) . Quantification of the volume of fibers visualized at day 7 reveals an almost 2 fold increase in these networks ( data not shown ) . Immuno-histochemical staining of lymph node sections for ERTR7 , a marker for fibroblastic reticular cells ( FRC ) . revealed that infection resulted in an increase in their density ( Figure 4B ) . ( The second harmonic signals generated in the lymph node show co-localization with the ERTR7 staining ( Figure S2A ) ) . In a naïve lymph node , the ERTR7 networks are confined to the T cell zones , but this well-defined organization is absent in the lymph nodes of the infected mice . This is in agreement with the loss of distinct T cell areas and B cell follicles upon infection ( Figure 4C ) . Differences were also seen in the localization of the OT1GFP cells relative to the capsule in the infected and uninfected mice . This is depicted in the representative z-stacks ( 20× ) of the mesenteric lymph nodes from the three different experimental groups ( Figure 4D ) . In uninfected mice , the majority of OT1GFP cells are located away from the capsule , whereas infection leads to the presence of OT1GFP cells in the sub-capsular region . This is reflected in the average frequency of the cells imaged at different distances from the capsule ( seen in purple ) from 300 µm z stacks of lymph nodes from the various treatment groups ( Figure 4E ) . This change in the localization of the OT1GFP cells was independent of the presence of cognate antigen as it was also observed in Pru infected mice . The chemokine environment within the lymph node , specifically the balance between CCL21/CCL19 and pro-inflammatory chemokines such as CCL3 , has been linked to T cell motility and their directionality [10] , [21] . Therefore , mRNA levels for CCL21 and CCL3 within the lymph node , during infection were measured by RT-PCR . Compared to uninfected mice , CCL21 expression ( normalized against control HPRT expression ) showed a down-regulation in the infected lymph nodes , while CCL3 expression showed a modest increase ( Figure 4F ) . Preliminary studies did not reveal significant changes in the levels of CCL5 in the lymph node during the time points when changes in CCL3 and CCL21 were observed ( data not shown ) . As noted earlier , during infection with Pru , the naive OT1GFP cells retain high levels of CCR7 and do not up regulate CCR5 ( Figure 2B ) . Thus , while the balance between the chemokines CCL21 and CCL3 changes during infection , the receptors for these chemokines , CCR7 and CCR5 respectively , are not altered on the naive T cells in the absence of cognate antigen . Together , these data show that infection induces distinct changes in the location of the T cells and micro architecture of the lymph node , all of which may contribute to the antigen independent regulation of T cell movement . Since infection with PruOVA induced a significant proportion of the OT1GFP cells to arrest and round up very early during infection , it seemed likely that this was a reflection of cross talk with professional APCs such as DCs . Previous studies have indicated that in the absence of DCs mice are susceptible to infection with T . gondii and this was linked to reduced IL-12 production in these mice [6] . In order to test whether transient depletion of DCs had any effect on T cell priming we used the CD11c-DTR transgenic model [39] . The CD11c-DTR transgenic mice express the diphtheria toxin ( DT ) receptor under the control of CD11c promoter and hence transient depletion of CD11c+ cells ( 2 days ) is achieved by injecting DT into these mice . CD11c-DTRGFP transgenic or WT mice received OT1GFP cells , followed by injection of DT ( 100 ng/mouse ) . The mice were then infected with PruOVA parasites 24 hours later . Transient depletion of DCs was verified in the CD11c-DTRGFP transgenic mice by flow-cytometric analysis of peripheral blood samples 24 hours after treatment with DT ( data not shown ) . The frequency and numbers of OT1GFP cells that were detected in the spleen and lymph nodes were significantly reduced in the CD11c-DTRGFP transgenic mice treated with DT compared to the CD11c-DTRGFP mice that were untreated or WT mice that were treated with DT ( Figure 5A ) . A large fraction of the OT1GFP cells recovered from the CD11c-DTRGFP transgenic mice treated with DT retained a naïve phenotype ( CD44loCD62Lhi ) . There was however a small proportion of OT1GFP cells that showed an activated phenotype CD44hiCD62Llo . These studies indicate that DCs are the major APCs for priming a CD8+ T cell response and their presence is crucial early during infection to generate an efficient CD8+ T cell response . In order to visualize if infection induced changes in the DC population , transgenic mice in which the CD11c promoter drives expression of YFP were used [40] . In uninfected mice , the CD11cYFP cells present in the lymph node displayed a morphology typical of DCs described previously [40] ( Figure 5B , Videos S2 and S4 ) . Upon infection , these cells developed a highly vacuolated appearance and showed an increase in their surface area ( day 3 post infection , Figure 5C ) . It should be noted that while a large proportion of DCs displayed this vacuolar phenotype , the number of infected cells present in these tissues was low . Further , in the rare instance when an infected and an uninfected DC could be visualized within the same imaging field in the lymph node , both the DCs were vacuolated ( Figure S3 ) . This phenotype could be detected as early as 24 hours post infection , and persisted at days 7 and 14 . Our studies did not reveal any significant differences in the movement of the DCs ( Video S2 ) between infected and uninfected mice . To assess whether the DCs and CD8+ T cells co-localize and interact , 2×106 OT1GFP cells were transferred into CD11cYFP transgenic mice , which were then either infected with 104 PruOVA parasites or left unchallenged . Distinct differences were noticed in the localization of the DCs ( similar to the localization of OT1GFP cells noted previously ) during infection . In uninfected mice , the DCs were distributed largely in the T cell areas , B cell follicles and a small proportion can be found in the sub-capsular/interfollicular regions of the lymph nodes ( data not shown ) . In mice infected with PruOVA there was a significant increase in the numbers of CD11cYFP cells and OT1GFP cells in the sub capsular/interfollicular region of the lymph node , as seen in the 150 µm z stacks ( 20× ) at day 3 post infection ( Figure 5D and Videos S3 and S4 ) . This increased localization of DCs and CD8+ T cells to this region was also seen at days 5 and 7 post infection , but by day 28 , the lymph node architecture was more similar to that observed in the uninfected state . Together these data reveal that infection with Toxoplasma leads to changes in DC morphology and localization within the lymph nodes draining the site of infection . Since DCs and T cells localize to the same regions during infection , we wanted to determine if there were any antigen dependent crosstalk between these two populations . T cell-DC interactions were analyzed at different times post infection in the CD11cYFP transgenic mice that were adoptively transferred with OT1GFP cells . A representative image of DCs and OT1GFP cells imaged during Pru and PruOVA infection is shown in Figure 6A . The frequency of cells that made contacts of different durations with DCs within the imaging sessions ( typically 12–15 minutes ) is shown in Figure 6B ( Videos S5 and S6 ) . In uninfected mice , OT1GFP and CD11cYFP cells had very brief encounters and infection with Pru did not lead to significant changes in these interaction times . In the presence of cognate antigen ( PruOVA ) long-lived interactions could be observed as early as 6 hours post infection . However , at these early times , there was a large variation in DC-T cell interaction times as seen in Figure 6B . The frequency of T cells making prolonged contacts with DCs increases between 18–24 hours and most of the contacts could be visualized for the entire imaging period . Consequently , the upper limit of interaction times shown in Figure 6B is an underestimate of how long these two populations remain in contact . By 36 hours post infection with PruOVA , in addition to the T cells that made long lasting interactions , there was a proportion of T cells that were engaged with DCs for comparatively shorter time periods . By day 3 , however the majority of the interactions visualized were of substantially shorter durations ( Videos S5 and S6 ) . There were no significant changes in DC-T cell interaction times in the absence of cognate antigen ( during Pru infection ) during any of these time points . These data indicate that sustained interactions between CD8+ T cells and DCs are visualized only in the presence of cognate antigen and are most frequent very early during infection ( within the first 36–48 hours ) . These sustained early interactions are antigen dependent , and are suggestive of antigen presentation by the dendritic cells to the OT1GFP cells . In order to ascertain whether the DCs that were interacting with the OT1GFP T cells were infected , CD11cYFP transgenic mice were infected with a PruOVA strain that was engineered to express cytoplasmic dTomato . This enabled the visualization of the parasites during live imaging . In the first 36 hours infected DCs were rarely detected in the mesenteric and mediastinal lymph nodes by 2-photon microscopy ( data not shown ) . Intracellular staining with a polyclonal anti-Toxoplasma antibody similarly showed very few infected DCs ( Figure 6C ) . However , staining with 25-D1 . 16 antibody , which recognizes MHC class I ( Kb ) -SIINFEKL complexes [41] , reveals that many of these cells were presenting the immunodominant peptide of ovalbumin . Immuno-staining for ovalbumin protein similarly showed DCs carrying ovalbumin early during infection ( Figure S2B ) . These data suggest that the prolonged interactions that were visualized early during infection most probably involved DCs cross-presenting Toxoplasma derived antigens , rather than infected DCs . The kinetics of activation of OT1GFP cells early during infection was monitored in the mesenteric , mediastinal and peripheral lymph nodes as well as the spleen at various time points post-infection to see if the acquisition of activation markers mirrored the time frame seen with the DC-T cell interaction studies ( Figure 7A ) . At 18 and 36 hours post infection the OT1 cells in all compartments retained their naïve phenotype ( CD62LhiCD69loCD25lo ) . By 48 hours , the OT1 cells in the mediastinal and mesenteric lymph nodes and a smaller proportion in the spleen showed signs of activation ( CD62LloCD69hiCD25hi ) ( Figure 7B ) . These studies indicate that the T cells start to express activation markers during the 36–48 hr time window subsequent to the initial prolonged interactions . Together , these data show that the early-sustained interactions observed between DCs and T cells in the presence of cognate antigen are indicative of T cell priming .
With the advent of live in vivo imaging , significant advances have been made in our understanding of T cell behavior within secondary lymphoid tissues [12] , [13] . While many of the early reports on this topic were based on non-infectious models , more recent studies have focused on the effects of inflammation and infection on immune cells in lymphoid and non-lymphoid compartments [11] , [12] , [20] , [22] , [25]–[30] . However , the dynamics of T-DC interactions during infection with a live replicating parasite have not been characterized previously and little is known about this process . The studies presented here describe the use of genetically modified parasites combined with TCR transgenic T cells and various reporters to allow visualization of T . gondii induced CD8+ T cell priming by DCs and the changes induced in these populations during infection . Consistent with current models , the presence of cognate antigen was the major factor that influenced CD8+ T cell motility during toxoplasmosis . The stalling of the OT1GFP cells observed in the presence of OVA expressing parasites could be due to a variety of reasons but the higher frequency of non-motile T cells very early during infection ( 36 hours ) correlated with sustained contacts with DCs . In other reports , long lived interactions between DCs loaded with the antigenic peptide and CD4+ T or CD8+ T cells were imaged in the first 18–36 hrs after transfer of T cells [19] , [22] . Moreover , in other infectious disease systems in which anti-bacterial drugs were used to limit bacterial replication , the first 24–48 hrs after challenge was crucial for T cell priming [42] , [43] . Thus , placed in this context , our findings indicate that the CD8+ T cell priming events during Toxoplasma infection happen much earlier than previously anticipated . Recent studies have dissected the priming response of CD8+ T cells into three stages: an initial phase dominated by transient short term interactions , followed by prolonged interactions and a third phase of short lived interactions between T cells and DCs [44] . While it is difficult to compare the results observed using DCs loaded with defined amount of peptide to an infection where antigen availability increases over time and the pathogen is modulating the host cell response , our studies show multiple stages in the T-DC crosstalk , with a transition from sustained interactions at the early time points to short lived interactions at the later time points . However , the duration of some of these T-DC contacts was difficult to estimate , since many of these lasted through out the imaging sessions . As infection progressed and T cells became activated , the interactions with DCs were of much shorter duration consistent with other reports [44] , [45] . This change in behavior reflects the evolution of the T cell response from a naive resting population to one composed predominantly of effector cells which have an intrinsically lower threshold for activation [46] and perhaps short term interactions with DC are sufficient to sustain the expansion of the CD8+ T cell response . One of the most notable changes following infection was in the organization of the lymph node associated with the presence of T cells and dendritic cells in the sub-capsular/interfollicular region . Similar reorganization was noted using vaccinia or vesicular stomatitis virus infections , where T cells and antigen were found largely in the sub-capsular region [29] , [30] . The redistribution of T cells and DCs during challenge with T . gondii could be due to the entry of these cells from the afferent lymphatics and accumulation at this location . The other possibility is that with the first round of parasite cytolysis of infected cells , there would be the release of parasite-derived secreted antigens from the parasitophorous vacuole that would drain into the lymph node through the afferent lymphatics . The ability of parasite-derived material to mobilize DCs has been reported previously [47] and this might mediate active relocalization of DCs to this site . A related possibility is that parasites disseminate rapidly from the site of infection and studies by Robey and colleagues using a virulent strain of T . gondii that imaged the neutrophil response to T . gondii noted the presence of parasites and inflammatory cells within the sub-capsular region [25] . This suggests that this location is a site of active inflammation and/or parasite replication . An unexpected finding from these studies was the antigen-independent modulation of CD8+ T cell motility , which correlated with the extensive remodeling of the lymph node during infection . In uninflamed lymph nodes , the FRC networks and the chemokines CCL19 and CCL21 that decorate these networks provide the major chemo-kinetic stimulus for the movement of naive T cells [18] . Changes in these structures have been reported in some infections , such as challenge with LCMV , where there is destruction of the FRC network [48] and down-modulation of CCL21 [49] . Similarly , challenge with Toxoplasma results in a disorganization of the FRC network , possibly due to the loss of well-defined T cell areas and B cell follicles , and a reduction in the levels of CCL21 . Since , in the absence of cognate antigen , the OT1GFP cells still maintain high levels of CCR7 , it is possible that the reduced motogenic signals associated with loss of CCL21 combined with changes in the architecture of the lymph node account for the reduction in T cell motility . Whether this change in behavior would reduce the likelihood of a naïve T cell contacting an appropriate DC or if it represents a mechanism to promote the development of more sustained interactions and so promote the priming of naive T cells in an inflamed environment remains to be tested . However , there are multiple reports suggesting that it is difficult to prime new T cell responses during acute infection/inflammation [49] , [50] . The phenomenon of antigen-independent slowing of naïve T cells in an inflamed environment observed in this study , may help to explain the basis for these previous observations . In the current studies , significant changes were also observed in the morphology of the DCs in infected mice . The appearance of multiple vacuolar structures was the most characteristic change and the initial expectation was that these might contain parasites , similar to what has been reported for Leishmania parasites [26] . However , the number of vacuolated DCs that contained parasites was rare and the majority of vacuolated DCs were uninfected . However , vacuolation of the DCs was observed only during infection with live parasites and not by injection of soluble tachyzoite antigen ( unpublished observations ) , suggesting that it is a consequence of the inflammatory events associated with infection . A similar morphological change has also been observed for astrocytes during toxoplasmic encephalitis ( unpublished observations ) . In current paradigms dendritic cells play a central role in the development of resistance to T . gondii likely through the production of IL-12 as well as antigen presentation . Moreover , recent studies from this laboratory and others , using a type I virulent strain of T . gondii , concluded that only infected DCs are capable of presenting antigens for the generation of CD8+ T cell responses [8] , [51] . However , the studies presented here , using an avirulent type II strain of T . gondii , revealed early sustained interactions between OT1GFP cells and DCs at a time point when the number of infected cells in the lymph node was minimal suggesting that uninfected DCs are capable of priming the CD8+ T cell response . Taken together , these results suggest that , depending on the parasite strain , there may be fundamentally different antigen sampling and/or processing pathways that dictate how the CD8+ T cell response to T . gondii is generated . Using available reporters and KO mice it should now be possible to distinguish how strains of T . gondii that differ in virulence influence the ability of DCs to cross present parasite derived antigens or act as a source of IL-12 . Understanding the mechanics of these events would help in the design of optimal strategies for immune based therapies designed to enhance vaccine-induced responses .
DPE-GFP transgenic mice that express GFP on all T cells were originally obtained from Ulrich H . von Andrian ( CBR , Harvard , Boston MA ) and were crossed to OT1 TCR transgenic mice ( The Jackson labs , Bar Harbor , ME ) [36] , [52] . CD11cYFP transgenic mice were obtained from Michel C Nussenzweig [40] . CD11c-DTRGFP transgenic mice were purchased from the Jackson Laboratory . These transgenic mice were maintained in a specific pathogen-free facility in the Department of Pathobiology at the University of Pennsylvania and the Wistar Institute in conformance with institutional guidelines for animal care . C57BL/6 mice were purchased from the Jackson Laboratory . Mice were used between 6–8 weeks of age and all animal experiments were performed with approval of the Institutional Animal Care and Use Committee ( IACUC ) . The Prugniaud strain of Toxoplasma gondii ( Δ HXGPRT ) originally obtained from D . Soldtai ( Imperial college , London , United Kingdom ) [8] was maintained as tachyzoites by serial passage through human foreskin fibroblast cell ( HFF ) monolayers . Transgenic strains of Prugniaud parasites that were engineered [8] to secrete ovalbumin protein ( aa 140–386 ) into the parasitophorous vacuole ( referred to as PruOVA ) were maintained similarly on HFF monolayers in the presence of 20 µM chloramphenicol . PruOVA strains were also engineered to express cytoplasmic dTomato [53] under the control of the alpha tubulin promoter and selected for by phleomycin drug selection . Tachyzoites were purified from the HFF monolayers by filtration through a 3 µm filter ( Nucleopore , Clifton , NJ ) . The parasites were washed , counted and resuspended in PBS for infections . Lymphocytes were isolated from spleen and peripheral lymph nodes of DPE-GFP OT1 TCR transgenic mice ( OT1GFP ) . Single cell suspensions were obtained by mechanical homogenization and RBCs and dead cells were removed by density gradient centrifugation ( Lympholyte-M , Cedarlane laboratories Ltd , Hornby , Ontario Canada ) . T cells were purified using the mouse T cell enrichment columns ( R&D systems , Minneapolis , MN ) . 2×106 purified OT1GFP cells were injected into recipient mice intravenously ( retro-orbital injections ) . 24 hours after transfer of T cells , the mice were infected intraperitoneally with either the parental ( Pru ) or ovalbumin expressing ( PruOVA ) prugniaud strains of T . gondii at a dose of 104 parasites per mouse . Mice were sacrificed by CO2 asphyxiation and the lymph nodes were removed immediately , with minimal mechanical disruption . They were embedded in 1% agarose ( in PBS ) in an imaging chamber ( Warner Instruments ) . The embedded lymph node was constantly perfused with warm ( 37°C ) media ( RPMI+10% FBS ) , which was oxygenated ( 95% O2/5%CO2 ) . The temperature in the imaging chamber was maintained at 37°C using heating elements and a temperature control probe . Live ex vivo imaging was done using a 2-photon microscope system designed by Prairie technology ( Ultima ) which included a Diode-pumped , wideband mode-locked Ti: Sapphire femtosecond laser ( 780–980 nm , <140 fs; 90 MHz; Coherent Chameleon ) , an Olympus BX-51 fixed stage microscope with 20× ( NA0 . 95 ) or 40× ( NA 0 . 8 ) water immersion objectives and external non descanned PMT detectors , which consisted of dichroic mirrors ( 520 nm , 495 nm , and 575 nm ) and barrier filters ( 457–487 nm; 503–537 nm; 525–570 nm and 580–652 nm ) . In some experiments , a Leica SP5 2-photon microscope equipped with a picosecond laser ( Coherent Chameleon; 720 nm–980 nm ) and tunable internal detectors that allow simultaneous detection of emissions of different wavelengths and second harmonic signals ( SHG ) was used . EGFP , YFP and dTomato were excited using laser light of 930 nm . Typically , z stacks of a series of x-y planes at a resolution of 0 . 49 µm/pixel ( 40× lens ) or 0 . 98 µm/pixel ( 20× lens ) with a total thickness of 30 µm and step size of 6 µm were captured every 30–45 seconds using the Prairie view acquisition software ( Prairie Technologies ) or Leica LAS AF software ( Leica Microsystems ) . Volocity software ( Improvision ) was used to convert the three dimensional image stacks into time series . Single cell tracking was done by a combination of manual and automated tracking . For automatic tracking intensity and size filters were used for identifying the cells ( exclusion of objects below background intensity levels and size; 50 µm3 for T cells and 200 µm3 for DCs ) . The mean migratory velocities , displacement , confinement ratios were calculated using the software . Measurements were typically performed on 31 frames . For measurement of T cell–DC interactions , the duration of contacts of all the T cells observed in a given filed of view were calculated for the entire imaging period ( typically lasting 12–15 minutes ) . Cellular contacts were determined manually as a lack of space between the interacting cells and the data obtained from an average of 6 imaging regions from 3 individual mice per group were used to obtain the frequency of T cells with different durations of contacts with the T cells . Parasite DNA levels were measured by real time PCR on DNA isolated from the tissue samples [54] . A 35-fold repetitive T . gondii B1 gene was amplified by real-time PCR . ( Forward primer 5′-TCCCCTCTGCTGGCGAAAAGT-3′; Reverse primer 5′-AGCGTTCGTGGTCAACTATCGATTG-3′ ) . Standard curves for parasite DNA levels were generated using 10-fold serial dilutions of parasite genomic DNA , ranging from 0 . 1 µg to 0 . 1 pg , as DNA template . These standard curves were used to measure the total parasite DNA amounts in a given tissue sample . RNA was isolated from mesenteric lymph nodes of different immune groups using TRIzol ( Invitrogen ) and DNase treated total RNA was reverse transcribed using Superscript II ( Invitrogen ) using standard protocols . Quantitative PCR was performed with customized primer sets for CCL3 and CCL21 ( leu ) and HPRT ( QIAGEN ) using Power SYBR green reagents ( Applied Biosystems ) and an AB7500 fast real time PCR thermal cycler ( Applied Biosystems ) . The values for the CCL3 and CCL21 were normalized to HPRT and displayed as fold induction over naïve controls . Lymph nodes and spleens were isolated from mice at the indicated time points , and single cell suspensions were obtained by mechanical homogenization . The livers were perfused before they were harvested , and lymphocytes were isolated as previously described [55] . For brain mononuclear cells , the mice were perfused with cold PBS , the brain was removed , diced , and passed through an 18-gauge needle and digested with Collagenase/Dispase ( 25 µg/ml ) and DNAse ( 100 µg/ml ) for 45 minutes at 37°C . The cell suspension was then washed and fractionated on a 30%–60% percoll gradient ( Pharmacia ) for 20 minutes [54] . The cells in the interface consisted of mononuclear cells , which were washed prior to experiments . CD11c-DTRGFP transgenic mice were treated with 100 ng per mouse of DT ( Diphtheria toxin ) IP , to deplete their DCs transiently [6] . Depletion of DCs was confirmed by sampling peripheral blood , 24 hours after DT treatment and staining for DCs by flowcytometry . OT1 T cells were transferred shortly before DT injection and the mice were infected with PruOVA 24 hours post DT treatment . Lymph nodes were either directly flash frozen in OCT and or were fixed in 4% formaldehyde/10% sucrose o/n at 4°C ( to visualize GFP+ cells ) prior to freezing . 6 µm sections were immuno-stained as previously described [35] For detection of second harmonic signals , lymph node sections were exposed to polarized laser light ( 930 nm ) on a 2-photon microscope and the signals generated were detected in the 457–487 nm range using barrier filters and non-descanned PMT detectors . All other immuno-histochemical image acquisition and analysis of stained lymph node sections were done using a Nikon fluorescence microscope and the Nikon software ( NIS elements ) . Freshly isolated cells were stained with the antibodies purchased from eBioscience ( San Diego , CA ) or BD Biosciences ( San Jose , CA ) and were run on a FACSCalibur ( BD , San Jose , CA ) . For intracellular staining the cells were stimulated ex-vivo for 5 hours in complete media with Brefeldin A , either in the presence or absence of SIINFEKL peptide ( 1 µg/ml ) . Following surface staining , the cells were fixed with 4% PFA for 10 minutes at room temperature . Permeablization was done using 0 . 3% saponin in staining buffer . The cells were run on a FACSCalibur and results were analyzed using FlowJo software ( TreeStar Inc . , Ashland , OR ) . Statistical significance of differences between groups of mice was tested using the student's t test or ANOVA/Kruskal-Wallis test for multiple groups . In all the cases , p<0 . 05 was considered significant .
|
Toxoplasma gondii is a protozoan parasite that can infect a wide range of hosts , including humans . Infection with T . gondii is potentially life threatening in immuno-compromised individuals and it can be detrimental during pregnancy , often leading to abortion of the fetus . Dendritic cells are thought to play a vital role in the development of protective immunity to Toxoplasma gondii through their ability to produce immunological signals such as cytokines and also process and present parasite derived peptides to T cells . However , little is known about the actual interactions between these cell types in an intact organ , such as the lymph node , during infection . Using the technology of live imaging by 2-photon microscopy we have identified a very early window of time during infection when dendritic cells and T cells make sustained contacts with one another , which appears crucial for the generation of protective responses . We also show that substantial changes are induced in the lymph node micro-architecture as a result of infection , which in turn could have effects on immune responses to secondary pathogens . Understanding the interaction between these immune cells in vivo that leads to resistance to active infection would help in the design of better strategies to develop protective immune responses against this pathogen in immuno-compromised individuals .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunology/antigen",
"processing",
"and",
"recognition",
"immunology/immune",
"response",
"immunology/innate",
"immunity",
"immunology",
"infectious",
"diseases/protozoal",
"infections",
"immunology/immunity",
"to",
"infections"
] |
2009
|
Dynamic Imaging of CD8+ T Cells and Dendritic Cells during Infection with Toxoplasma gondii
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Phosphorylation relays are a major mechanism by which bacteria alter transcription in response to environmental signals , but understanding of the functional consequences of bacterial response regulator phosphorylation is limited . We sought to characterize how phosphorylation of the control of virulence regulator ( CovR ) protein from the major human pathogen group A Streptococcus ( GAS ) influences GAS global gene expression and pathogenesis . CovR mainly serves to repress GAS virulence factor-encoding genes and has been shown to homodimerize following phosphorylation on aspartate-53 ( D53 ) in vitro . We discovered that CovR is phosphorylated in vivo and that such phosphorylation is partially heat-stable , suggesting additional phosphorylation at non-aspartate residues . Using mass spectroscopy along with targeted mutagenesis , we identified threonine-65 ( T65 ) as an additional CovR phosphorylation site under control of the serine/threonine kinase ( Stk ) . Phosphorylation on T65 , as mimicked by the recombinant CovR T65E variant , abolished in vitro CovR D53 phosphorylation . Similarly , isoallelic GAS strains that were either unable to be phosphorylated at D53 ( CovR-D53A ) or had functional constitutive phosphorylation at T65 ( CovR-T65E ) had essentially an identical gene repression profile to each other and to a CovR-inactivated strain . However , the CovR-D53A and CovR-T65E isoallelic strains retained the ability to positively influence gene expression that was abolished in the CovR-inactivated strain . Consistent with these observations , the CovR-D53A and CovR-T65E strains were hypervirulent compared to the CovR-inactivated strain in a mouse model of invasive GAS disease . Surprisingly , an isoalleic strain unable to be phosphorylated at CovR T65 ( CovR-T65A ) was hypervirulent compared to the wild-type strain , as auto-regulation of covR gene expression resulted in lower covR gene transcript and CovR protein levels in the CovR-T65A strain . Taken together , these data establish that CovR is phosphorylated in vivo and elucidate how the complex interplay between CovR D53 activating phosphorylation , T65 inhibiting phosphorylation , and auto-regulation impacts streptococcal host-pathogen interaction .
Bacteria causing infections in humans must closely modulate virulence factor production in response to different environmental challenges [1] , [2] , [3] . It has long been recognized that two-component gene regulatory systems ( TCS ) are a major mechanism by which bacteria react to external stimuli , and thus are critical to the virulence of numerous pathogenic bacteria [4] , [5] , [6] , [7] . Although there is diversity in TCS composition [8] , standard TCS consist of a membrane-embedded histidine kinase that can respond to environmental signals by either phosphorylating or dephosphorylating a cognate response regulator , usually on an aspartate residue in the N-terminal receiver domain [9] . The aspartate phosphorylation status of the response regulator alters its gene regulation effect thereby allowing the organism to remodel its expression profile [10] . The critical role of TCS is exemplified by their status as possible targets for novel antimicrobials [11] , [12] , [13] , [14] . However , much remains to be learned about the mechanisms and effects of bacterial response regulator phosphorylation . One of the model systems for understanding how response regulators influence bacterial pathogenesis has been the control of virulence regulator ( CovR , also known as CsrR ) from group A Streptococcus [15] , [16] , [17] . GAS causes a wide range of infectious and post-infectious syndromes in humans [18] . CovR is a member of the OmpR/PhoB family of response regulators and is a key repressor of numerous GAS virulence factors such that CovR-inactivated strains are hypervirulent [15] , [19] , [20] . In vitro studies have shown that phosphorylation of CovR at amino acid residue aspartate-53 ( D53 ) results in homodimerization and increased DNA-binding affinity , but in vivo phosphorylation of CovR has not been demonstrated [21] , [22] , [23] . covR is co-transcribed with an adjacent gene encoding the sensor kinase CovS [15] . Although it has been assumed that CovS controls the D53 phosphorylation status of CovR , numerous groups have reported that inactivation of CovS produces a distinct phenotype from inactivation of CovR suggesting that factors in addition to CovS influence CovR phosphorylation and thus activity [19] , [21] , [24] , [25] . Recently , Agarwal et al . found that the GAS eukaryotic-like serine/threonine kinase Stk phosphorylates CovR on threonine residues in vitro although neither the exact site nor the functional consequences of such phosphorylation has been determined [26] . GAS Stk and CovR homologues are present in group B Streptococcus ( GBS ) , and GBS Stk has been shown to phosphorylate CovR on threonine-65 ( T65 ) [27] , [28] , [29] . Stk-mediated threonine phosphorylation of GBS CovR resulted in a decreased ability of CovR to be phosphorylated on D53 , decreased CovR binding to DNA from the cylX promoter , and relieved CovR-mediated repression of the cyl operon which encodes the potent β-hemolysin/cytolysin [29] , [30] , [31] . Whether GAS Stk influences CovR-mediated gene regulation in a fashion similar to GBS is unknown . To gain new insights into the functional consequence of GAS CovR phosphorylation on host-pathogen interaction , we performed a series of biochemical , genetic , and virulence assays . First , we used the recently developed Phos-Tag technology to demonstrate that CovR is phosphorylated in vivo . Using a combination of mass spectrometry , Phos-Tag assays , and targeted mutagenesis , we determined that Stk phosphorylates GAS CovR at T65 and that such phosphorylation negatively influences CovR phosphorylation on D53 . In this way , Stk phosphorylation of CovR on T65 significantly impacts GAS global gene expression and virulence . Moreover , we discovered that , in contrast to CovR-mediated gene repression , CovR-mediated activation of gene expression is not primarily determined by CovR D53 phosphorylation status . Taken together , these data provide crucial new information about how the phosphorylation status of the receiver domain of a TCS response regulator influences host-pathogen interaction and provide a key platform for achieving a fuller understanding of the mechanisms influencing response regulator phosphorylation status in vivo .
Although the importance of CovR phosphorylation has been well established in GAS and GBS over the past 15 years , in vivo phosphorylation of CovR has not been demonstrated in either species [22] , [27] , [28] , [29] , [30] , [32] , [33] , [34] . Recently , Phos-Tag gels , in which the migration of phosphorylated proteins is retarded compared to non-phosphorylated proteins , have been used to assay protein phosphorylation status in vitro and in vivo [35] , [36] , [37] , [38] . To investigate whether Phos-Tag gels would be suitable for assessing CovR phosphorylation , we first compared in vitro CovR phosphorylation using Phos-Tag gel and native polyacrylamide gel electrophoresis ( PAGE ) , which has been the typical method for studying CovR phosphorylation [22] , [39] . Purity of the recombinant proteins used in these assays is shown in Figure S1A in Text S1 . Phosphorylation of recombinant CovR by the small molecule phosphodonor acetyl phosphate induces homodimerization , which results in slower migration on a native polyacrylamide gel ( Figure 1A ) [22] . An alanine substitution at D53 abrogates phosphorylation at the altered site [22] and thereby homodimerization ( Figure 1A ) . Similarly , acetyl-phosphate mediated phosphorylation of wild-type CovR , but not CovR-D53A , could be readily detected using the Phos-Tag method , as demonstrated by the appearance of a higher migrating band in the phosphorylated sample ( Figure 1B ) . Heating of the CovR samples , which removes the heat-labile aspartate-phosphorylation , eliminated the higher running band , confirming that the Phos-tag assay was able to detect CovR aspartate-phosphorylation ( Figure 1B ) [22] . Next , we sought to use the Phos-Tag assay to determine whether CovR is phosphorylated in vivo . To this end , strain MGAS10870 , a serotype M3 strain which has been fully sequenced and is known to contain a wild-type CovR/S TCS [40] , and its isogenic CovR-inactivated derivative ( 10870ΔcovR ) were grown to mid-exponential phase in THY medium . The cells were pelleted , lysed , and cell lysates were run on a Phos-Tag gel , transferred to a nitrocellulose membrane , and probed with a polyclonal anti-CovR antibody . The performance of the anti-CovR antibody is shown in Figure S2 in Text S1 . For strain MGAS10870 , we observed two distinct bands reacting with the anti-CovR antibody which were at the same location as recombinant CovR and recombinant CovR phosphorylated with acetyl phosphate ( Figure 1C ) . These data are consistent with partial CovR phosphorylation in strain MGAS10870 during growth in a standard laboratory medium ( THY medium ) . Heating of the MGAS10870 cell extract led to the disappearance of the majority of the slower migrating band whereas treating of the sample with calf intestinal phosphatase ( CIP ) completely removed the slower migrating band ( Figure 1C ) . Conversely , no bands were observed in the lysate of strain 10870ΔcovR ( Figure 1C ) . Next we assayed the phosphorylation status of CovR grown in THY medium supplemented with 15 mM MgCl2 as Mg2+ is thought to increase CovR D53 phosphorylation [41] . Following growth in a high Mg2+ medium , only the slower migrating band was detected by the anti-CovR antibody suggesting that CovR phosphorylation is complete under the high Mg2+ condition ( Figure 1D ) . Given that GAS CovR and GBS CovR are highly similar ( 84% identity , 92% similarity at the amino acid level ) , we also assayed the cell lysate from the GBS strain SGBS001 and found that our anti-CovR antibody did react with the GBS cell lysate and that GBS CovR appears to be partially phosphorylated during growth in THY ( Figure 1E ) . Phosphorylation of GBS CovR was removed by heat or CIP-treatment . We conclude that the Phos-Tag assays can be used to determine GAS and GBS CovR phosphorylation status in vitro and in vivo and that during growth in a standard laboratory medium , the majority of GAS CovR phosphorylation is heat-labile , consistent with aspartate phosphorylation . The fact that some , but not all , CovR phosphorylation disappeared upon heating suggested that CovR may be phosphorylated at heat-stable sites , such as threonine , in addition to being phosphorylated at the heat-labile aspartate site [35] . It was recently shown that Stk phosphorylates CovR in vitro but the phosphorylation site was not identified [26] . Thus , we first sought to determine the amino acid residue in GAS CovR that is the target for Stk mediated phosphorylation . To this end , we overexpressed and purified the kinase domain of Stk ( StkKD ) from the serotype M3 strain MGAS10870 ( Figure S1A in Text S1 ) . StkKD encompasses the N-terminal 315 amino acids and has been shown previously to be sufficient to phosphorylate CovR on threonine residues in vitro [26] . CovR was incubated with StkKD , subjected to chymotrypsin or trypsin digestion , and then analyzed by LC/MS/MS ( see Materials and Methods ) . No specific phosphorylated peptide was detected in the trypsin digest . However , in the chymotrypsin digest , the CovR-derived peptide EVTRRLQTEKTTY was predicted to be phosphorylated at position 3 , which corresponds to T65 ( Figure 2A ) . In order to validate the site of phosphorylation we then instructed the mass spectrometer to specifically acquire MS/MS of only this phosphorylated peptide in addition to acquiring MS/MS/MS of specific fragments . Fragmentation of the peptide EVT65RRLQTEKTTY showed fragments that lost phosphoric acid ( m/z 804 , marked with blue arrow in Figure 1A ) as well as a specific y102+ fragment at m/z 648 . 61 , which was predicted to be RRLQTEKTTY . This fragment was not phosphorylated therefore suggesting that the phosphorylated amino acid residue was T65 . Further fragmentation of this y102+ fragment proved that this fragment was indeed RRLQTEKTTY ( Figure 2B ) . Thus , in vitro , StkKD phosphorylates CovR on T65 . We next sought to confirm our mass spectroscopy finding that T65 is the site of CovR phosphorylation by Stk and to investigate the relationship between CovR D53 and T65 phosphorylation . To this end , we generated a recombinant CovR variant with alanine at the T65 phosphorylation site ( CovR-T65A ) . We performed circular dichroism ( CD ) spectroscopy on CovR-T65A and the previously generated CovR-D53A ( Figure S1A in Text S1 ) to ensure that the mutations did not result in aberrantly folded proteins . The resulting CD spectra of all recombinant CovR variants were identical to the spectrum of the wild-type CovR protein indicating that our introduced changes had not altered the overall secondary protein structure ( Figure S1B in Text S1 ) . Given that CovR threonine phosphorylation is not expected to induce protein dimerization , native PAGE is not suitable for analysis of CovR threonine phosphorylation status . Thus , we used Phos-tag PAGE to assay for CovR T65 phosphorylation by incubating CovR with StkKD and then performing standard Western blot using the anti-CovR antibody . This approach eliminates the strong signal from highly phosphorylated ( and therefore appearing as several bands ) StkKD , which overwhelmed the weaker CovR-P signal when using anti-threonine antibodies ( data not shown ) . As depicted in Figure 3A , the Phos-tag analysis demonstrated wild-type CovR phosphorylation following incubation with StkKD . Although Jin et al . found GAS StkKD to be an Mn2+ dependent threonine kinase [42] , we did not observe any difference in StkKD-CovR phosphorylation reactions containing 10 mM Mg2+ or Mn2+ ions , respectively , in the kinase buffer ( Figure 3A ) . Therefore , we used 10 mM MgCl2 throughout the following experiments . Consistent with our mass spectrometry data , incubation of CovR-T65A with StkKD resulted in no detectable phosphorylation using the Phos-tag assay ( Figure 3A ) . In contrast , StkKD was able to phosphorylate CovR with an alanine substituted for threonine at position 73 ( CovR-T73A , data not shown ) , further supporting the specific role of T65 in Stk-dependent CovR phosphorylation . Having established that Stk phosphorylates CovR on T65 , we sought to investigate whether CovR D53 and T65 phosphorylation events influence each other . To this end , we generated the recombinant CovR variant T65E ( Figure S1A in Text S1 ) . Introduction of a negative charge at this position mimics constitutive phosphorylation of T65 ( i . e . a phospho-mimetic mutation ) [29] . Similar to the CovR-D53A and -T65A variants , we observed no difference in CD spectra for the CovR-T65E protein compared to wild-type indicating normal protein folding ( Figure S1B in Text S1 ) . Next , we determined whether the CovR variants could be phosphorylated in vitro by either acetyl-phosphate or StkKD . By Phos-Tag analysis , CovR-T65A could be phosphorylated by acetyl phosphate similar to wild-type CovR ( Figure 3B ) . However , analogous to the CovR-D53A protein , the T65E substitution in CovR completely impeded acetyl-phosphate mediated phosphorylation ( Figure 3B ) . Consequently , only a phosphor-mimetic ( T65E ) , not a neutral ( T65A ) mutation at T65 interferes with phosphorylation at CovR D53 . StkKD was unable to phosphorylate either the CovR-T65A or -T65E variants ( Figure 3C ) . Moreover , StkKD readily phosphorylated CovR-D53A to the point where we observed reproducibly higher amounts of phosphorylation following incubation with StkKD for the CovR-D53A protein compared to wild-type CovR ( Figure 3C ) . Hence , in vitro , the D53 and T65 CovR phosphorylation sites influence each other . To better understand the functional consequences of CovR phosphorylation , we next created the following GAS strains from the serotype M3 strain MGAS10870: a CovS-knockout strain ( 10870ΔcovS ) , a strain with an alanine at CovR position 53 ( CovR-D53A ) , a strain with an alanine at CovR position 65 ( CovR-T65A ) , and a strain with glutamate at CovR position 65 ( CovR-T65E ) ( Figure 4A ) . We previously had created the CovR knockout strain 10870ΔcovR [43] . The growth curves of the strains in a standard laboratory medium ( THY ) were indistinguishable ( Figure 4B ) , whereas the phenotypes of the various strains on sheep blood-agar plates were quite distinct ( Figure 4A ) . Compared to wild-type , the 10870ΔcovR , CovR-D53A , and CovR-T65E strains had a larger colony phenotype indicating increased production of the GAS hyaluronic acid capsule which is known to be negatively regulated by CovR [15] . Conversely , strains 10870ΔcovS and CovR-T65A had a phenotype similar to strain MGAS10870 . Consistent with these observations , strains 10870ΔcovR , CovR-D53A , and CovR-T65E produced significantly more capsule during growth in THY compared to strains MGAS10870 , 10870ΔcovS , and CovR-T65A ( Figure 4C ) . In many GAS strains , CovS positively influences the production of the cysteine proteinase , streptococcal pyrogenic exotoxin B ( SpeB ) [44] . Similarly , strain 10870ΔcovS had significantly decreased SpeB production compared to wild-type as measured by casein hydrolysis ( Figure 4D ) . No significant difference in SpeB production was observed between the CovR variant strains and strain MGAS10870 ( Figure 4D ) . To determine the genome-wide effects of alterations in CovR phosphorylation status on GAS gene expression , four replicates of each strain were grown to mid-exponential phase ( Figure 4B ) , and transcriptome analyses were performed using RNA-Seq . A minimum of 2 . 3 million paired reads were resolved per strain for a minimum average base coverage of 174 indicating excellent sequencing depth . Gene transcripts were detected for 1609 genes or approximately 83% of the 1951 genes in strain MGAS10870 . Principal components analysis , which creates a global view of the variance in the data set , showed that strains 10870ΔcovR , CovR-D53A , and CovR-T65E were the most distant from wild-type ( Figure S3 in Text S1 ) . Strain 10870ΔcovS was closest to wild-type whereas strain CovR-T65A had a phenotype intermediate between wild-type and strain 10870ΔcovR . Gene transcript levels were considered significantly different between the wild-type and a derivative strain if the mean transcript level had at least a 1 . 5-fold change and the multiple-testing adjusted P value was ≤0 . 05 . Compared to wild-type , there were significant differences in transcript levels for 200 genes in strain 10870ΔcovR , or some 10% of the genome ( Table S1 ) . Known CovR-influenced genes whose transcript levels were higher in strain 10870ΔcovR included hasA , the initial gene in the hyaluronic acid capsule-encoding operon [45] , prtS , which encodes an IL-8 degrading enzyme [46] , and grab , which encodes the protein G-related α2-macroglobulin-binding protein [47] ( Figure 5A ) . Genes with decreased transcript level in the CovR knockout strain included the dipeptide permease encoding operon ( dppA-E ) [48] and gene spyM3_1493 which encodes a platelet acetyltransferase degrading enzyme known as esterase or Sse [49] . Consistent with D53 phosphorylation being critical to CovR function , the transcriptome of strain CovR-D53A was quite similar to that of the CovR-inactivated strain . Pairwise comparison of log2 transcript level ratios of strains CovR-D53A and 10870ΔcovR relative to the wild-type strain MGAS10870 showed a Pearson correlation r2 value of 0 . 65 ( P<0 . 001 ) . The transcript levels of genes encoding virulence factors well-established to be repressed by CovR such as hasA , prtS , and ska , which encodes the plasminogen-activating streptokinase [50] , were increased relative to wild-type in strain CovR-D53A ( Figure 5A ) . However , the transcript levels of the dipeptide permease operon and the esterase-encoding gene spyM3_1493 , although decreased in the CovR knockout strain , were not significantly altered compared to wild-type in the CovR-D53A strain ( Figure 5A ) . We previously found that changing T65 to glutamate ( T65E ) prevented phosphorylation of CovR at D53 by the small molecule phosphodonor acetyl phosphate in vitro . Thus we hypothesized that the CovR-T65E strain would have a transcriptome similar to the CovR-D53A strain . Indeed , among all the strains studied in this experiment , the Pearson correlation of log2 transcript levels ratios relative to the wild-type strain were the highest for strain CovR-D53A and CovR-T65E ( r2 = 0 . 86 ) ( Figure 5B ) . Genes whose transcript levels were significantly increased in strain CovR-T65E relative to wild-type included the key virulence factor-encoding genes hasA , mac-1 ( also known as ideS ) , which encodes an immunoglobulin degrading enzyme [51] , prtS , and sagA , which encodes the cytolysin streptolysin S [52] ( Figure 5A ) . Similar to strain CovR-D53A , we observed no difference in the transcript levels of the CovR-activated genes dppA and spyM3_1493 between strain CovR-T65E and strain MGAS10870 . The 10870ΔcovR , CovR-D53A and CovR-T65E strains each had approximately 200 genes with altered gene transcript levels relative to strain MGAS10870 . In contrast , the replacement of CovR T65 with an alanine resulted in a strain with only 111 genes whose transcript levels were significantly different compared to wild-type ( Figure 5C ) . The transcript levels of approximately half of the virulence factor encoding genes affected in the CovR-knockout strain were also affected in the CovR-T65A strain including ska , mac-1 , and prtS . Genes whose transcript levels were affected in the CovR-knockout and CovR-D53A strains but not in strain CovR-T65A included sagA and mf , which encodes a DNA degrading enzyme [53] . As we had observed for strains CovR-D53A and CovR-T65E , there was no significant transcript level difference compared to wild-type for the CovR-activated genes dppA and spyM3_1493 in strain CovR-T65A . In contrast to the profound transcriptome effects of altering the CovR phosphorylation sites D53and T65 , inactivating CovS had a relatively modest impact on GAS gene transcription during growth in THY ( Figure 5C ) . Only 39 genes had significantly different transcript levels between the CovS-knockout and wild-type strain , which was the lowest number of differentially transcribed genes observed for any of the strains studied . Also , the effect of CovS inactivation led a distinct pattern of differential gene expression compared to the strains in which CovR had been altered . Specifically , in the CovR-isoallelic strains , all significant transcript level differences in CovR-repressed genes involved an increase in transcript levels relative to wild-type ( Figure 5A ) . Conversely , CovS inactivation could result in either an increase or decrease in transcript level for CovR-repressed genes compared to wild-type , an effect that has been previously described for a CovS-inactivated serotype M1 strain [25] . For example , compared to strain MGAS10870 , mac-1 , prtS , and ska transcript levels were all significantly increased in strain 10870ΔcovS whereas ropB , which encodes an transcription factor activating speB expression [54] , and grab transcript levels were decreased ( Figure 5A ) . Adding Mg2+ to standard laboratory medium is known to increase the repression of a subset of CovR-regulated genes , presumably by increasing CovS-mediated CovR D53 phosphorylation ( Figure 1C ) [41] . Thus , we next sought to specifically analyze the response of CovR-regulated genes to Mg2+ in our isogenic and isoallelic strains using quantitative real-time PCR ( qRT-PCR ) . In accordance with previous data , in the wild-type strain MGAS10870 , we observed significantly higher gene transcript levels during growth in a low Mg2+ medium compared to a high Mg2+ medium for hasA , prtS , mac-1 , spyM3_0132 , and spyM3_0105 ( Figure 6A ) [41] , [55] . This effect did not appear to be due to altered CovR levels as there was no significant difference in covR gene transcript levels between the two media ( Figure 6A ) . Similarly , we observed no significant differences in transcript levels between the two media for sagA or dppA ( Figure 6A ) . Consistent with the idea that CovS phosphorylation on CovR D53 mediates the response to Mg2+ , we saw no difference in hasA , prtS , or spyM3_0105 gene transcript levels in either strain 10870ΔcovR , 10870ΔcovS , CovR-D53A , or CovR-T65E between growth in low and high Mg2+ concentration ( Figure 6B–D ) . Conversely , for strains MGAS10870 and CovR-T65A , the gene transcript levels of hasA , prtS , and spy_0105 were significantly decreased in the high Mg2+ medium consistent with the hypothesis that the CovR-T65A strain can still be phosphorylated on D53 in vivo . We next examined the CovR-activated genes dppA and spyM3_1493 . There was no difference in dppA transcript level in response to altered Mg2+ concentration for any of the studied strains ( Figure 6E ) whereas there was a significant decrease in the transcript level of spyM3_1493 in strains MGAS10870 and CovR-T65A ( Figure 6F ) under high Mg2+ condition . Thus , of the strains tested here , a Mg2+ response for CovR-regulated genes was only observed for strains MGAS10870 and CovR-T65A . The finding that some , but not all CovR-regulated genes , have altered gene transcript levels in the presence of increased Mg2+ concentration has previously been noted [41] , but the explanation for this observation is not known . One possibility that has been postulated is that Mg2+-responsive promoters are bound by CovR phosphorylated at D53 ( CovR-D53∼P ) with lower affinity compared to Mg2+ non-responsive promoters [41] . Consequently , Mg2+-responsive genes would only be fully repressed by CovR under conditions that increase CovR phosphorylation above that observed in a standard laboratory medium ( compare Figure 1C and 1D for different CovR phosphorylation levels under different growth conditions ) . To test this hypothesis , we measured the DNA binding properties of wild-type CovR-D53∼P for the Mg2+ non-responsive promoters covR and dppA in comparison to the Mg2+ responsive promoters prtS and hasA . Unexpectedly , we observed that CovR-D53∼P bound to DNA from both groups with similar affinity ( Figure S4 in Text S1 ) . For all promoters tested , CovR-D53∼P mediated shifts began at CovR concentration of 0 . 1–0 . 2 µM to form a low molecular weight complex; at ∼1 µM the higher molecular weight complex became more prominent . Hence , in vitro DNA affinity alone does not seem to be the decisive factor for the different response of CovR regulated promoters towards Mg2+ ions . However , these data do not rule out differential CovR-DNA affinity in vivo given the complex nature of CovR-DNA interaction in the bacterial cell [16] . We hypothesize that the primary functional effect of CovR T65 phosphorylation is to prevent phosphorylation at D53 , and a previous study found that recombinant CovR-D53A bound to DNA from the has promoter with the same affinity as unphosphorylated wild-type CovR [22] . However , in group B Streptococcus , recombinant CovR-T65E was unable to bind to DNA from the promoter of CovR-regulated gene cylX [29] . Thus , we sought to determine the DNA binding characteristics of GAS CovR-T65E compared to wild type CovR and CovR-D53A . To this end , ∼300 bp DNA fragments that encompass the complete promoter regions of the CovR-regulated genes hasA , prtS , and sagA were amplified from MGAS10780 genomic DNA [33] , [46] , [56] . Both CovR-D53A and CovR-T65E bound to all of the tested promoters ( Figure 7 and Figure S5 in Text S1 ) . The binding affinity of CovR-D53A and CovR-T65E was similar to that of unphosphorylated wild-type CovR , with initial shifts starting at 0 . 25–0 . 5 µM protein concentration ( formation of a low molecular weight complex ) and a full shift at ∼1 . 5 µM protein concentration ( Figure 7 ) . The specificity of CovR DNA binding was ascertained using a promoter that is not CovR-regulated , adcR ( Figure S5 in Text S1 ) . To test whether CovR phosphorylation affects GAS virulence , outbred CD-1 mice were challenged intraperitoneally with the various CovS- or CovR-inactivated and CovR isoallelic strains and followed for near-mortality over 7 days . As expected , there was a significant survival difference amongst the mice challenged with the 6 strains ( P<0 . 001 by Mantel-Cox log rank test , Figure 8A ) . Specifically , strain MGAS10870 was less virulent compared to the other five strains ( P<0 . 001 after accounting for multiple comparisons ) . There was no significant difference in survival among mice infected with strains 10870ΔcovR , 10870ΔcovS , or CovR-T65A ( P = 1 . 0 ) . However , the survival time was significantly shorter for mice infected with strains CovR-D53A or CovR-T65E compared to strains 10870ΔcovR , 10870ΔcovS , or CovR-T65A ( P<0 . 01 for all comparisons ) . No significant difference in survival was observed between mice infected with strain CovR-D53A or CovR-T65E ( P = 0 . 19 ) . We sought to gain insight into the survival differences noted in the animal challenge experiment by determining the gene expression profile of bacteria during infection . To this end , we euthanized 4 animals per infecting strain 24 hours after infection , isolated GAS RNA from the blood of infected animals , and analyzed select gene transcript levels . As expected , the transcript levels of hasA , sagA , and prtS genes were significantly higher in the CovR-inactivated and CovR-isoallelic strains compared to wild-type ( Figure 8B , data not shown ) . The transcript levels of ska were significantly lower in the wild-type strain compared to the other strains , but ska transcript levels were also lower in strain 10870ΔcovS and CovR-T65A compared to strains 10870ΔcovR , CovR-D53A , and CovR-T65E ( Figure 8C ) . Similarly to what we had observed during growth in THY , inactivation of CovS significantly decreased speB transcript level and significantly increased spyM3_1493 transcript level compared to wild-type and the other tested strains ( Figure 8D , 8E ) . Moreover , we observed decreased transcript level of spyM3_1493 and dppA specifically in strain 10870ΔcovR compared to the other tested strains ( Figure 8E , 8F ) . Our in vitro experiments showed that mutation of CovR T65 to alanine impedes Stk-mediated phosphorylation , while having no impact on phosphorylation of D53 by acetyl-phosphate . Hence , we predicted that the concentration of CovR-D53∼P in the CovR-T65A strain would be equal or even higher than in the parental wild type strain leading to pronounced CovR-mediated gene repression and decreased virulence . However , our expression and animal data did not confirm this hypothesis as the CovR-T65A strain showed increased virulence compared to strain MGAS10870 . As CovR is known to repress its own expression [57] , we compared the CovR transcript and protein levels in wild type strain MGAS10780 , the CovR-deletion strain , and the CovR-T65A isoallelic strain using qRT-PCR and Western blot analysis , respectively . As expected no CovR signal was detected in strain10870ΔcovR ( Figure 9A ) . However , the amount of CovR was significantly higher in the wild type compared to the CovR-T65A strain under both high and low Mg2+ growth conditions ( Figure 9A ) . Similarly , the level of covR transcript was significantly higher in strain MGAS10870 compared to the CovR-T65A isoallelic strain ( Figure 9B ) . Finally , during infection , we also observed significantly decreased covR transcript levels in the CovR-T65A strain compared to strain MGAS10870 ( Figure 9B ) . Consequently , at least part of the characteristics of the CovR-T65A strain is likely a result of decreased covR expression due to increased CovR self-repression and thus lower CovR levels compared to wild-type .
Until recently , studies of how protein phosphorylation participates in prokaryotic signal transduction have mainly focused on linear TCS pathways that involve phosphorylation of aspartate in response regulators by their cognate histidine kinase [9] . Increasingly , however , it is being recognized that the phosphorylation status of response regulators can be influenced by a multitude of factors , including phosphorylation on non-aspartate residues , clearly placing response regulators into the wider gene regulation network [28] , [58] , [59] . Understanding the mechanisms influencing the phosphorylation status of bacterial regulator proteins and determining how such phosphorylation ultimately influences bacterial gene expression is critical to a more complete understanding of bacterial pathogenesis . Herein we demonstrate that the key GAS response regulator CovR is phosphorylated in vivo and that CovR phosphorylation at both aspartate and threonine residues profoundly influences GAS global gene expression and virulence . The recognition of CovR in 1998 as a negative regulator of GAS hyaluronic acid capsule production was accompanied by the observation that CovR is a OmpR/PhoB family member , and as such , contains a highly conserved aspartate phosphorylation site [15] . It was also determined at that time that the covR gene is located immediately upstream of covS and that the two genes are co-transcribed , although mono-cistronic covR transcripts have also been reported [15] , [60] . This combination of observations has led to the supposition that CovS controls CovR aspartate phosphorylation status analogous to the situation observed for the well-studied EnvZ/OmpR TCS in Escherichia coli , although CovS has never been directly shown to phosphorylate CovR in vitro or in vivo [16] . Over the past 15 years , numerous investigations have demonstrated the critical role of CovR D53 phosphorylation in CovR-mediated gene repression , mainly relying on in vitro binding assays and transcriptional reporter systems [22] , [32] , [56] , [57] . However , up to now , demonstration of CovR phosphorylation in vivo has been lacking . Our finding that a Phos-Tag assay can be used to measure GAS and GBS CovR phosphorylation status in vivo opens extensive possibilities into understanding the mechanisms and impact of streptococcal response regulator phosphorylation . Moreover , the fact that the CovS-inactivated and CovR-D53A strains had dramatically different transcriptomes provides additional impetus to study which factors , other than CovS , influence CovR D53 phosphorylation . In addition to demonstrating CovR phosphorylation in vivo , another key finding of this work was the identification of T65 as the target of Stk phosphorylation in CovR using both mass spectrometry and targeted mutagenesis strategies . A previous work had established that recombinant Stk phosphorylates CovR on threonine residues but did not establish the phosphorylation site [26] . In contrast to the highly specific phosphotransfer in TCS , eukaryotic-like serine/threonine kinases , such as Stk , are well known to have multiple targets , including cell-wall division regulating proteins that are critical to cellular homeostasis [61] , [62] , [63] . Thus , genetic inactivation of Stk or its cognate phosphatase , Stp , as has previously been done in serotype M1 GAS strains , is unlikely to generate information specifically relevant to threonine phosphorylation of CovR [42] , [64] . For example , in serotype M1 GAS strains , inactivation of both Stk and its cognate phosphatase , Stp , resulted in decreased virulence , probably as a result of their pleiotropic effects on GAS physiology [26] , [64] . Thus , once we established the site of CovR-threonine phosphorylation , we used a combination of deletion ( ΔcovR , ΔcovS ) , phosphorylation silencing ( CovR-D53A and CovR-T65A ) , and phosphorylation mimicking ( CovR-T65E ) mutations to comprehensively assess the functional consequences of CovR phosphorylation . Our data indicate that the combination of competing CovR D53 and T65 phosphorylation enables the integration of thus far unknown signals sensed by Stk into the regulatory network in order to fine-tune CovR/S-mediated gene regulation during GAS host-pathogen interaction . One surprising finding from this study was that the CovR-D53A and CovR-T65E strains were more virulent compared to strain 10870ΔcovR . A likely explanation for this finding can be gleaned from our transcriptome data . Whereas CovR-mediated repression of gene expression strongly depended on phosphorylation of D53 ( which is abolished in strains CovR-D53A and CovR-T65E ) , it had minimal effect on CovR-mediated gene activation . A possible target to explain the virulence effects of this differential gene regulation is spyM3_1493 , which encodes a platelet-activating factor acetylhydrolase recently shown to be critical for GAS pathogenesis [65] . Review of previously published microarray data from serotype M3 GAS confirms that spyM3_1493 transcript levels were lower in CovR-inactivated strains compared to the wild-type [41] , [43] . Similar findings of lower transcript levels in the CovR-inactivated , but not the CovR-D53A and CovR-T65E , strains were also observed for the dpp operon , which encodes proteins involved in amino acid uptake [48] . Apparently , merely the presence of CovR , not its phosphorylation status , is crucial for the regulation of these genes . The mechanism of CovR-mediate gene activation is unknown as neither CovR nor CovR-D53∼P was sufficient to activate transcription from the dppA promoter in vitro despite the fact that CovR specifically binds to the dppA promoter [48] . Thus , whereas nearly all previous GAS CovR related work has focused on CovR-mediated gene repression , our data provide new impetus to better elucidate the mechanism underlying CovR gene activation . Moreover , these data may provide an explanation for why the majority of naturally occurring CovR variation identified in strains causing invasive infection involves alterations in N-terminal amino acid residues , rather than truncations of the CovR protein as are commonly observed for CovS [43] , [66] . T65 has also previously been identified as the site for Stk-mediated phosphorylation of CovR in GBS [29] . However , despite significant parallels , such as the site of phosphorylation and negative interplay between the two phosphorylation sites [28] , [29] , [30] , there are some striking differences between GAS and GBS in terms of the effect of CovR T65 phosphorylation . For example , GBS CovR-T65E was completely unable to bind to DNA from the CovR-regulated cylX promoter [29] . In contrast , we found that recombinant GAS CovR-T65E and CovR-D53A bound DNA from several CovR-regulated promoters at concentrations equivalent to unphosphorylated wild type CovR , which is consistent with our transcript data showing that the CovR-T65E and CovR-D53 strains maintained CovR-mediated gene activation profiles . Thus , in GAS , it appears that Stk-mediated phosphorylation of CovR T65 reduces , but does not completely abrogate CovR-DNA binding as was observed in GBS . Given that GAS CovR D53 phosphorylation increases interaction with RNA polymerase in addition to enhancing CovR-DNA interaction [22] , GAS CovR T65 phosphorylation likely has additional consequences besides affecting CovR DNA binding affinity . Another key difference between the CovR system in GAS and GBS is that GAS CovR represses its own transcription whereas GBS CovR is self-activating [30] , [57] . There is significant variance in the covR promoter regions between GAS and GBS , including differences at previously identified key GAS CovR binding sites [57] . Abolishing CovR threonine phosphorylation in GBS via the T65A substitution increased covR transcript level whereas we observed decreased covR transcript and decreased CovR expression in GAS CovR-T65A [30] . Interestingly , in GBS the CovR-T65A variant was also hypervirulent in mice compared to wild-type and hypovirulent compared to the CovR-D53A and CovR-T65E strains , which was the same phenotypic hierarchy we observed in GAS [30] . These and other data on CovR-Stk interaction in GAS and GBS raise the important question of how T65 phosphorylation hampers D53 phosphorylation and vice versa [26] , [42] . The best studied example of dual-site phosphorylation in a prokaryotic pathogen concerns the histidine-containing phosphocarrier ( HPr ) protein , which can be phosphorylated on histidine-15 as well as serine-46 [67] . The various phosphorylation states of HPr regulate its interaction with other proteins as exemplified by the fact that HPr-S46-P , but not HPr-H15∼P can interact with the regulatory protein catabolite control protein A ( CcpA ) [68] . Conversely , HPr-His15∼P , but not HPr-S46-P serves as component of the phosphorelay in the phosphoenol-phosphotransferase system ( PTS ) regulating PTS-sugar transport [67] . In contrast to HPr , it does not appear that the phosphorylated forms of CovR are active in distinct functional systems but instead serve to influence the final effect of CovR on gene expression . Rather than obstructing specific protein-protein interactions ( e . g . CovR-CovS ) , it is likely that CovR T65 phosphorylation induces an allosteric change in the CovR N-terminal receiver domain that serves to inhibit D53 phosphorylation by interfering with the general activation mechanism for OmpR/PhoB family members [69] . Such a change would explain why even the small molecule phosphodonor acetyl phosphate is unable to phosphorylate CovR-T65E . Similarly , although the CovR homolog OmpR is not known to be regulated by serine/threonine phosphorylation , fluorescence-labeling of OmpR cysteine-67 , which corresponds to T65 in CovR , also impaired OmpR aspartate-phosphorylation and vice versa [70] . A crystal structure of the N-terminal domain of CovR is not available , but modeling of CovR on the structure of the related response regulator PhoP in complex with the phosphomimic BeF3− ( PBD code 2PL1 ) shows that D53 and T65 are ∼9 Å apart meaning that interference due to direct electrostatic repulsion can be excluded [71] . We are currently engaged in generating crystal structures of the N-terminal domain of CovR and its various phosphorylated forms in an attempt to better understand the molecular consequences of CovR dual-site phosphorylation . In summary , we have employed a combination of biochemical , genetic , and virulence assays to generate new insights into how phosphorylation of CovR mediated by distinct pathways affects GAS pathogenesis . Further studies of how bacteria modulate the phosphorylation status of regulatory proteins may generate new opportunities to prevent or treat serious bacterial infections .
This study was carried out in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by MD Anderson Animal Care and Use Committee ( Protocol Number: 07-09-09131 ) . All efforts were made to minimize suffering . The strains and plasmids used in this work are presented in Table 1 , and primers used for strain creation are listed in Table S2 . Strains were grown in a nutrient-rich standard laboratory medium ( Todd-Hewitt broth with 0 . 2% yeast extract ( THY ) ) at 37°C with 5% CO2 with 15 mM MgCl2 added when noted to create a high Mg2+ condition [41] . THY without supplemental MgCl2 has previously been determined to have a Mg2+ concentration of ∼1 mM [72] . When appropriate , spectinomycin and chloramphenicol were added at 150 µg/mL and 10 µg/mL , respectively . Strain MGAS10870 is a fully-sequenced , invasive , serotype M3 strain that contains a wild-type covRS operon [40] . Strains 10870ΔcovR and 10870ΔspeB have been previously described [43] , [73] . Strain 10870ΔcovS was created by replacing the covS gene in strain MGAS10870 with a spectinomycin resistance cassette via insertional inactivation as described [17] , [25] . Derivatives of strain MGAS10870 that differed only by the presence of a single amino acid replacement were created using the chloramphenicol-resistant , temperature-sensitive plasmid pJL1055 ( gift of D . Kasper ) as described [74] . For each of the CovR strains derived from strain MGAS10870 , sequencing of the entire covRS operon , as well as the mga and emm genes , was performed to check for the presence of spurious mutations that could have developed during the strain construction process ( none were found ) . Strain SGBS001 is a serotype V group B Streptococcus strain isolated from human blood in Houston . Recombinant CovR was isolated from plasmid pTXB1-covR using the IMPACT Protein Purification System ( New England Biolabs ) , which allows for recovery of soluble CovR isoforms lacking any non-native residues ( e . g . no His-tag ) [39] . To generate CovR variants , single nucleotide exchanges were introduced into pTXB1-covR via Quick-change mutagenesis ( Stratagene ) using the respective primer pairs ( see Table S2 ) . Wild type and variant CovR proteins were overexpressed in E . coli BL21/pLysS at 18°C overnight and purified to ≥95% homogeneity as described previously [39] . All CovR proteins were extensively buffer exchanged to 50 mM CAPS pH 10 . 0 , 100 mM NaCl . Purified CovR protein was used to immunize rabbits to generate anti-CovR antibody ( Covance , Denver , PA ) . The specificity of the anti-CovR antibody for CovR is shown in Figure S2 . The isolated Stk kinase domain ( StkKD ) has been shown previously to be sufficient to phosphorylate CovR [26] . Thus , recombinant StkKD was generated by amplifying DNA encoding the Stk kinase domain ( amino acids 1–315 ) from MGAS10870 . The resulting PCR product was cloned into pET15b ( Novagen ) via NdeI and XhoI . The N-terminal His-tagged StkKD was overexpressed in E . coli BL21/pLysS . Cells were induced with 1 mM IPTG at an OD ∼0 . 6 , incubated for five hours at 20°C and harvested by centrifugation . After lysing the cells in buffer containing 20 mM Tris/HCl pH 8 . 0 , 200 mM NaCl , 20 mM imidazole , and 10% glycerol , StkKD protein was purified over a Ni-NTA column and eluted with 200 mM imidazole . The protein was concentrated to ∼10 mg/ml and stored at −20°C in 20 mM Tris/HCl pH 8 . 0 , 150 mM NaCl , 40% glycerol . The resultant StkKD protein was ∼% pure ( Figure S1A ) . Wild type and variant CovR proteins were phosphorylated on D53 for 2 h at 37°C in phosphorylation buffer containing 50 mM Tris/HCl pH 8 . 0 , 10 mM MgCl2 , 3 mM DTT , and 32 µM acetyl-phosphate ( Sigma ) , as previously described [56] . Threonine phosphorylation of CovR was performed by incubating wild type or variant CovR proteins for 30 min at 37°C with a three-fold excess of StkKD in phosphorylation buffer containing 100 mM Tris/HCl pH 7 . 5 , 10 mM MgCl2 or MnCl2 , 1 mM DTT , and 10 mM ATP . To detect phosphorylated CovR species we used Phos-tag SDS polyacrylamide ( PAA ) gels which contain a phosphate-binding reagent that specifically retards the migration of phosphorylated proteins , thereby allowing for resolution between phosphorylated and non-phosphorylated protein species [35] . The phosphorylation samples were separated on 12% Phos-tag SDS-PAA gels containing 100 µM Phos-tag solution ( Wako Pure Chemical Industries Ltd , Richmond , VA ) and 200 µM MnCl2 for 70 min at 180 V . The gel was washed in transfer buffer ( SDS running buffer containing 20% MeOH and 1 mM EDTA ) for 15 min . The proteins were then transferred onto a nitrocellulose membrane ( 0 . 45 µm , Bio-Rad ) using a Trans-blot SD semi-dry electrophoretic transfer cell ( Bio-Rad ) for 15 min at 15 V . After blocking the membrane overnight in 20 mM Tris/HCl pH 7 . 5 , 150 mM NaCl , 0 . 05% Tween 20 , and 5% dry milk , it was incubated for 1 h with affinity purified anti-CovR antibody at a 1∶5 , 000 dilution with blocking solution . The secondary antibody , goat anti-rabbit IgG ( Pierce ) , was diluted 1∶10 , 000 . The blot was developed using the SuperSignal West Pico Chemiluminescent Substrate ( Thermo Scientific ) . GAS and GBS strains were grown in 100 ml of THY or THY supplemented with 15 mM MgCl2 to OD = 0 . 5 and harvested by centrifugation . Cell lysates were prepared by the rapid preparation method previously described taking care to always keep the lysates chilled to minimize spontaneous dephosphorylation [36] . A total protein amount of 70 µg as determined by Bradford assay ( Bio-Rad ) was loaded on the gel for each sample . As phosphorylation controls , wild type cell lysates were either boiled at 100°C for 1 min , which specifically removes the heat labile aspartate phosphorylation , or incubated with 40 units calf intestine phosphatase ( CIP , New England Biolabs ) at 37°C for 10 min , which completely removes any phosphorylation . Samples were electrophoresed for 80 min at 150 V on a 10% Bis-Tris buffered Zn2+-Phostag SDS-PAGE . This allows the separation of unphosphorylated and phosphorylated proteins under neutral pH [38] . Subsequently , CovR species were detected by standard Western blotting using anti-CovR antibodies . Wild type and mutant CovR proteins were diluted to a concentration of 0 . 4 mg/ml in 10 mM potassium phosphate , pH 7 . 5 , 10 mM NaF prior to measurements . Far-UV ( 200–260 nm ) spectra were recorded on a Jasco J-810 spectropolarimeter at 37°C and a scan speed of 20 nm/min as described [43] . 15 µg of recombinant CovR was phosphorylated using StkKD as described above . The entire reaction was run on a 12% SDS polyacrylamide gel . The band corresponding to CovR was excised and 50 pmol of in vitro phosphorylated CovR was diluted into 45 µl of 0 . 1 M ammonium bicarbonate , reduced with 2 µl 0 . 1 M DTT and alkylated with 2 µl 0 . 2 M iodoacetamide . The protein was digested with 1 µg of chymotrypsin ( Roche , Indianapolis , IN ) at 25°C or 1 µg of trypsin at 37°C overnight . 10 µl of the peptide mixture was analyzed by automated microcapillary liquid chromatography-tandem mass spectrometry ( LC-MS-MS ) . The application of a 1 . 8 kV distal voltage electro-sprayed the eluted peptides directly into the LTQ Orbitrap XL ion trap mass spectrometer equipped with a nanoLC electrospray ionization source ( ThermoFinningan ) . Full masses ( MS ) spectra were recorded on the peptides over a 400–2000 m/z range at 60 , 000 resolution in the Orbitrap , followed by five tandem mass ( MS/MS ) events sequentially generated in a data-dependent manner on the first , second , third , fourth and fifth most intense ions selected from the full MS spectrum ( at 35% collision energy ) . Mass spectrometer scan functions and HPLC solvent gradients were controlled by the Xcalibur data system ( ThermoFinnigan ) . MS/MS spectra were extracted from the RAW file with ReAdW . exe ( http://sourceforge . net/projects/sashimi ) . The MS/MS data were searched with Inspect [75] against the MGAS315 Streptococcus pyogenes database ( NC_004070 ) with optional modifications: +15 . 9994 on methionine , +57 . 0214 on cysteine , and +79 . 9663 on threonine , serine , and tyrosine , respectively . Only peptides with at least a P-value of 0 . 01 were analyzed further . Data from keratins and trypsin were excluded from further analysis . Peptides identified by the software to be phosphorylated were manually verified . In addition , further verification was performed by analyzing putative phosphorylated peptides in targeted MS/MS and MS/MS/MS modes . The amount of cell-associated capsular polysaccharide was done as previously described using GAS grown to late-exponential phase ( OD600 = 0 . 9 ) [15] . Functional SpeB protease activity was determined using casein hydrolysis as described [76] . RNA was purified from various GAS strains grown to mid-exponential phase using an RNeasy mini kit ( Qiagen ) . 1 µg of RNA per sample was converted to cDNA using a High Capacity Reverse Transcription Kit ( Applied Biosystems ) . TaqMan real-time qRT-PCR ( primers and probes listed in Table S2 ) was performed on an Applied Biosystems Step-One Plus System as described [77] . All samples were done at least in duplicate on two separate occasions and analyzed in duplicate . To compare gene transcript levels between the wild-type and the various derivative strains , a two-sample t-test ( unequal variance ) was applied with a P value of <0 . 05 and a mean transcript level of at least 1 . 5-fold change being considered statistically significant . For RNA-Seq analysis , strains were grown in quadruplicate to mid-exponential phase and RNA was isolated as for TaqMan qRT-PCR . First and second strand cDNA synthesis was performed on 500 ng of RNA using the Ovation Prokaryotic RNA-Seq System ( NuGEN ) . The resulting cDNA was fragmented to 200 bp ( mean fragment size ) with the S220 Focused-ultrasonicator ( Covaris ) and used to make barcoded sequencing libraries on the SPRI-TE Nucleic Acid Extractor ( Beckman-Coulter ) . No size selection was employed . Libraries were quantitated by qPCR ( KAPA Systems ) , multiplexed and 8 samples per lane were sequenced on the HiSeq2000 using 76 bp paired-end sequencing . The raw reads in FASTQ format were aligned to the reference genome , Streptococcus pyogenes MGAS315 ( GI:21905618 ) , using Mosaik alignment software ( version: 1 . 1 . 0021 , http://code . google . com/p/mosaik-aligner/ ) with the following alignment parameters: 8 percent maximal percentage read length allowed to be errors and 50 percent minimal percentage of the read length aligned . Duplicate fragments with a lower alignment quality were discarded . Next , the overlaps between aligned reads and annotated genes were counted using HTSeq software ( http://www-huber . embl . de/users/anders/HTSeq/doc/overview . html ) . If the number of overlapped read of any given gene was less than one per million total mapped read for all samples , this gene was excluded from further analysis . 330 ( 17% ) of total 1951 genes were removed due to low expression . The gene counts were normalized using the scaling factor method [78] . A negative binomial generalized linear model was fitted to each gene . Then a likelihood-ratio test was applied to examine if there was a difference in the gene transcript levels among the six strains [78] . The Benjamini-Hochberg method was used to control false discovery rate ( FDR ) [79] . Next , pair-wise comparisons using the likelihood ratio test were performed to compare the gene transcript levels between pairs of strains with the Holm's method used to calculate adjusted P-values to correct for multiple testing . Transcript levels were considered significantly different only if the mean transcript level difference was ≥1 . 5-fold and the final , adjusted P value was less than 0 . 05 . The ∼300 bp encompassing promoter regions of selected CovR regulated genes were amplified by PCR from MGAS10870 genomic DNA using the respective primer pairs listed in Table S2 . The purified PCR products ( 0 . 4 µg ) were incubated with indicated amounts of various CovR isoforms at 37°C for 15 min in TBE-buffer ( 89 mM Tris , 89 mM borate , 1 mM EDTA , 5% glycerol , and 10 µg/ml polydI:dC ( Sigma ) ) as described [43] . Samples were then separated on a 6% TBE-PAA gel for 70 min at 120 V and stained with ethidium bromide . 20 female outbred CD-1 Swiss mice per strain ( Harlan-Sprague-Dawley ) were injected intraperitoneally with 1 . 0×107 GAS CFU and monitored for near-mortality . Differences in survival were calculated using a Kaplan-Meier survival analysis with Bonferroni's correction for multiple comparisons . For in vivo gene expression assays , four mice per strain were euthanized 24 hours after infection and blood was isolated via cardiac puncture . Total RNA was isolated from blood using the QIAamp RNA Blood Mini Kit ( Qiagen ) with DNA contamination being eliminated using Turbo DNAfree ( Ambion ) . Bacterial RNA was preferentially isolated from the total blood RNA using the MICROBEnrich Kit ( Invitrogen ) according to the manufacturer's instruction . cDNA was created from the RNA as previously described . RNA samples without reverse transcriptase were included as negative controls to ensure that no contaminating DNA was present in any of the samples . TaqMan real-time qRT-PCR was performed in triplicate on an Applied Biosystems Step-One Plus system as previously described [77] . RNA-Seq data have been deposited at the short-read archive under accession # PRJNA238945 .
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Group A Streptococcus ( GAS ) causes a variety of human diseases ranging from mild throat infections to deadly invasive infections . The capacity of GAS to cause infections at such diverse locations is dependent on its ability to precisely control the production of a broad variety of virulence factors . The control of virulence regulator ( CovR ) is a master regulator of GAS genes encoding virulence factors . It is known that CovR can be phosphorylated on aspartate-53 in vitro and that such phosphorylation increases its regulatory activity , but what additional factors influence CovR-mediated gene expression have not been established . Herein we show for the first time that CovR is phosphorylated in vivo and that phosphorylation of CovR on threonine-65 by the threonine/serine kinase Stk prevents aspartate-53 phosphorylation , thereby decreasing CovR regulatory activity . Further , while CovR-mediated gene repression is highly dependent on aspartate-53 phosphorylation , CovR-mediated gene activation proceeds via a phosphorylation-independent mechanism . Modifications in CovR phosphorylation sites significantly affected the expression of GAS virulence factors during infection and markedly altered the ability of GAS to cause disease in mice . These data establish that multiple inter-related pathways converge to influence CovR phosphorylation , thereby providing new insight into the complex regulatory network used by GAS during infection .
|
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2014
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Dual-Site Phosphorylation of the Control of Virulence Regulator Impacts Group A Streptococcal Global Gene Expression and Pathogenesis
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The spread of Aedes albopictus , a vector for re-emergent arbovirus diseases like chikungunya and dengue , points up the need for better control strategies and new tools to evaluate transmission risk . Human antibody ( Ab ) responses to mosquito salivary proteins could represent a reliable biomarker for evaluating human-vector contact and the efficacy of control programs . We used ELISA tests to evaluate specific immunoglobulin G ( IgG ) responses to salivary gland extracts ( SGE ) in adults exposed to Aedes albopictus in Reunion Island . The percentage of immune responders ( 88% ) and levels of anti-SGE IgG Abs were high in exposed individuals . At an individual level , our results indicate heterogeneity of the exposure to Aedes albopictus bites . In addition , low-level immune cross-reactivity between Aedes albopictus and Aedes aegypti SGEs was observed , mainly in the highest responders . Ab responses to saliva could be used as an immuno-epidemiological tool for evaluating exposure to Aedes albopictus bites . Combined with entomological and epidemiological methods , a “salivary” biomarker of exposure to Aedes albopictus could enhance surveillance of its spread and the risk of arbovirus transmission , and could be used as a direct tool for the evaluation of Aedes albopictus control strategies .
The incidence of arthropod-borne disease is on the rise and mosquito-borne diseases in particular constitute a world-wide threat [1] . In Asia , Africa and South America , arbovirus diseases are re-emerging , notably dengue and chikungunya . According to the World Health Organization , there are 50 million cases of dengue fever every year and the number of countries declaring cases is increasing [2] Chikungunya is an emerging arbovirus [3] and several outbreaks have been recorded , such as the 2006 epidemic on Reunion Island in the Indian Ocean [4] . The threat of these diseases in the developed world is real with , in addition to the chikungunya outbreak in Italy in 2007 [5] , sporadic autochthonous cases of dengue and chikungunya recently reported in Southern France [6] . Therefore , epidemiological tools for evaluating such risks are urgently needed in both developing and developed countries . Aedes aegypti and Aedes albopictus are both vectors of the dengue and chikungunya viruses , and Ae . albopictus populations are dramatically expanding worldwide . Epidemiological evaluation of Aedes-borne diseases is currently based on pathogen detection in human populations and entomological methods . The exposure of human populations to Aedes is currently evaluated by mapping breeding sites and using mosquito-capture strategies . But these methods have substantial limitations when it comes to large-scale studies in the field , e . g . vector density and transmission risk are estimated by counting immature Aedes in breeding sites to derive House and Breteau Indices , a process which is too demanding for regular implementation in the field [7] , especially in the urban setting . In addition , current methods for evaluating Aedes exposure are mainly applicable at the population level and cannot be used to gauge the heterogeneity of individual exposure . In order to improve vector control and follow the risk of arbovirus transmission , much effort is being devoted to developing new , simple , rapid and sensitive indicators to evaluate human exposure to Aedes bites and thus the risk of arbovirus transmission in exposed populations . One promising approach is based on the idea that exposure could be directly assessed by measuring human-vector contact as reflected by the human antibody ( Ab ) response to arthropod salivary proteins [8] . At the time of biting , the female mosquito injects saliva containing biologically active molecules to favour feeding and some of these are highly immunogenic [9] . Human Ab responses to the saliva of a number of vectors , including Triatoma ( Chagas disease ) [10] and Phlebotomus ( Leishmaniasis ) [11] , have been identified as promising biomarkers for vector exposure . Ab responses to the saliva of Glossina ( the vector of Human African Trypanosomiasis ) have been shown to have high diagnostic value [12] . For mosquitoes , Ab responses to whole saliva have been correlated to human exposure to Culex mosquitoes [13] , and Anopheles gambiae [14] , Anopheles dirus [15] and Anopheles darlingi [16] , vectors of Plasmodium . Recently , it has been shown that the IgG response to whole An . gambiae saliva could be a useful biomarker for evaluating the efficacy of malaria vector control [17] . Studies on Ab responses to Aedes saliva have tended to focus on human allergic reactions [18] and the identification of the immunogenic proteins [19] although they have shown that quantitative evaluation of anti-saliva Ab responses ( IgG and specific isotypes ) could give a measure of human exposure to biting Aedes [20] , [21] . It was recently demonstrated that IgM and IgG responses to Ae . aegypti saliva could be used to estimate exposure in transiently exposed populations [22] . Finally , recent data showed that IgE and IgG4 responses to Ae . aegypti saliva could be detected in young Senegalese children during the exposure season [23] . The present study addresses one important application of this salivary biomarker as a tool to evaluate the specific exposure of individuals to Ae . albopictus bites . Human IgG responses to Ae . albopictus saliva ( salivary gland extracts; SGE ) were measured in adults living on Reunion Island . In this area , Ae . albopictus represents the only Aedes species which is known to bite humans and is the unique vector of chikungunya . Ae . aegypti , which is non anthropophilic in Reunion Island is totally absent from the study area [24] . To check the specificity of this biomarker for Ae . albopictus , cross-reactivity was tested by comparing IgG Ab levels i ) to Ae . aegypti SGE in individuals from Reunion Island and ii ) in sera from Bolivian subjects who had only ever been exposed to Ae . aegypti species .
All studies followed ethical principles as stipulated in the Edinburgh revision of the Helsinki Declaration . The studies in La Reunion and the North of France were approved by a French Ethics Committee ( the Sud Ouest , Outre Mer Ethics Committee , 25/02/2009 ) and authorized by the French Drug Agency ( AFFSAPS , Ministry of Health; 12/01/2009 ) . The study in Bolivia was approved by the Bolivian Committee of Bioethics ( September 2006 ) and the Institut de Recherche pour le Dévelopement ( IRD ) “Comité Consultatif de Déontologie et d'Ethique” ( July 2006 ) . Written informed consent was obtained from every subject . The study populations were from two different areas , namely Reunion Island and Bolivia , for specific exposure to Ae . albopictus or Ae . aegypti , respectively . In the south of Reunion Island ( Le Tampon ) , Ae . albopictus is abundant and is found up to 1200 meters in winter . Chikungunya transmission was high during the 2006 epidemic [25] . Blood samples were collected in May–June 2009 during the seasonal peak of Ae . albopictus exposure , from adults of between 18 and 30 years of age ( n = 110 ) . Subjects exposed only to Ae . aegypti were randomly selected from a large study conducted in the city of Santa Cruz de la Sierra , Bolivia ( n = 104 ) and pair-matched for age with the Reunion Island subjects . Sera from unexposed individuals ( n = 18 ) in a region free of either Ae . albopictus or Ae . aegypti ( North of France ) were used as a negative control . SGE were obtained from 10 day-old uninfected females reared in insectaries . Ae . albopictus was bred from larvae collected in the field in Reunion Island ( Direction Regionale des Affaires Sanitaires et Sociales , Saint Denis , Reunion Island ) and the Bora-Bora strain of Ae . aegypti was used ( IRD , Montpellier , France ) . Briefly , two days after a blood meal , the mosquitoes were sedated with CO2 and then their salivary glands were dissected out and transferred into a tube containing 30 µl of phosphate buffered saline ( PBS ) . The dissected glands were then pooled in 30 or 60 pairs per batch and frozen at −80°C before extraction . A simple technique consisting of 3 successive freeze-thaw cycles in liquid nitrogen was used to disrupt the membranes . The soluble SGE fraction was then separated by centrifugation for 20 minutes at 30 , 000 g at +4°C . The concentration of protein was evaluated by the Bradford method ( OZ Biosciences ) after pooling of the different batches to generate a homogenous SGE for immunological assessment . SGEs were then stored at −80°C before use . An enzyme-linked immunosorbent assay ( ELISA ) was carried out on Maxisorp plates ( Nunc , Roskilde , Denmark ) coated with Ae . albopictus or Ae . aegypti SGE , ( 0 . 8 µg/ml PBS ) at 37°C for 150 min . Plates were blocked using 250 µl of protein free Blocking-Buffer ( Pierce , Thermo Fisher , France ) for 60 minutes at room temperature . Individual sera were incubated in duplicate at a 1/100 dilution in PBS-Tween 1% , 4°C overnight . Monoclonal mouse biotinylated Ab against human IgG ( BD Pharmingen , San Diego , CA ) was incubated at a 1/1000 dilution for 90 minutes at 37°C . Peroxidase-conjugated streptavidin ( GE healthcare , Orsay , France ) was added at 1/1000 for 60 minutes at 37°C . Colorimetric development was carried out using ABTS ( 2 , 2′-azino-bis ( 3-ethylbenzthiazoline 6-sulfonic acid ) diammonium , Pierce ) in 50 mM citrate buffer ( pH 4 ) containing 0 . 003% H2O2 , and absorbance was measured at 405 nm . Each test sample was assessed in duplicate wells and in a blank well containing no antigen ( ODn ) to measure non-specific reactions , as previously described [17] , [23] , [26] . Individual results were expressed as the ΔOD value calculated using the equation ΔOD = ODx-ODn , where ODx represents the mean of the OD readings in the two antigen wells . A subject was considered as an “immune responder” if the ΔOD result was higher than the mean ΔOD+ ( 3 SD ) for unexposed individuals ( negative control ) . The threshold of positivity was 0 . 271 for IgG against Ae . albopictus and 0 . 161 for IgG against Ae . aegypti . Graph Pad Prism Software ( San Diego , CA USA ) was used to analyse the data . After confirmation of non-normal distribution , a non-parametric Mann-Whitney test was used to compare Ab levels between two independent groups , and a non-parametric Kruskal-Wallis test was used for comparisons between more than two groups . A Spearman test was used to assess the correlation between IgG levels against Ae . albopictus and Ae . aegypti SGEs . All differences were considered significant at p<0 . 05 .
IgG responses to Ae . albopictus SGE were evaluated in individuals from Reunion Island and North of France ( Figure 1 ) . In the unexposed group , one individual IgG response was slightly above the cut-off value ( ΔOD = 0 . 297 ) ( Figure 1 ) . In contrast , a high percentage ( 88% ) of the exposed group from La Reunion responded positively to the anti-SGE IgG Ab . Although considerable differences in specific Ab level were observed between exposed individuals ( ΔOD from 0 . 034 to 3 . 308 ) , a significant difference in specific IgG level was observed between the exposed group ( median = 1 . 067 ) and the unexposed group ( median = 0 . 015 ) ( p<0 . 0001 , Mann-Whitney test ) . Cross-reactivity between Ae . albopictus and Ae . aegypti SGEs was evaluated by two complementary approaches . First , the specific IgG response to both SGEs ( Figure 2 ) was evaluated in individuals only exposed to Ae . albopictus ( from Reunion Island ) ; in parallel , IgG responses to both SGEs were assessed in individuals only exposed to Ae . aegypti ( from Bolivia ) . In the Bolivian group , 16% showed a positive IgG response against Ae . albopictus SGE with only one strong response ( ΔOD>1 ) . The median ( 0 . 107 ) level of IgG against Ae . albopictus SGE was significantly lower in the Bolivians than in the Reunion Island group ( 1 . 067 ) ( P<0 . 0001 , Mann-Whitney test ) . The IgG response to Ae . aegypti SGE was also evaluated in both groups of subjects . As expected , the Bolivian group ( exposed only to Ae . aegypti ) presented high levels of IgG against Ae . aegypti SGE with 76% of immune responders . In contrast , only 19% of the subjects from Reunion Island were responders to Ae . aegypti SGE and the median ( 0 . 068 ) IgG level was very low compared with the Bolivian group ( 0 . 991 ) ( p<0 . 0001 , Mann Whitney test ) . Only one individual from Reunion presented very high level of IgG to Ae . aegytpi SGE ( ΔOD>3 ) . In addition , in 58% of double immune responders from Reunion Island , the level of IgG against Ae . albopictus SGE was above the 75% percentile value ( ΔOD = 2 . 426; data not shown ) . In the Bolivian double immune responders , the corresponding figure for Ae . aegypti SGE was 50% ( ΔOD value of 75% percentile = 2 . 341 ) . These results indicate that IgG to Ae . albopictus and Ae . aegypti SGE are cross reactive , particularly in individuals presenting a very high level of IgG . Secondly , the level of specific IgG Ab against both SGEs was compared by a statistical correlation analysis ( Figure 3 ) . High positive correlation between IgG against Ae . albopictus SGE and Ae . aegypti SGE was observed for both the Reunion Island group ( r = +0 . 445; P<0 . 0001 , Spearman test ) and the Bolivian group ( r = +0 . 617; P<0 . 0001 , Spearman test ) . For each population , IgG cross-reactivity was low with few individuals responding to both Ae . albopictus and Ae . aegypti SGEs . For the Reunion Island group , only 5 individuals showed a strong IgG response to Ae . aegypti SGE . These correlations indicate that cross-reactivity between the two Aedes species may depend on IgG level . In the Bolivian group , the same trend is observed with only 8 individuals showing a strong IgG response to Ae . albopictus SGE .
In this study , we investigated IgG responses to Ae . albopictus SGE in exposed adults from Reunion Island where Ae . albopictus—the only anthopophilic Aedes species—transmits chikungunya . First , specific IgG responses were high in the exposed group and significantly different to those observed in an unexposed population from Europe: 88% of exposed individuals developed IgG against Ae . albopictus SGE . In addition , specific IgG Ab levels showed considerable inter-individual variations . Since the intensity of exposure in a given population living in the same area can obviously vary between individuals , these results suggest that the anti-SGE IgG response may be a reliable biomarker for exposure to Ae . albopictus bites . Furthermore , the significant difference in Ab levels between unexposed and exposed individuals shows that this biomarker could distinguish individuals exposed to Ae . albopictus bites . A useful biomarker for Ae . albopictus bites needs to be highly specific and devoid of immune cross-reactivity with other Aedes species . We evaluated the cross-reactivity between two species using complementary approaches , i . e . in individuals only ever exposed to Ae . aegypti and by analysing IgG levels against both SGEs . In the Bolivian group only exposed to Ae . aegypti , 16% of individuals responded to Ae . albopictus SGE ( heterologous ELISA ) . The ΔOD values for these “cross-reactive” individuals are characterised by very low IgG levels whereas a high percentage ( 88% ) and high IgG levels ( homologous ELISA ) were observed in subjects from Reunion Island . In addition , IgG responses against Ae . aegypti SGE are significantly different: 76% of immune responders in Bolivia compared with 19% in Reunion Island . Interestingly , we observed that IgG cross-reactivity was mainly detected in high immune responders . In Reunion Island , in 58% of double immune responders , the level of IgG against Ae . albopictus SGE was above the third quartile . In parallel , in Bolivia , the level of IgG against Ae . aegypti SGE of 50% of double immune responders was above the third quartile . Taken together , these results suggest that there is cross-reactivity between Ae . albopictus SGE and Ae . aegypti SGE , especially in high immune responders . Further investigations would be required to identify species-specific salivary antigens . IgG response to Ae . albopictus SGE has been detected in individuals exposed to the bites of this mosquito [27] . It can be hypothesised that , in Reunion Island , the observed specific IgG responses were elicited as a result of antigenic stimulation following biting by Ae . albopictus . In the urban area of Reunion Island , Ae . albopictus is highly antropophilic [28] and characterised by numerous “artificial” breeding sites [25] which could explain the high percentage ( 88% ) of specific responders to Ae . albopictus SGE . These results point up the relevance of this approach to developing a specific biomarker for exposure to Ae . albopictus . However epidemiological factors—history of exposure , genetic background , immune tolerance , etc . —have to be taken into account when explaining variations in responsiveness . Further longitudinal studies could focus on this . To our knowledge , measuring IgGs against Ae . albopictus SGE represents the first direct method for evaluating human exposure to Ae . albopictus and this parameter probably represents the first genuine biomarker for man-vector contact . This method could help overcome the shortcomings of the current methods which only give indirect measurements of exposure to Ae . albopictus and therefore have considerable limitations for evaluating the risk of arbovirus transmission [7] . The current standard methods—immature stage counting and trapping techniques—are both “static” and mainly target “household exposure” , ignoring all the anthropogenic factors that can affect exposure ( e . g . water storage practices ) . Ae . albopictus and Ae . aegypti are diurnal mosquitoes , biting both indoors and outdoors , and these characteristics may complicate the assessment of exposure using conventional methods . Using anti-SGE IgG responses to evaluate exposure to Ae . albopictus , highly heterogeneous Ab levels were observed between exposed individuals , as previously reported for another vector [26] . It could be hypothesized that different levels could reflect the intensity of exposure to biting vectors , e . g . the experimental results indicate that a high Ab response is the result of high exposure and the ame association is also observed for low Ab levels [29] . This has also been observed in human populations in the field where arthropods vectors are endemic . In exposed individuals from endemic areas , it has been shown that the level of anti-saliva Ab was closely associated with the intensity of exposure to vector bites [12] , [23] , [26] , [30] . Therefore , this could be a useful tool for comparing the exposure to Ae . albopictus at different sites in a given study area or between different areas , and could be useful for evaluating the efficacy of vector control . In addition , recent findings in the malaria field have shown that Ab responses to saliva antigens are useful in the assessment of low-level exposure to Anopheles bites [31] . Detection of low level exposure in newly colonized areas is of particular interest for Ae . albopictus due to its ongoing worldwide spread , especially in urban contexts . Moreover , a clear correlation between larval indices and pathogen transmission is difficult to establish when the level of exposure is low [32] , [33] . In both cases , evaluation of the anti-saliva IgG response could complement entomological methods . However , several validation steps ( e . g . seasonal variation and correlation with entomological measurements ) will have to be checked . In this study , we measured the Ab response to whole SGE . As long as any salivary proteins are shared with other species or genera , the degree of cross-reactivity with major other Aedes vectors will have to be assessed . Thus , cross-reactivity was investigated between Ae . albopictus and Ae . aegypti , closely related species with shared salivary proteins [34] , [35] . Only weak cross-reactivity was detected between Ae . albopictus and Ae . aegypti SGEs , mainly observed in high immune responders . This may suggest that species-specific proteins are more immunogenic than genus-shared proteins . Species-specificity has been already reported with several Aedes species [20] , [23] , [36] and for a broad range of vectors [12] , [29] , [37] . In contrast , western-blot analysis reveals extensive cross-reactivity and shows that some antigens are common to all Aedes species [21] , [38] , [39] . This low level of cross-reactivity also raises the roles of intensity and history of exposure in determining the acquired IgG response against SGE . Individuals from Reunion Island are unlikely to have been exposed to Ae . aegypti because this mosquito is not found in town and its breeding sites are restricted to natural habitats [24] . Cross-reactivity between salivary proteins common to all members of the Aedes genus seems therefore to be the most likely explanation of the observed IgG responsiveness to Ae . aegypti SGE in Reunion Island . Travelling could also lead to contact with Ae . aegypti which is present in most of the islands of the Indian Ocean . To enhance the usefulness of this biomarker for large-scale applications and to exclude cross-reactivity , an Ae . albopictus-specific salivary antigen needs to be identified . In malaria , only one peptide in whole Anopheles salivary antigen is an efficient biomarker for exposure to Anopheles bites [30] . To improve the sensitivity and the specificity of detection , an immuno-proteomic study is currently underway to identify Ae . albopictus-specific proteins and peptides . The study described here represents the first step for estimating human exposure to Ae . albopictus by quantifying the IgG response to vector salivary antigens . In an area of chikungunya transmission , it was shown that the level of Ab against Ae . albopictus SGE can be used to identify individuals who have been exposed to the bites of this important vector . Low level cross-reactivity was observed with Ae . aegypti SGE suggesting that it will be possible to develop a specific biomarker for human exposure to biting Ae . albopictus . By combining the use of such a biomarker with classical entomological and epidemiological methods , it could enhance the assessment of human exposure to Ae . albopictus and therefore contribute to both accurate prediction of the risk of arbovirus transmission and evaluation of the efficacy of vector control .
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Aedes-borne viruses like dengue and chikungunya are a major problem in Reunion Island . Assessing exposure to Aedes bites is crucial to estimating the risk of pathogen transmission . Currently , the exposure of populations to Aedes albopictus bites is mainly evaluated by entomological methods which are indirect and difficult to apply on a large scale . Recent findings suggest that evaluation of human antibody responses against arthropod salivary proteins could be useful in assessing exposure to mosquito bites . The results indicate that 88% of the studied population produce IgG to Ae . albopictus saliva antigens in Reunion Island and show that this biomarker can detect different levels of individual exposure . In addition , little cross-reactivity is observed with Aedes aegypti saliva , suggesting that this could be a specific marker for exposure to Aedes albopictus bites . Taken together , these results suggest that antibody responses to saliva could constitute a powerful immuno-epidemiological tool for evaluating exposure to Aedes albopictus and therefore the risk of arbovirus infection .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"immunology",
"biology",
"immunologic",
"techniques",
"viral",
"diseases",
"vectors",
"and",
"hosts"
] |
2012
|
Evaluation of the Human IgG Antibody Response to Aedes albopictus Saliva as a New Specific Biomarker of Exposure to Vector Bites
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Although nucleotide-binding domain , leucine-rich repeat ( NLR ) proteins are the major immune receptors in plants , the mechanism that controls their activation and immune signaling remains elusive . Here , we report that the avirulence effector AvrPiz-t from Magnaporthe oryzae targets the rice E3 ligase APIP10 for degradation , but that APIP10 , in return , ubiquitinates AvrPiz-t and thereby causes its degradation . Silencing of APIP10 in the non-Piz-t background compromises the basal defense against M . oryzae . Conversely , silencing of APIP10 in the Piz-t background causes cell death , significant accumulation of Piz-t , and enhanced resistance to M . oryzae , suggesting that APIP10 is a negative regulator of Piz-t . We show that APIP10 promotes degradation of Piz-t via the 26S proteasome system . Furthermore , we demonstrate that AvrPiz-t stabilizes Piz-t during M . oryzae infection . Together , our results show that APIP10 is a novel E3 ligase that functionally connects the fungal effector AvrPiz-t to its NLR receptor Piz-t in rice .
Unlike animal responses to pathogen infection , plant responses to pathogen infection do not include a circulatory system or specialized cells [1] . Instead , individual plant cells launch defense responses against invading pathogens . Extensive molecular studies over the last two decades have revealed two layers of host immunity in plants . Plant immunity can be activated when highly conserved pathogen-associated molecular patterns ( PAMPs ) are recognized by plasma membrane-bound pattern recognition receptors ( PRRs ) in a process called PAMP-triggered immunity ( PTI ) . PTI is considered the first layer of plant immunity [2 , 3] . For the second layer , immunity can be activated when pathogen-delivered avirulence ( Avr ) effectors are recognized by the product of plant resistance ( R ) genes in a process called effector-triggered immunity ( ETI ) . ETI can be achieved by the direct or indirect interaction between the Avr effectors and R proteins in the plant cell [1 , 4] . Upon recognition , both immunity layers are capable of initiating a signaling cascade that can result in multiple defense responses . The nucleotide-binding domain , leucine-rich repeat ( NLR ) proteins play a major role as intracellular immune receptor R proteins in plant immunity[5] . Most R genes cloned to date encode NLR proteins that mediate recognition of diverse effectors from all classes of plant pathogens . Both direct and indirect interactions between NLRs and effectors occur in different pathosystems [6] . In the indirect interactions , additional plant proteins are the targets of effectors and may be either genuine virulence targets of the effectors [7] or decoy proteins that plants have evolved to mimic bona fide effector targets [8] . A hybrid model of the direct and indirect interactions was proposed in which the target protein serves as ‘bait’ that the effector associates with before direct interaction with the NLR receptor and before immune signaling is activated [9 , 10] . Because NLR activation and signaling usually results in strong defense responses and a hypersensitive reaction ( HR ) , such activation and signaling must be tightly regulated to avoid adverse effects on plant growth and development when plants are not under pathogen attack [11–13] . Some factors controlling NLR activation and signaling have been identified [10] . For example , analysis of crystal structure and in vitro interactions revealed that the two CHORD domains of a single RAR1 molecule bridge the N-termini of the HSP90 monomers , thus regulating the ‘open’ and ‘closed’ state of the HSP90 dimer that coordinates NLR stabilization [14] . Two independent studies showed that the tetratricopeptide repeat-containing protein SRFR1 is a negative regulator of the accumulation and activation of the NLR receptor SNC1 [15 , 16] . Ubiquitin-mediated degradation of proteins via the 26S proteasome is important for the regulation of protein levels in living cells [17] . The E3 ligases in the ubiquitination process interact and bring substrates to be ubiquitinated in proximity to the conjugating enzyme E2 . Involvement of ubiquitination in NLR-mediated immunity has been recently reported in plants ( see review by [18] ) . For example , the SCF E3 ubiquitin ligase complex involving the F-box protein CPR30/CPR1 ( SCFCPR1 ) targets the NLR protein SNC1 and RPS2 for degradation [11 , 12] . Furthermore , when plants overexpressing CPR1 were treated with the 26S proteasomal inhibitor MG132 , levels of SNC1 increased . This observation suggested that SNC1 levels are modulated by SCFCPR1 via the 26S proteasome-mediated degradation pathway . However , it is unknown whether these E3 ligase complexes are the host targets of pathogen effectors . Magnaporthe oryzae is the causal agent of rice blast , a severe disease that limits rice production worldwide . We cloned the R gene Piz-t from rice and its cognate avirulence gene AvrPiz-t from M . oryzae [4 , 19] . Piz-t encodes an NLR protein , but AvrPiz-t does not show homology to any genes in the databases . Our previous study showed that AvrPiz-t is secreted into the rice cell and interacts with the rice E3 ligase APIP6 [20] . Analysis of APIP6 RNAi transgenic plants showed that APIP6 is a positive regulator of PTI . AvrPiz-t and APIP6 can degrade each other in planta . APIP10 is another E3 ligase that was identified in the yeast-two hybrid screen when AvrPiz-t was used as the bait in our previous study [20] . To determine the role of APIP10 in rice immunity in the current study , we analyzed the relationships among APIP10 , AvrPiz-t , and Piz-t . We report that APIP10 contributes to rice immunity by functioning in both PTI and ETI . While APIP10 is the target of AvrPiz-t’s virulence activity for suppression of PTI , APIP10 is also a negative regulator of the accumulation and activation of the NLR receptor Piz-t . Degradation of APIP10 by AvrPiz-t results in the release of APIP10 suppression of Piz-t accumulation and the initiation of a strong defense response . Our study identifies a novel E3 ligase , APIP10 , that functionally connects a fungal effector with its NLR receptor in plants .
We previously reported that AvrPiz-t interacts with three putative C3HC4-type E3 ligases in yeast-two hybrid ( Y2H ) screens [20] . Among the AvrPiz-t interacting proteins ( APIPs ) , APIP10 showed a strong interaction and was selected for further studies . We confirmed the interaction between AvrPiz-t and APIP10 in yeast using four selection markers ( S1A Fig ) . To further validate the interaction in yeast , we performed in vivo Co-IP ( co-immunoprecipitation ) experiments by co-expressing GFP:AvrPiz-t:HA and Myc:APIP10 in Nicotiana benthamiana using the agroinfiltration method . Because the AvrPiz-t signal peptide is cleaved in the mature protein , we used the AvrPiz-t gene without its N-terminal signal peptide sequence to make constructs in the following experiments unless indicated otherwise . When the GFP:AvrPiz-t:HA fusion protein was immunoprecipitated ( IP ) from the plant extract using anti-HA IgG beads , the Myc:APIP10 proteins were detected in the immunocomplex of GFP:AvrPiz-t:HA with the anti-Myc antibody ( S1B Fig , middle lane of the upper-right panel ) . As a control , no visible background signal was detected in the samples expressing only GFP:AvrPiz-t:HA ( S1B Fig , the third lane of the upper-right panel ) or Myc:APIP10 ( S1B Fig , the first lane of the upper-right panel ) . These results indicate that AvrPiz-t interacts with APIP10 in vivo . Since AvrPiz-t interacts with three putative C3HC4-type E3 ligases in the Y2H screens as previously reported [20] , we decided to confirm whether that the interaction between AvrPiz-t and APIP10 is specific by including an unrelated E3 ligase , SPL11 [21] , as an additional negative control in the Co-IP experiment . To facilitate the detection of SPL11 in planta as reported previously [22] , mSPL11 , which has three mutations in the U-box domain , was used in the experiment . Similar with the assay in S1B Fig , GFP:AvrPiz-t:HA , Myc:APIP10 and Myc:mSPL11 were co-expressed in N . benthamiana . When the GFP:AvrPiz-t:HA fusion protein was immunoprecipitated from the plant extract using the anti-HA IgG beads , the Myc:APIP10 proteins were also detected in the immunocomplex of GFP:AvrPiz-t:HA with the anti-Myc antibody ( S1C Fig , first lane of the top-right panel ) . However , no visible signal was detected in the sample expressing only GFP:AvrPiz-t:HA ( S1C Fig , third lane of the top-right panel ) or co-expressing GFP:AvrPiz-t:HA and Myc:mSPL11 ( S1C Fig , second lane of the top-right panel ) . These results indicate that the interaction in planta between AvrPiz-t and APIP10 is specific . APIP10 identified from the Y2H library consists of a 1 , 416-bp open reading frame and encodes a protein with 472 amino acids . BLAST searches showed that APIP10 is a single-copy gene in the rice genome and that the predicted protein belongs to a large family of conserved and ubiquitous RING finger proteins in eukaryotes . APIP10 has multiple , predicted conserved domains such as a BRAP2 ( BRCA1-Associated Protein 2 ) , a C3HC4-type RING finger , a ZnF UBP ( Zinc-Finger Ubiquitin Binding Protein ) , and a coiled-coil domain ( S2A Fig ) . To determine whether APIP10 has E3 ligase activity like other BRAP2-RING Finger-ZnF UBP proteins , we performed an in vitro ubiquitination assay with a series of negative controls . In the E3 ligase activity assay , the MBP:APIP10 fusion protein purified from E . coli was incubated with wheat ( Triticum aestivum ) E1 , Arabidopsis E2 ( AtUBC10 ) , 5X Myc:ubiquitin ( Myc:Ub ) , and ATP . To verify whether the E3 ligase activity of APIP10 depends on its RING finger domain , we included the mutant dRING ( APIP10 dRING ) in which the RING finger at the amino acid position from 158 to 204 was completely deleted . In the preliminary experiment , no polyubiquitin product was visible when Ub was used . Therefore , Ub fused with 5X Myc was used in the reaction , and the immunoblot with anti-Myc antibody was performed to enhance the detection of the polyubiquitin . A band of polyubiquitin product with high molecular weight was detected in the reaction with the complete APIP10 ( S2B Fig , lane 6 , arrow indicated ) but not in the reaction with APIP10 dRING ( S2B Fig , lane 5 in the top panel ) , suggesting that the RING finger domain is required for the E3 ligase activity of APIP10 . To further confirm this result , we performed an E3 ligase assay with time and E2 enzyme quantity as variables and with APIP10 dRING as negative a control . The immunoblot analysis with anti-Myc antibody showed that a signal of the high molecular weight protein band ( about 170 kD ) became stronger as the time was increased ( the protein band is indicated by an arrow in S3A Fig in the top panel ) . Similarly , the signal of the high molecular weight protein band was stronger when more E2 enzyme was added to the reaction ( as indicated by an arrow in S3B Fig in the top panel ) . To assess whether AvrPiz-t has any biochemical functions in the APIP10-mediated ubiquitination , we included the purified GST:AvrPiz-t:HA protein in the in vitro E3 ligase assay of APIP10 . Surprisingly , a band above the GST:AvrPiz-t:HA protein was detected by the immunoblot analysis with the anti-HA antibody in the presence of the GST:AvrPiz-t:HA recombinant protein ( Fig 1A , lane 6 , arrow ) . In contrast , no such signal was detected in the presence of the GST:AvrPi-ta:HA protein , an unrelated effector protein from M . oryzae [23] ( Fig 1A , lane 7 ) . The difference in size between the two bands is about the size of a 5X Myc:ubiquitin ( about 16 KDa ) , indicating that the GST:AvrPiz-t:HA is ubiquitinated by APIP10 in vitro . To confirm the ubiquitination result , we repeated the E3 ligase assay for the reactions in lane 6–8 in Fig 1A . Then we conducted a GST pulldown analysis by washing the GST:AvrPiz-t:HA and GST:AvrPi-ta:HA beads with the PBST solution ( Phosphate Buffered Saline with 0 . 5% Triton X-100 ) after the E3 ligase reaction . Immunoblot analysis with the anti-HA antibody showed the ubiquitinated bands above the GST:AvrPiz-t:HA fusion protein ( S4 Fig , first lane in the upper panel ) . Immunoblot analysis with the anti-ubiquitin antibody showed a smear of high molecular bands above GST:AvrPiz-t:HA only in the reaction with both the wild type MBP:APIP10 and GST:AvrPiz-t:HA ( S4 Fig , first lane in lower panel ) , but not with both MBP:APIP10 and GST:AvrPi-ta:HA ( S4 Fig , second lane in the lower panel ) or with both MBP:APIP10 dRING and GST:AvrPiz-t:HA ( S4 Fig , third lane in the lower panel ) . These results demonstrated that AvrPiz-t is specifically ubiquitinated by APIP10 in vitro . Furthermore , the immunoblot analysis that used the anti-Myc antibody to detect polyubiquitin showed that the E3 ligase activity of APIP10 was reduced when the GST:AvrPiz-t:HA fusion protein was included in the reaction ( Fig 1B , lane 6 , arrow ) , suggesting that AvrPiz-t interferes with APIP10 E3 ligase activity . The GST:AvrPi-ta:HA protein , which did not affect the E3 ligase activity of APIP6 [20] , was used as a negative control ( Fig 1B , lane 7 ) . These results show that AvrPiz-t interferes with APIP10 E3 ligase activity and that APIP10 ubiquitinates AvrPiz-t in vitro . Because AvrPiz-t is ubiquitinated by APIP10 in vitro ( Fig 1A ) , we hypothesized that AvrPiz-t may be a substrate of APIP10 in planta . To test this , we co-expressed GFP:AvrPiz-t:HA with Myc:APIP10 in N . benthamiana leaves . The immunoblot analysis revealed that the GFP:AvrPiz-t:HA protein level was significantly lower in the tissue when Myc:APIP10 was co-expressed than when Myc:APIP10 dRING was co-expressed ( Fig 2A , compare lane 1 and 3 in the top panel ) . This result suggests that APIP10 promotes the degradation of AvrPiz-t in plant cells . Pre-treatment of the leaves with MG132 inhibited the degradation of GFP:AvrPiz-t:HA ( Fig 2A , lane 2 in the first panel ) , suggesting that APIP10 degrades AvrPiz-t via the 26S proteasome system . To test whether the mutated APIP10 dRING affects the stability of its associated protein AvrPiz-t , we used Myc:GFP as a negative control and repeated the co-infiltration assay . The western blot analysis revealed that GFP:AvrPiz-t:HA was significantly lower in the tissue where APIP10 was co-expressed ( S5 Fig , first lane in the top panel ) compared to the control where Myc:GFP was co-expressed ( S5 Fig , third lane in the top panel ) . This result confirmed that that APIP10 promotes the degradation of AvrPiz-t in plant cells . Because AvrPiz-t promotes the degradation of APIP6 when they are co-expressed in N . benthamiana [20] , we reasoned that AvrPiz-t might also affect the accumulation of APIP10 in plant cells . The immunoblot analysis showed that APIP10 was reduced by 30–40% ( relative to the controls ) when GFP:AvrPiz-t:HA and Myc:APIP10 were co-expressed ( Fig 2B , lane 3 in the upper panel ) . Furthermore , the degradation was inhibited by MG132 ( Fig 2B , lane 4 in the upper panel ) , suggesting that AvrPiz-t promotes the degradation of APIP10 in planta , likely through the 26S proteasome system . To obtain more evidence that the degradation of APIP10 is dependent of AvrPiz-t , AvrPii , an unrelated effector protein [24] , was used as a negative control in the co-infiltration . The immunoblot analysis showed that the accumulation of Myc:APIP10 was significantly decreased by the co-expression with GFP:AvrPiz-t:HA ( . S6 Fig , first lane in the top panel ) compared to the negative control , co-expression of Myc:APIP10 with GFP:AvrPii:HA ( S6 Fig , third lane in the top panel ) . This provides additional evidence that the degradation of APIP10 in planta is dependent on AvrPiz-t . As described above , AvrPiz-t interferes with the E3 ligase activity of APIP10 in vitro ( Fig 1B ) and promotes the degradation of APIP10 in vivo ( Fig 2B ) . Based on these results and our previous report on APIP6 [20] , we speculated that APIP10 might be another target of AvrPiz-t-mediated suppression of host defense . To determine the role of APIP10 in PTI against M . oryzae , we designed an RNAi construct targeting 215 bp of APIP10 3’UTR using the pCXUN vector [25] and generated over 20 stable transgenic lines in NPB ( without Piz-t ) . Three homozygous lines with a single T-DNA insertion were selected from the T3 generation for the subsequent analysis and transcription levels of each line were determined by qRT-PCR ( S7 Fig , top panel ) . To determine the function of APIP10 in rice PTI , we used a luminol-based chemi-luminescence assay to monitor ROS generation induced by flg22 and chitin treatments in 4-week-old homozygous APIP10 RNAi plants [26] . The analysis showed that APIP10 knockdown significantly suppressed flg22-induced ROS accumulation ( Fig 3A ) but only partially suppressed chitin-induced ROS accumulation in the rice tissue ( Fig 3B ) . At 3 h after treatment with flg22 and chitin , qRT-PCR also revealed that the transcriptional profiles of PTI-related defense genes such as KS4 and PAL differed between APIP10 RNAi plants and non-silenced plants ( Fig 3C ) . KS4 encodes one of the two diterpene cyclase enzymes involved in momilactone biosynthesis [27 , 28] , and the APIP10 RNAi plants showed significant suppression of KS4 transcripts 3 h after treatment with flg22 ( Fig 3C , left ) . Phenylalanine ammonia lyase ( PAL ) catalyzes the deamination of L-phenylalanine to trans-cinnamic acid and is involved in the biosynthesis of certain classes of low molecular weight antimicrobial compounds called phytoalexins [29 , 30] . In rice , the transcription of PAL is induced by flagellin from bacteria as well as by chitin [31–33] . In APIP10 RNAi lines , significant suppression of PAL transcripts was observed at 3 h after treatment with either flg22 or chitin ( Fig 3C , right ) . Suppression of PAL transcripts without PAMP treatment was also observed ( Fig 3C , water ) , indicating that APIP10 might be involved in PAMP-independent regulation of PAL . Taken together , these results suggest that host immunity triggered by PAMPs is compromised in APIP10 RNAi plants . Next , we used the punch inoculation method to measure the resistance of APIP10 RNAi plants to the virulent M . oryzae isolate RB22 . Lesions were larger on the APIP10 RNAi plants than on the control plants ( Fig 3D ) . The relative fungal mass of M . oryzae , measured by the DNA-based qPCR assay , was also greater in the APIP10 RNAi plants than in the control plants ( Fig 3E , left panel ) . In addition , more spores were produced on the APIP10 RNAi plants than on the control plants ( Fig 3E , right panel ) . These results suggest that silencing of the APIP10 gene in rice compromises the basal defense against M . oryzae . Because the phenotypes of APIP10 RNAi lines are similar to those of APIP6 RNAi lines , we conducted qRT-PCR of APIP6 in the APIP10 RNAi lines ( . S8A Fig , top panel ) and APIP10 in the APIP6 lines ( S8B Fig , lower panel ) . The analysis showed that there is no correlation between the expression levels of the two genes when one of them is silenced . Piz-t is the cognate R gene of AvrPiz-t in rice [4] . To understand the relationship between APIP10 and Piz-t , we first transformed the Piz-t:HA construct with hygromycin as a selection marker in the NPB background in order to generate NPB Piz-t:HA rice . Then we screened T1 lines for hygromycin resistance and chose the lines showing a 3:1 segregation ratio . After the T2 plants were inoculated with the avirulent isolate RO1-1 , the presence of the Piz-t:HA fusion protein was confirmed by immunoblot analysis with the anti-HA antibody . With this approach , we obtained five homozygous lines with a single T-DNA insertion of Piz-t:HA . Next , we developed an APIP10 RNAi construct ( same as described above ) with the G418 Sulfate antibiotic selection and transformed the construct into the calli of selected NPB Piz-t:HA line . The APIP10 transcription levels in selected lines were determined by qRT-PCR ( S7 Fig , lower panel ) . Surprisingly , NPB Piz-t:HA calli transformed with the APIP10 RNAi construct showed severe cell death but not with an empty vector ( Fig 4A and S9 Fig ) . To determine whether the severe cell death triggered in the calli is related to the Piz-t:HA protein , we performed immunoblot analysis for Piz-t:HA with the anti-HA antibody and qRT-PCR of the APIP10 transcripts; we did this with four independently transformed callus lines that showed different levels of cell death . qRT-PCR indicated that the transcript level of APIP10 was lower in lines with severe cell death than in the line without cell death ( S10 Fig , the upper panel ) , indicating that the cell death observed in the transgenic plants was caused by the silencing of APIP10 . Strikingly , the lines with lower APIP10 transcripts in the NPB Piz-t:HA background showed a higher expression level of the Piz-t-HA protein ( Fig 4B , the upper panel ) , suggesting that the APIP10 transcript level is negatively correlated with Piz-t accumulation and cell death . To determine whether the accumulation of the Piz-t protein is due to its increased transcription , we used qRT-PCR to quantify Piz-t transcripts . The analysis revealed that the number of Piz-t transcripts in the APIP10 RNAi callus lines was inversely related to Piz-t protein accumulation ( . S10 Fig , the lower panel ) , indicating that the accumulation of the Piz-t protein is not the result of its increased transcription . After two rounds of rice transformation , we were able to obtain only six T1 lines that had reduced cell death because most APIP10 RNAi lines died within 2–3 weeks after transfer to soil ( Fig 4C , right panel ) . To confirm the results obtained from callus lines , we compared the T2 plants of the APIP10 RNAi lines in the NPB Piz-t:HA background with the wild-type NPB Piz-t:HA plants . All of the lines in the NPB Piz-t:HA background showed cell death and dwarf phenotypes ( S11A Fig ) . Immunoblot analysis of total protein obtained from the leaf tissue of two lines ( #14–4 and 38–6 ) revealed that they contained 1 . 5- to 2 . 2-times more Piz-t:HA than the controls ( Fig 4D ) . qRT-PCR analysis using the same leaf tissue showed that Piz-t transcripts were less abundant in the APIP10 RNAi lines 14–4 and 38–6 than in the control plants ( S11B Fig ) , indicating that the Piz-t accumulation is not due to an increase in its transcription level . To determine whether PTI responses of APIP10 RNAi lines in NPB Piz-t:HA were compromised as we had observed in the APIP10 RNAi lines in NPB , we monitored the ROS generation triggered by chitin and flg22 in the leaf disks of 4-week-old plants . The analysis showed that silencing of APIP10 in the presence of Piz-t almost completely suppressed ROS induced by flg22 in the leaf tissue ( Fig 3F ) but did not suppress ROS induced by chitin significantly ( Fig 3G ) . This observation was similar to that observed in the APIP10 silencing lines in NPB ( Fig 3B ) . qRT-PCR also revealed that the RNAi lines showed significant but distinct transcriptional induction or suppression profiles of the PTI-related defense genes 3 h after treatment with chitin or flg22 ( Fig 3H ) . For example , the APIP10 RNAi lines showed suppression of KS4 transcripts at 3 h after treatment with flg22 or chitin ( Fig 3H , left ) but showed significant suppression of PAL transcripts at 3 h after treatment with flg22 but not after treatment with chitin ( Fig 3H , right ) . We next used the punch inoculation method to measure the resistance of the APIP10 RNAi lines in the NPB Piz-t:HA background to the virulent M . oryzae isolate RB22 . Surprisingly , lesions were smaller on the APIP10 RNAi plants in the Piz-t background than on the wild-type NPB-Piz-t:HA plants ( Fig 3I ) ; this was opposite to the disease phenotype observed in the APIP10 RNAi plants in the NPB background ( Fig 3D ) . Consistent with lesion size , the relative fungal biomass measured by the DNA-based qPCR was significantly lower in the APIP10 RNAi-NPB-Piz-t:HA plants than in the Piz-t:HA plants ( Fig 3J , left panel ) . Furthermore , the sporulation in the infected area was significantly lower on the APIP10 RNAi-NPB-Piz-t:HA plants than on the Piz-t:HA plants ( Fig 3J , right panel ) . Taken together , these results suggest that silencing of APIP10 in the Piz-t plants enhances resistance to the virulent isolate RB22 possibly through the accumulation of Piz-t , even though the PTI response was compromised because of the silencing of APIP10 . Because we found that silencing of APIP10 in transgenic rice leads to accumulation of the Piz-t protein ( Fig 4B and 4D ) , we speculated that APIP10 may promote the degradation of Piz-t in rice . To test this hypothesis , we co-expressed either Myc:APIP10 or Myc:APIP10 dRING ( as a negative control ) with Piz-t:HA using agroinfiltration in N . benthamiana leaves . Less Piz-t:HA protein accumulated when it was co-expressed with APIP10 than when it was co-expressed with APIP10 dRING , and the accumulation was recovered almost to the control level by treatment with MG132 ( S12 Fig , lane 1 vs . 2 and lane 3 vs . 4 in the first panel ) . To confirm these results , a semi-in vivo degradation assay was performed as described previously [34 , 35] . For this assay , total protein extracted from the M . oryzae-inoculated Piz-t:HA rice plants was mixed with total protein extracted from N . benthamiana leaves co-expressed with either APIP10 or APIP10 dRING with GFP as an internal control . The samples were collected at different times before 1X SDS loading buffer was added to stop the reaction . The level of Piz-t was decreased by APIP10 over time , and after 2 h , less Piz-t protein was detected in the presence of APIP10 ( Fig 5A , lane 5 ) than in the presence of APIP10 dRING ( Fig 5A , lane 10 ) . The decrease in the level of the Piz-t protein at 4 h was partially inhibited by treatment with MG132 ( Fig 5B , lane 2 in the first panel ) . To rule out the possibility that the deletion of the RING finger domain in APIP10 stabilizes both APIP10 dRING and Piz-t , myc:GFP was used as a negative control instead of APIP10 dRING in the semi in vivo degradation assay . The decrease in the level of the Piz-t protein was observed in the presence of Myc:APIP10 ( S13 Fig , lane 1 vs . lane 3 in the top panel ) and the degradation of Piz-t:HA was partially inhibited by the MG132 treatment ( S13 Fig , lane 1 vs . lane 2 ) . However , no obvious degradation of Piz-t in the presence of Myc:GFP was observed ( S13 Fig , lane 3 vs . lane 4 in the top panel ) . Together , these data suggest that APIP10 promotes Piz-t degradation through the 26S proteasome system . Because we found that AvrPiz-t promotes degradation of APIP10 and that silencing of APIP10 leads to accumulation of Piz-t , we reasoned that expression of AvrPiz-t in planta may lead to the accumulation of Piz-t . To determine the relationship between AvrPiz-t and Piz-t , we co-expressed either empty vector , GFP , or GFP:AvrPiz-t with Piz-t:HA in N . benthamiana and observed the accumulation of both proteins by immunoblot analysis . Intriguingly , the Piz-t protein level was ~1 . 6-fold greater when Piz-t:HA was co-expressed with GFP:AvrPiz-t:HA ( Fig 6A , top panel , lane 3 ) than with the empty vector or with GFP ( Fig 6A , top panel , lane 1 and 2 ) , suggesting that AvrPiz-t stabilizes the Piz-t protein . To determine whether the increased accumulation of Piz-t in the presence of AvrPiz-t is specific to AvrPiz-t , we included an unrelated effector protein from M . oryzae , AvrPii , as a negative control . As described above , we co-expressed the empty pGD vector , GFP:AvrPiz-t or GFP:AvrPii with Piz-t:HA in N . benthamiana and observed the accumulation of proteins by immunoblot analysis . The assay showed that the Piz-t protein level was ~2 . 7-fold greater when Piz-t:HA was co-expressed with GFP:AvrPiz-t:HA ( S14 Fig , the middle lane in the top panel ) than that with the empty vector or with GFP:AvrPii ( S14 Fig , the first and the third lanes in the top panel , respectively ) , suggesting that the stabilization of Piz-t by AvrPiz-t is specific . To confirm this result in rice plants , we transformed the construct expressing the AvrPiz-t gene under the control of the inducible XVE system into the rice calli generated from the Piz-t:HA rice seeds in order to generate iAvrPiz-t transgenic lines . Over 20 independently transformed transgenic lines were obtained . After confirming the genotype by PCR , we selected six T4 lines with the Piz-t plants as a negative control for the following analyses . Young leaves of each line were cut and transferred to N6 medium containing the β-estradiol to induce the expression of AvrPiz-t . Piz-t accumulation increased upon the induction of AvrPiz-t ( Fig 6B ) . The induction of AvrPiz-t as well as the level of Piz-t transcript was monitored by qRT-PCR after the treatment as shown in S15 Fig To confirm the above results with rice plants under physiologically relevant conditions , i . e . , when rice plants were inoculated with M . oryzae , we inoculated the Piz-t plants by the spray method with RB22 isogenic blast transformants: RB22 , RB22:AvrPiz-t , and RB22:AvrPii . Consistent with the results from N . benthamiana , Piz-t:HA accumulation was greater in the RB22:AvrPiz-t-inoculated plants than in the RB22 or RB22:AvrPii-inoculated plants at all the time points we monitored ( Fig 6C ) . The Piz-t level was still high in the RB22:AvrPiz-t-inocualted plants at 144 h after inoculation , confirming that AvrPiz-t promotes the accumulation of the Piz-t protein in planta .
In host–microbe interactions , ubiquitination plays an important role in both host defense and pathogen infection [18 , 36] . Researchers have identified both pathogen effectors that target the ubiquitination machinery for defense suppression and plant ubiquitination-related proteins that target pathogen effectors for degradation and thus for defense enhancement . Most of these findings , however , have been derived from several model plant diseases caused by bacterial pathogens . Although recent research has revealed the importance of ubiquitination in plant diseases caused by fungi or oomycetes [20 , 37] , the role of ubiquitination in these diseases is poorly understood . In particular , how microbial perturbation of host ubiquitination activates the defense response mediated by NLR receptor proteins is largely unknown . In this study , we describe the relationship among the fungal effector AvrPiz-t , the rice RING finger E3 ligase APIP10 , and the NLR receptor Piz-t . We found that AvrPiz-t can interact with and promote the degradation of APIP10 when it is secreted into rice cells by M . oryzae . Silencing of APIP10 in the Piz-t background causes severe cell death and accumulation of Piz-t . Co-infiltration assays showed that APIP10 expression leads to Piz-t degradation and that such degradation depends on the RING finger domain of APIP10 . In contrast , AvrPiz-t can stabilize Piz-t during blast infection . These results demonstrate an elegant defense mechanism in which rice cells use the E3 ligase APIP10 to regulate Piz-t for immune responses when attacked by the blast fungus carrying the AvrPiz-t gene . Degradation of the APIP10 by AvrPiz-t and the resulting elimination of the negative regulation of Piz-t protein by APIP10 leads to a rapid increase in Piz-t and a strong defense response including programmed cell death in the infected cells . Although APIP10 seems similar to RIN4 in Arabidopsis in that they both negatively regulate an NLR [7] , the ability of APIP10 to degrade a pathogen effector ( AvrPiz-t ) and to regulate a host NLR ( Piz-t ) is unique . Therefore , identification of the novel E3 ligase APIP10 that functionally connects a fungal effector to its cognate NLR receptor in rice provides new insights into plant innate immunity . We found that AvrPiz-t interacts with APIP10 and that this interaction reduces APIP10 E3 ligase activity . APIP10 specifically ubiquitinates AvrPiz-t but not the unrelated effector AvrPi-ta . The ubiquitination of AvrPiz-t depends on the RING domain of APIP10 , and the degradation of AvrPiz-t depends on the 26S proteasome system . These results suggest that AvrPiz-t could be the pseudo-substrate of APIP10 . By acting as the pseudo-substrate , AvrPiz-t might prevent APIP10 from ubiquitinating either the host proteins or even other cytoplasmic effector proteins secreted from the fungus . Interaction with AvrPiz-t reduces APIP10’s E3 ligase activity and the stability of APIP10 . Turnover of E3 ligase enzymes that contain RING domains is regulated in many ways in cells . For example , CBL RING E3 ligases have substrate-dependent regulation in animal systems because substrate specificity plays a role in CBL turnover [38–40] . Turnover of the rice E3 ligase APIP10 by a fungal effector is an interesting phenomenon . Further investigation of the mechanism underlying APIP10 degradation by AvrPiz-t in rice may provide new insights into fungal–plant interactions . Ubiquitination is important in the regulation of defense-related NLR proteins in plants . Recent research shows that SCFCPR1 regulates the levels of SNC1 and RPS2 [11 , 41] . Also , COP1-dependent regulation of an NLR HRT was observed in response to turnip crinkle virus [13] . In this study , we found that APIP10 is a negative regulator of the NLR receptor Piz-t . Specifically , Piz-t levels are higher in the APIP10 RNAi plants than in control plants , which is consistent with the accumulation of Piz-t after infection with isolates carrying AvrPiz-t . The accumulation of the Piz-t protein after the recognition of AvrPiz-t is unique because the R proteins RPM1 and RPG1 disappear after the recognition of cognate effectors [42 , 43] . RPM1 is rapidly degraded with effector-mediated activation , perhaps due to a negative feedback that limits HR and attenuates the disease resistance response [42] . The same laboratory reported that the disappearance of activated RPM1 is not dependent on the proteasome system because the two common proteasome inhibitors , MG132 and clasto-lactacystin β-lactone , were not able to stabilize steady-state levels of RPM1 [44] . Our results show that the Piz-t protein level is regulated by the proteasome system . However , we don’t know whether the accumulation of the Piz-t protein due to reduced transcription levels of APIP10 leads to the activation of Piz-t and whether the activated form is translocated into the nucleus . In addition , the accumulation of Piz-t in N . benthimiana when AvrPiz-t is expressed is intriguing because it implies that N . benthamiana may have functional otholog ( s ) of APIP10 . Indeed , two APIP10 homologs ( Niben101Scf01072g01009 . 1 , 47% identity , and Niben101Scf05720g06002 . 1 , 43% identity ) were found in the Sol Genomics Network Database ( https://solgenomics . net/ ) . In addition , the APIP10 RING domain is vital for Piz-t degradation , suggesting the importance of E3 ligase activity in regulating NLRs . Even though the negative regulation of Piz-t by APIP10 during M . oryzae infection is clear , how APIP10 regulates the Piz-t protein level before and after M . oryzae infection remains unknown . Because no direct interaction between APIP10 and Piz-t was found in yeast , we speculate that a partner or chaperone protein links APIP10 and Piz-t in rice cells . Identifying this unknown protein is one of our objectives in dissecting the Piz-t-mediated signaling pathway . Many Avr/R protein-protein interactions fit into the guard model , but the molecular mechanism that regulates the recognition and signaling between the pathogen and host proteins is incompletely understood , especially for fungal and oomycete pathogens of plants . In addition and as noted earlier , the regulation of NLR receptors before and after pathogen infection is still unclear . In our previous study [20] , we found that AvrPiz-t targets the E3 ligase APIP6 for degradation and that APIP6 in turn degrades AvrPiz-t and positively regulates PTI to M . oryzae in rice . In this study , we found that APIP10 not only has a similar relationship as APIP6 with AvrPiz-t but also negatively regulates the NLR protein Piz-t via ubiquitination . Based on our previous results and those from this study , we provide the following model to explain the relationships among AvrPiz-t , APIP6 , APIP10 , and Piz-t ( Fig 7 ) . After being secreted and translocated into rice cells , AvrPiz-t interacts with both APIP6/10 and interferes with their E3 ligase activity . In response , APIP6/10 ubiquitinate AvrPiz-t , which causes the degradation of AvrPiz-t in rice cells . When AvrPiz-t is delivered into rice cells without Piz-t , it promotes the degradation of APIP6/10 to suppress PTI . When the Piz-t plants are not attacked by M . oryzae , APIP10 directly or indirectly maintains the Piz-t protein at a low level through ubiquitination . However , when AvrPiz-t is delivered into rice cells expressing Piz-t , AvrPiz-t interacts with and degrades APIP10 , which removes the negative regulation on Piz-t and causes the rapid accumulation of Piz-t protein . The rapid accumulation of Piz-t triggers a strong HR and the activation of defense responses .
Agrobacterium tumefaciens strain GV3101 carrying different constructs was grown with shaking at 28°C . After 18 h , bacterial cells were spun down for 20 min at 3 , 200 g and then resuspended in MES buffer ( 10 mM MgCl2 and 10 mM MES , pH 5 . 6 ) to a final OD600 of 1 . 5 for testing constructs , OD600 of 1 . 0 for p19 , and OD600 of 0 . 25 for TAP tag . After acetosyringone was added to a final concentration of 150 μM , bacterial suspensions were kept at room temperature in the dark for 3 h and were then infiltrated into N . benthamiana plants as previously described [45] . The punch inoculation method [46] with a slight modification was used to evaluate infection of rice plants by M . oryzae . Isolate RB22 was cultured on oat meal agar medium for 2 weeks . A 10-μl volume of a spore suspension ( 5 × 105 spores ml-1 ) was applied to slightly punctured sites of leaves on plants that were 4 to 6 weeks old . Lesion diameter was recorded 10 days after inoculation . To measure the sporulation rate , we removed a 3×1 cm2 leaf piece that included a lesion and immersed it in a microcentrifuge tube containing 100 μl of distilled water with 1% Tween 20 . The samples were vigorously mixed in a vortex apparatus for 2 min to dislodge the spores , and the number of spores ml-1 was determined with a microscope and hemacytometer . The infection ratio was calculated as previously described [47] . Student’s t- test was used to test the significance of the differences between the segregating wild-type and lines expressing the transgenes . qRT-PCR was used to determine gene expression in rice plants or detached leaves . After treatments had been applied to plants or detached leaves , total RNAs were extracted from leaf tissue using TRIzol reagent ( Invitrogen ) according to the manufacturer’s instructions . Total RNA was treated with DNase I ( Invitrogen ) to remove DNA contamination following the manufacturer’s protocol . About 1 μg of DNase I-treated RNA was subjected to first-strand cDNA synthesis using the Promega Reverse Transcription System ( Promega ) . qRT-PCR was carried out using the iQ5 real-time PCR detection system ( Bio-Rad ) . Primers used in this study are listed in S1 Table . The second leaf from the top of 4- to 6-week-old rice plants was used for the measurement of ROS . Small leaf discs ( approximately 4 mm in diameter ) were cut from the leaves with a cork borer and pre-incubated overnight in sterile-distilled water . After the leaf disks were treated with elicitors , ROS generation was monitored by the luminol chemi-luminescence assay [26] . Three pre-incubated leaf disks per sample were immersed in a microcentrifuge tube containing 100 μl of luminol ( Bio-Rad ) , 1 μl of horseradish peroxidase ( Jackson ImmunoResearch ) , and the elicitor ( 100 nM flg22 , 8 nM hexa-N-acetylchitohexaose , or water control ) . Luminescence was measured at 10-s intervals for 21 min using a Glomax 20/20 luminometer ( Promega ) . Each treatment was represented by three replicate microcentrifuge tubes . Semi-in vivo degradation of Piz-t:HA protein by APIP10 was measured as described before [34] . Briefly , total rice protein extracted from M . oryzae-inoculated Piz-t:HA plants was mixed with total protein from either APIP10- or APIP10 dRING-agroinfiltrated N . benthamiana leaves . The reaction was started by adding 10 μM ATP to the mixture on ice . At the indicated time point , SDS loading buffer was added to the samples , which were boiled for 5 min to stop the reaction before immunoblot was performed . More detailed experimental methods can be found in S1 Methods .
|
Rice is the staple food for half of the world’s population . Rice diseases are , however , the major threat for stable rice production worldwide . Elucidating the molecular basis is pivotal for the development of durable resistance to control rice diseases . We previously found that the RING finger E3 ligase APIP6 interacts with AvrPiz-t and plays a role in rice PAMP-triggered immunity ( PTI ) . In this study , we characterized another RING finger E3 ligase in rice , named APIP10 . Like APIP6 , APIP10 and AvrPiz-t degrade each other , and APIP10 is a positive regulator of PTI . Interestingly , reduction of APIP10 expression level in the Piz-t resistant plants causes severe cell death and accumulation of the NLR receptor Piz-t , indicating APIP10 is a negative regulator of Piz-t . We also show that APIP10 can promote Piz-t degradation while AvrPiz-t can stabilize Piz-t . Our results demonstrate that APIP10 is a target of a fungal effector and a negative regulator of an NLR receptor in plants .
|
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2016
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The E3 Ligase APIP10 Connects the Effector AvrPiz-t to the NLR Receptor Piz-t in Rice
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Insulin/IGF-1 signaling ( IIS ) regulates development and metabolism , and modulates aging , of Caenorhabditis elegans . In nematodes , as in mammals , IIS is understood to operate through a kinase-phosphorylation cascade that inactivates the DAF-16/FOXO transcription factor . Situated at the center of this pathway , phosphatidylinositol 3-kinase ( PI3K ) phosphorylates PIP2 to form PIP3 , a phospholipid required for membrane tethering and activation of many signaling molecules . Nonsense mutants of age-1 , the nematode gene encoding the class-I catalytic subunit of PI3K , produce only a truncated protein lacking the kinase domain , and yet confer 10-fold greater longevity on second-generation ( F2 ) homozygotes , and comparable gains in stress resistance . Their F1 parents , like weaker age-1 mutants , are far less robust—implying that maternally contributed trace amounts of PI3K activity or of PIP3 block the extreme age-1 phenotypes . We find that F2-mutant adults have <10% of wild-type kinase activity in vitro and <60% of normal phosphoprotein levels in vivo . Inactivation of PI3K not only disrupts PIP3-dependent kinase signaling , but surprisingly also attenuates transcripts of numerous IIS components , even upstream of PI3K , and those of signaling molecules that cross-talk with IIS . The age-1 ( mg44 ) nonsense mutation results , in F2 adults , in changes to kinase profiles and to expression levels of multiple transcripts that distinguish this mutant from F1 age-1 homozygotes , a weaker age-1 mutant , or wild-type adults . Most but not all of those changes are reversed by a second mutation to daf-16 , implicating both DAF-16/ FOXO–dependent and –independent mechanisms . RNAi , silencing genes that are downregulated in long-lived worms , improves oxidative-stress resistance of wild-type adults . It is therefore plausible that attenuation of those genes in age-1 ( mg44 ) -F2 adults contributes to their exceptional survival . IIS in nematodes ( and presumably in other species ) thus involves transcriptional as well as kinase regulation in a positive-feedback circuit , favoring either survival or reproduction . Hyperlongevity of strong age-1 ( mg44 ) mutants may result from their inability to reset this molecular switch to the reproductive mode .
The IIS pathway , governing developmental arrest , metabolism and life span in Caenorhabditis elegans [1]–[3] , is highly conserved from invertebrates to mammals . The single IIS pathway of nematodes corresponds in structure and function to two distinct pathways of mammals that signal metabolic responses to insulin , and growth response to insulin-like growth factor 1 ( IGF-1 ) , respectively [4] . IIS disruption was first discovered to enhance longevity in C . elegans [5]–[8] , but it was subsequently shown to also extend life in D . melanogaster and mice [9]–[11] . Binding of insulin-like peptides to DAF-2 , the insulin/IGF-1 receptor of nematodes , modulates receptor autophosphorylation and activation [12] . Active DAF-2 recruits and phosphorylates the AGE-1 catalytic subunit of phosphatidylinositol 3-kinase ( PI3K ) , which in turn phosphorylates the regulatory subunit . Activated AGE-1 then adds a phosphate to phosphatidylinositol 4 , 5-diphosphate [PI ( 4 , 5 ) P2] at the inositol-ring 3-position , converting it to phosphatidylinositol 3 , 4 , 5-triphosphate [PI ( 3 , 4 , 5 ) P3 or PIP3] . PIP3 plays a dual role in the canonical insulin/IGF-1 pathway . The first pivotal role is membrane tethering of many signaling molecules including AKT-1 and -2 , PDK-1 , GSK-3 and protein kinase C [13]–[16] . PIP3-binding recruits or retains many kinases at the cytoplasmic surface of the cell membrane , where these enzymes and their substrates ( largely other kinases ) are concentrated and , by mass action , interact more efficiently . Because PIP3 quantitatively affects multiple components of the IIS cascade , the influence of its concentration is compounded . In addition , PIP3 binding to AKT-1 allosterically exposes a cryptic site recognized by PDK-1 ( phosphatidylinositol-dependent kinase 1 ) , allowing AKT phosphorylation and activation [17] . In this second role , PIP3 may act catalytically , in that a single molecule of PIP3 has the potential to bind successively to many AKT-1 molecules , enabling their activation . Although AKT-1 is the only target for which this allosteric role has been documented [17] , it is possible that other signaling molecules that also possess high-affinity PIP3 binding sites ( termed “Pleckstrin homology domains” ) may be similarly controlled . In any event , we infer that insulinlike signaling should be exquisitely sensitive to PIP3 depletion , and that AKT-1 action ( which extends far beyond IIS [18] , [19] ) may be absolutely dependent on the presence of at least trace amounts of PIP3 . The AKT-1/AKT-2/SGK-1 complex , once all of its constituent kinases have been activated by PDK-1 [20] , phosphorylates the DAF-16/FOXO transcription factor at sites that block its entry into the nucleus , where it would activate or repress transcription of hundreds of target genes , including many that modulate metabolism , reproduction , life span , and resistance to oxidative stresses [21]–[24] . Reduction-of-function mutations impairing the C . elegans IIS pathway ( e . g . , daf-2 and age-1 mutations ) cause these worms to arrest development as dauer ( alternative stage-3 ) larvae [1]–[3] . If allowed to mature at a permissive temperature , temperature-sensitive ( ts ) daf-2 mutant adults can attain twice the normal longevity [6]; life extension ranges from 1 . 1- to 2 . 5-fold for different daf-2 alleles [25] . A ts mutant allele of age-1 , hx546 , was discovered by Klass [26] and reported to confer 40% and 65% life extension at 20° and 25°C respectively [5] , [27] , [28] . Two constitutive age-1 alleles , m333 and mg44 , were initially reported to extend C . elegans life span by 2- to 2 . 6-fold [2] , [8] , [29]; these survivals were conducted only for first-generation ( “F1” ) homozygotes . We recently observed that second-generation age-1 ( mg44 ) and ( m333 ) larvae slowly mature at 15–20°C into adults that live close to ten times as long as near-isogenic wild-type controls , and are highly resistant to oxidative and electrophilic stresses [30] . These exceptional worms have mean and maximal adult life spans at least three times those conferred by any other longevity-extending mutation , and throughout their adult lives they appear and behave very much like wild-type worms of a tenth their age . Addition of a second mutation in the daf-16 gene largely or entirely reverses life-span extension and other phenotypes of all daf-2 or age-1 mutations examined to date [3] , [6] , [29] , [30] . Studies of IIS-pathway mutants in C . elegans and other taxa have provided valuable insights into genetic mechanisms regulating life span [4] . The molecular basis for the extreme survival phenotypes of age-1 ( mg44 ) F2 homozygotes remains unknown , and cannot be assumed to differ only in degree from molecular mechanisms that underlie 4- to 5-fold lesser life extensions seen in other IIS mutants . The key may be PIP3 , which plays both structural and catalytic roles in signal transduction [17] , [31] , and is thought to mediate both DAF-16-dependent and -independent signaling [32] . Strong age-1 mutants , lacking all class-I PI3K activity , have no direct route to generate PIP3 [31] . As a result , they are expected to be deficient in all enzyme activities that require PIP3 , either for activation by regulatory kinases , or for membrane tethering which ensures proximity of kinases to their targets [17] , [31] . In the present study , we sought evidence to support such a broad role of PIP3 in the unique properties of age-1 ( mg44 ) -F2 adults . This role is an inferred one , since even normal PIP3 levels ( in unstressed N2 worms ) are too low for detection by existing methods; detectable levels are attained in starved , peroxide-stressed wild-type worms but not in similarly stressed age-1-mutants [33] . We were able to document the expected widespread disruption of protein kinase activity in age-1 ( mg44 ) -F2 worms , while making the unexpected observation that the same kinases are chiefly inhibited at the transcriptional level . Direct measurement of transcripts confirms silencing of kinase gene expression , leading us to propose a novel “hybrid” positive-feedback loop in which the IIS kinase cascade that inhibits the DAF-16/FOXO transcription factor , is itself attenuated by DAF-16-mediated transcriptional silencing of upstream kinases .
The age-1 ( mg44 ) kinase-null mutants should be deficient in phosphatidylinositol 3 , 4 , 5-triphosphate production . Given the importance of the PIP3 molecule in signal transduction events originating from many membrane-receptor kinases , we anticipated that phosphorylation of numerous proteins may be impaired in those mutants . To initially assess the breadth of this impairment , we compared in vitro kinase activities with respect to endogenous substrates for five age-1 mutant strains , each normalized to a wild-type N2DRM stock ( Figure 1A–1C ) . Panels A and B illustrate a typical experiment , and panel C summarizes results for replicate experiments with independent expansions of each group . The first-discovered and most widely used age-1 allele , hx546 [5] , [27] , [28] , showed 32% less kinase activity than N2DRM ( Figure 1C ) . However , worms bearing the age-1 ( mg44 ) allele had less than 10% of wild-type kinase activity , whether maternally protected first-generation ( F1 ) or very long-lived second-generation ( F2 ) homozygotes . The F2 worms had somewhat lower kinase activity than F1 ( 7 . 3 vs . 8 . 6% of N2DRM , P = 0 . 05 ) , although the difference was consistently much greater for specific bands ( see Figure 1B ) . Staining of total protein showed similar loads for all samples , although banding patterns differed ( Figure 1A ) . One obvious difference between age-1 ( mg44 ) and the other strains is that these mutants are totally infertile in the F2 generation , despite the presence of syncytial nuclei [30] . Several controls exclude this as an explanation for the mutants' lack of kinase activity . age-1 ( mg44 ) F1's have similar kinase levels when gravid ( day 2 of adulthood ) or post-gravid ( adult day 6; see Figure S1 ) . Moreover , N2DRM eggs contain about half as much kinase activity as their parents , per weight of protein ( Figure S1 ) , so their absence would not reduce kinase activity in any case . Deficiency of kinase activity is not a characteristic of dauer larvae , which exhibit a level comparable to that of N2DRM adults ( Figure S1 ) . The consequences of adding a daf-16 mutation are quite different for the two age-1 alleles: in age-1 ( hx546 ) worms , the daf-16 ( m26 ) mutation more than doubled the in vitro kinase activity , from 68% of wild-type to 160% , whereas this mutation restored less than half of the kinase deficiency due to the age-1 ( mg44 ) allele . Insofar as kinase suppression is reversed in daf-16; age-1 ( mg44 ) double mutants , we infer that activity is inhibited in part through the DAF-16/ FOXO transcription factor . However , reversion is far from complete , by either the m26 ( point-mutant ) or the mu86 ( large-deletion ) allele of daf-16 ( see Figure 1C and Figure S1 ) . This implies that a large proportion of observed kinase silencing is DAF-16-independent—perhaps reflecting direct effects of PIP3 depletion on kinases other than AKT , or AKT targets other than DAF-16/FOXO . To corroborate low protein-kinase activity of age-1 ( mg44 ) adults , and to distinguish whether they are deficient for many protein kinases or a few very active ones , we constructed arrays of 70 synthetic peptides comprising 50 near-consensus kinase sites from the C . elegans proteome and 20 from mouse or human proteins . Phosphorylation in vitro was observed on 29 peptides , representing potential substrates for at least 18 distinct kinases ( Figure S2 and Table S1 ) . Protein kinase activity in extracts from age-1 ( mg44 ) F2 adults was reduced by 1 . 8- to >8-fold , relative to isogenic N2DRM postgravid worms ( each at nominal P<0 . 05 ) , for 22 of the 29 kinase targets that were phosphorylated in vitro . Addition of the daf-16 ( mu86 ) mutation produced essentially complete reversion , or hyper-reversion ( activity>N2DRM ) , for 17 of those 22 peptides . In view of the reduced protein-kinase activity of age-1 ( mg44 ) worms , we anticipated that their steady-state level of protein phosphorylation would also be depressed . To assess this , phosphoproteins were separated by acrylamide gel electrophoresis and compared among wild-type and age-1-mutant strains of C . elegans ( Figure 1D–1F ) . Total protein staining ( panel D ) demonstrated even loading , while panel E shows the same gel stained with Pro-Q Diamond to detect and quantify phosphoproteins . Results for three replicates ( independent expansions of each strain ) are summarized in panel F . Relative to wild-type N2DRM , age-1 ( hx546 ) worms had 16% less phosphoprotein staining ( marginally significant at P<0 . 05 ) , while age-1 ( mg44 ) homozygous F2 adults showed a 41% reduction in steady-state phosphoprotein level ( P<0 . 001 ) . The daf-16 ( m26 ) mutation restores either allele to ∼92% of the N2DRM level . This finding is also supported by 2-D dual-fluor phosphoprotein gels ( Figure 2 ) , in which 72% of the phosphoprotein spots resolved ( 1199/1669 ) were reduced at least twofold in F2 age-1 ( mg44 ) adults relative to N2DRM . The deficiency of total phosphoprotein content is less pronounced than that of protein kinase activity , in age-1 ( mg44 ) -homozygous F2 adults , which is not surprising given that phosphoprotein levels reflect the steady state , i . e . , a balance between kinase and phosphatase activities . We present evidence ( next section ) that the PTEN phosphatase is indeed downregulated in age-1 ( mg44 ) . F2 homozygotes for age-1 ( mg44 ) are expected to produce only truncated class-I PI3KCS , lacking the kinase domain and C-terminus of the protein . These worms indeed lack the main bands recognized by antibodies to the AGE-1 C-terminal region ( Figure S3 ) ; residual bands may represent class-II and -III homologs of AGE-1 . PIP3 , formed exclusively by class-I PI3K , should thus be greatly reduced or absent . PIP3 is strictly required for PDK-1 activation of AKT kinase , which then phosphorylates and inactivates DAF-16/FOXO . Kinases that require PIP3 binding for membrane tethering or kinase activation [17] , [31] , such as AKT , PDK-1 , and SGK-1 , are expected to show marked suppression of activity , which cannot be directly reverted by a daf-16 mutation . The surprising observation that mutations to daf-16 restore nearly half of the age-1 ( mg44 ) -F2 kinase deficiency , and >70% of its phosphoprotein deficit , implies that their inhibition must be mediated in part by DAF-16/FOXO . Such regulation could be direct ( DAF-16 suppresses transcription of many kinase genes ) or indirect ( DAF-16 suppresses one or a few kinases , or stimulates one or a few phosphatases , which then suppress other kinases by impeding or opposing their phosphorylation ) . To test direct effects of DAF-16/FOXO , we used real-time polymerase chain reaction ( RT-PCR ) to quantify the effects of age-1 alleles , with or without added inactivation of daf-16 , on transcript levels for IIS genes and a panel of other signaling components , representing a wide range of transduction pathways . F2 age-1 ( mg44 ) adults , which are 4- to 5-fold longer-lived than F1 adults ( comparing data of [8] , [29] to [30] ) , also outperform their parents with respect to resistance to oxidative and electrophilic stresses ( Figure 5A and 5B ) . Relative to N2DRM controls , survival in 5% hydrogen peroxide is extended 2-fold in F1 adults , but 10-fold in their F2 progeny . Because age-1 ( mg44 ) -F2 adults barely reached 20% mortality after 24 h , by which time 100% of worms had died in all other groups , survival time is here compared at a threshold of 20% mortality . Survival of an electrophilic stress , 4-HNE ( similarly defined as time to 20% mortality ) increased 1 . 6-fold in age-1 ( mg44 ) F1 worms but 5-fold at F2 , with reference to N2DRM . Although resistance to these stresses is restored almost to wild-type levels in double mutants with daf-16 , we note that reversion is not quite complete , whether using the weaker daf-16 ( m26 ) allele [30] or the daf-16 ( mu86 ) deletion allele ( Figure 5A ) , indicating that such stress-resistance traits are mediated in part by a DAF-16-independent pathway . These results parallel the incomplete reversion , in daf-16; age-1 ( mg44 ) double mutants , seen for in vitro kinase activity and phosphoprotein levels ( Figure 1 ) and for transcript levels of several genes ( Table 1 ) . Most or all of the age-1 ( mg44 ) -downregulated genes are essential for nematode growth and development . That is , double-stranded RNAs ( dsRNAs ) targeting them , administered to developing C . elegans , produce embryonic lethality or larval arrest [54]–[56] . The impact of such knockdown , however , has thus far remained largely untested in adults . Because resistance to oxidative stresses is a common feature of many long-lived C . elegans mutants [57] , and in particular parallels longevity in the age-1 allele set studied here ( Figure 5 and [30] ) , we employed it as a short-term assay to evaluate the contribution of individual-gene downregulation , to the exceptional survival of age-1 ( mg44 ) -F2 adults in both benign and toxic environments . Hydrogen peroxide resistance was measured in duplicate experiments , for wild-type N2DRM worms that had been exposed to dsRNA-expressing bacteria targeting 10 genes for which transcript levels are markedly reduced in age-1 ( mg44 ) -F2 adults . Genes were selected from among those not directly involved in the IIS pathway , but representing a variety of other signaling pathways , and for which RNAi constructs were available from the Ahringer library [56] . E . coli , either harboring an empty-vector control or expressing one of 10 gene-targeted dsRNA species , were fed to mature adults ( days 3 through 6 after the L4/adult molt ) so as to preclude effects on development . Survival curves , during subsequent exposure to 5-mM H2O2 , are shown in Figure 5C . RNAi for four of the ten genes ( encoding a transcription factor and three components of distinct protein-kinase signaling cascades ) produced highly significant gains in peroxide survival ( each P<0 . 001 ) , and a fifth dsRNA exposure offered marginally significant protection ( vps-34 , P<0 . 03 ) . The remaining five dsRNA treatments had no discernible effect on survival , compared to worms exposed only to the empty expression vector . The above results were reproduced in an independent experiment , with the same four genes attaining P<0 . 001 , while vps-34 achieved P<0 . 08 . Genes ( and encoded proteins ) for which RNAi knock-down conferred a protective effect were daf-3 ( SMAD transcription factor ) and daf-4 ( TGF-β receptor , a Ser/Thr kinase ) , both involved in TGF-β signaling; aak-1 ( AMP-dependent protein kinase 1 ) , part of the AMPK/TOR pathway; let-60 ( RAS-family GTPase activating MAPK ) , part of the ERK-MAPK pathway , and vps-34 ( class-III PI3KCS ) , involved in vesicular trafficking and autophagy . None of these individual RNAi effects matched the peroxide survival of untreated age-1 ( mg44 ) F2 adults at 62 days of adult age ( large diamond symbols , Figure 5C ) . These data demonstrate that transcript-level changes seen in age-1 ( mg44 ) F2 homozygotes favor oxidative-stress survival . They may also contribute incrementally to the greatly enhanced longevity of F2 homozygotes , but we have not been able to confirm such effects . When begun at the end of larval development , RNAi to aak-1 and daf-4 extended survival by 7–11% , while let-60 dsRNA reduced it by ∼12% ( data not shown ) . Such small effects on life span require large groups to reach significance; moreover , significance in one experiment provides little assurance that independent replicates will attain significance . This may reflect the low statistical power inherent to survivals of modest size , and/or inability to control environmental variance among experiments .
Transcriptional effects within the IIS pathway seem fully consistent with impaired insulinlike signaling , which might be expected to further augment survival through the same mechanisms employed by weaker IIS mutations . Moreover , repression of class-II and class-III PI3K catalytic-subunit genes ( Table 1 ) would impede formation of PI ( 3 ) P and PI ( 3 , 4 ) P2 , suppressing alternative routes to PI ( 3 , 4 , 5 ) P3 . Increased expression of aak-2 contributes to activation of DAF-16/FOXO , further opposing IIS ( which inhibits this transcription factor ) and increasing life span [43] , [44] . In addition to effects on IIS genes , however , age-1 ( mg44 ) -F2 adults also show striking transcriptional attenuation of several other signal transduction pathways that interact with IIS and with one another . TGF-β endocrine/paracrine signaling is active in development , and modulates several other signaling pathways including p38/MAPK and ERK/MAPK [46] . Both daf-1 and daf-4 , encoding type-I and -II TGF-β receptors , respectively , are downregulated 4- to 5-fold in age-1 ( mg44 ) -F2 adults . Expression is also reduced 3-fold for daf-3 , encoding a co-SMAD transcription factor deployed by several pathways including TGF-β . Perhaps in partial compensation for this signaling downregulation , the daf-7 gene encoding a TGF-β-family ligand/agonist is 5-fold upregulated . Silencing of TGF-β signaling , by RNAi directed at daf-3 or daf-4 , improves survival in the presence of hydrogen peroxide , consistent with a prior observation that daf-1 , -4 and -7 mutants are long-lived [46] . AMPK/TOR signaling has been implicated in innate immunity and stress responses . Although it remains controversial whether the primary response is to the microbe or to the stress it causes [47] , both could be secondary to its role in nutrient sensing [37] , [43] . AAK-1 and AAK-2 are regulated by the PAR-4 transcription factor [37] , [58] , [59] , and aak-1 knockdown by RNAi confers resistance to oxidative stress ( Figure 5C ) . Inhibition of the C . elegans TOR pathway confers stress resistance and extends life span [60] , [61] . ERK/MAPK signal-transduction is essential for many developmental processes; because the constituent genes are also expressed in adult nematode tissues , they are presumed to have post-developmental functions not yet defined [62]–[64] . All six genes tested in this pathway are markedly downregulated , by 3- to >6-fold ( Table 1 ) , and RNAi inhibition of let-60 ( encoding a RAS membrane co-receptor that initiates ERK/MAPK signaling ) significantly improves survival of oxidative stress ( Figure 5C ) . The most dramatic effects of gene mutations on life span have involved hypomorphic ( loss-of-function ) mutations , and the genes affected have been termed aging “master genes” . The genes encoding IIS components provide the best-studied example . IIS , in common with many “master genes” and essentially all signaling pathways , regulates numerous other genes . In the case of IIS , a number of these are modulated in ways that are protective , or otherwise conducive to long life , such as upregulation of GSTs and other detoxification genes , which are among the “foot soldiers” of longevity assurance [65] , [66] . However , we should not expect all such downstream consequences to confer uniformly pro-longevity effects; each gene is likely to serve several “masters” , and its level of expression will depend on the genetic , environmental , and signaling context . In keeping with this perspective , the downstream manifestations of longevity assurance genes are far less conserved , both in evolution and between distinct physiological states of a given species , than are the over-arching pathways and the functions they serve [67] . Improved stress resistance and survival of age-1 ( mg44 ) F2 worms , apparently arising from transcriptional attenuation of signaling pathways presumed to be protective , poses an intriguing paradox . These pathways , activated by nutrient deficiency , pathogens , or growth factors , have been reported to cross-talk with IIS at diverse levels [19] , [43]–[47] , [68] , [69] . This suggests a complex fabric of signaling interactions , for which the impact of silencing multiple components cannot be predicted . Moreover , signaling that promotes survival in a variable or hostile setting may entail energy costs and harmful side-effects that would be unwarranted in a constant , pathogen-free environment with abundant food . An organism that avoids the deleterious aspects of these surveillance systems may thus reap survival benefits under benign conditions . In several instances , the expression changes seen in strong-age-1 mutants appear to oppose their longevity or stress-resistance , based on the effects of down- or upregulation previously reported for the same genes . For example , age-1 ( mg44 ) F2 adults downregulate daf-18 , which encodes the PIP3 3-phosphatase , PTEN . This would be expected to elevate the steady-state level of PIP3 , thereby enhancing IIS and reducing longevity of normal worms . However , in the absence of AGE-1/PI3KCS kinase activity , there may be little or no PIP3 substrate on which PTEN could act . A second example is downregulation in age-1 ( mg44 ) F2 adults of skn-1 , encoding a transcription factor responsive to oxidative damage and regulated via IIS [70]–[72] . Reduced expression of skn-1 seems at odds with increased oxidative-stress resistance and longevity; however , these very long-lived worms may generate lower levels of reactive oxygen species , thereby reducing skn-1 induction . RNAi to vps-34 ( encoding a class-III PI3KCS required for vesicular trafficking and autophagy [73] ) was recently shown to block life extension of eat-2 ( ad1116 ) and daf-2 ( mu150 ) mutants , although not of wild-type worms [58] . Autophagy is induced by TOR deficiency [58] , and several TOR signaling components are downregulated in F2 worms ( Table 1 ) . Considering this , autophagy should be at least moderately induced in those worms , and its absence would not account for low expression of vps-34 . These results argue against any direct role of vps-34 attenuation in the exceptional longevity of age-1 ( mg44 ) F2 worms . The possibility remains , however , that vps-34 downregulation could reinforce PIP3-depleting effects of a strong age-1 mutation . Downregulation in age-1 ( mg44 ) worms , of transcripts for let-60/RAS and five other members of the ERK-MAPK cascade , might be expected to oppose additional life extension beyond that typical of IIS mutants , because a let-60 gain-of-function mutation enhances daf-2 life extension [74] . RNAi targeting smk-1 , encoding a transcriptional coactivator shared by DAF-16 and PHA-4 [75] , reduces stress-resistance and lifespan of daf-2 ( e1370 ) worms [76] , whereas the effect on wild-type worms is controversial [34] , [76] . Although smk-1 knockdown impairs sod-3 expression in daf-2 worms [34] , we found 9-fold elevation of sod-3 transcripts in the face of a 72% drop in smk-1 expression in age-1 ( mg44 ) ( Table 1 ) . Finally , sir-2 . 1 overexpression was reported to extend lifespan , and knock-down to shorten it [77] , [78] , whereas we found almost 4-fold downregulation of sir-2 . 1 in age-1 ( mg44 ) -F2 adults . Although contradictory in the context of extreme stress resistance and longevity , all six of these “exceptions” are also mirrored , in most cases to a lesser degree , in dauer larvae ( Table 1 ) , a robust state of developmental arrest that can endure for months without reducing adult life span [1] , [79] , [80] . This raises the possibility that for these genes , the effects of downregulation are context-dependent , and may be beneficial in worms that are already highly protected from stress and aging . Alternatively , these expression changes may follow from regulatory mechanisms shared by age-1 ( mg44 ) adults and N2 dauers , and yet work in opposition to their robustness . This is plausible in the case of a severe loss-of-function mutant , effects of which are not orchestrated , but is difficult to reconcile with a highly-evolved alternative developmental state such as the dauer larva . Perhaps , rather than a single coherent program , the patterns we observe reflect aberrant triggering in the adult of one or more regulatory mechanisms that are normally utilized in developmental or metabolic regulation . This particular combination of mechanisms could be the serendipitous result of a profound alteration in PIP3 levels which in turn impacts multiple pathways . The expression profile of age-1 ( mg44 ) worms depends largely on DAF-16/FOXO , consistent with prior evidence that C . elegans IIS operates mainly through this transcription factor , impacting several hundred target genes [2] , [21] , [22] , [29] , [52] , [81] . Although DAF-16/FOXO has been regarded largely as a transcriptional activator [21] , [82] , it also effects negative regulation of many genes [24] . In our selected panel of genes , two-thirds ( 22/33 ) of the DAF-16-mediated effects of age-1 ( mg44 ) mutation involve reduced transcript levels , indicating that silencing prevails for gene transcripts that encode kinases and other mediators of intracellular signaling . Twenty-eight genes ( of the 33 for which transcripts appear to be primarily regulated via DAF-16/FOXO ) were mapped for DAF-16 binding sites within 5 kb upstream of the initiation codon ( Table 1 ) . Of these , 21 ( 75% ) have exact matches to one or both of the two known consensus sites , GTAAA ( C/A ) AA and CTTATCA . Genes lacking such sites may be indirect targets of DAF-16/FOXO , but considering that those motifs occur at almost the same frequency in the genome at large [81] , as in DNA immunoprecipitated with antibody to DAF-16/FOXO [52] , it is possible that precise motif matches are neither necessary nor sufficient for DAF-16 binding . In other words , near-match sequences might be able to bind DAF-16 , while even perfect-match motifs may require additional features in nearby DNA . It is surprising that hyperactivation of DAF-16/FOXO in age-1 ( mg44 ) F2 adults silences essentially the entire IIS pathway . This implies a positive feedback loop , in which DAF-16/FOXO imposes transcriptional silencing on the very kinases that would inhibit its own nuclear localization and hence access to target genes ( Figure 6 ) . We propose that second-generation age-1 ( mg44 ) homozygotes are trapped in a nonadaptive state , incapable of responding to diverse environmental and internal signals . This apparent paradox , that failure of adaptive mechanisms greatly extends lifespan , is easily explained because those mechanisms maximize Darwinian fitness – transmission of genetic alleles to ensuing generations – rather than individual survival [83] , [84] . When IIS kinase signaling predominates ( the reproductive state ) , it suppresses DAF-16/FOXO activity . Activation of PI3K favors PIP3 production and AKT activation , both of which promote cell proliferation [18] , [31] , [85] . However , IIS can switch to a second , functionally distinct , state: when kinase signaling is weak , DAF-16/FOXO becomes activated . As we have demonstrated , active DAF-16/FOXO transcriptionally silences its own upstream regulatory kinases , which otherwise would have impeded DAF-16/FOXO action by preventing its nuclear localization . Therefore , the low-signaling , longevity state of IIS is self-sustaining . Biologically , this state promotes dauer formation during development , or life-extension and delayed reproduction in the adult ( reviewed in [4] ) . Signals that inhibit IIS kinases or augment DAF-16/FOXO action , if sufficient , trigger a switch from reproductive to longevity state in which DAF-16/FOXO promotes somatic protective mechanisms ( Figure 6 ) . However , exiting the stable longevity mode requires a shift in the balance of inputs that govern the positive feedback loop . Such inputs may include insulin-like peptide agonists and antagonists , hormones , pheromones , transcriptional co-activators and co-repressors of DAF-16/FOXO such as SIR-2 and 14-3-3 proteins , and nutrient- and stress-sensors signaled though other kinase pathways ( e . g . , MAPK , JNK and AMPK ) that cross-talk with IIS . Combined , these two normal states of the IIS pathway ( reproductive and longevity ) constitute a “flip-flop” circuit with opposing kinase-cascade and transcriptional signals ( Figure 6 ) . The concept of a “genetic switch” for dauer formation is not new [1] , [86] , [87] , and has even been demonstrated to constitute a bistable feedback loop [21] , [87] . Nevertheless , a dual-level ( kinase/transcriptional ) feedback mechanism had not previously been proposed or described . Any such “flip-flop” circuitry allows the organism a simple binary choice in response to its environment: early reproduction under benign conditions , or postponed reproduction and extended survival in harsher conditions . Mutational disruption of IIS forces dauer formation , irrespective of environment , although larvae with temperature-sensitive mutations can mature at lower temperatures into long-lived adults . Recovery from the dauer state requires that pro-reproductive-state kinases retain partial function , so that favorable signals ( restoration of food , absence of stress and crowding ) can reset the switch to the reproductive mode; this requirement is demonstrated by the impaired post-dauer recovery of IIS-defective mutants [86] . Nonsense mutations truncating AGE-1 produce an extreme phenotype that forfeits this option , while acquiring a distinctive transcriptional profile and greatly enhanced survival . Details of the mechanism or mechanisms , by which elimination of PI3K activity blocks exit from the longevity mode and promotes extreme longevity , remain to be elaborated . Features described in this report , which may contribute , include transcriptional silencing of upstream and collateral signaling components , and accompanying loss of multiple kinase activities . Infertile mutants may thus reveal new strategies to extend life well beyond the limits imposed by natural selection , which of course requires reproduction . In view of the striking evolutionary conservation of the IIS pathway , and the emerging parallels between inter-pathway cross-talk in nematodes and mammals [16] , [19] , [47] , [68] , [69] , the mechanistic insights afforded by very long-lived worms are likely to also apply to insulin and IGF-1 pathways of mammals .
Nematode strains , supplied by the Caenorhabditis Genetics Center ( CGC , Minneapolis ) , or derived in our laboratory from CGC strains , were maintained at 20°C on 0 . 6% peptone NGM-agar plates seeded with E . coli strain OP50 , as described [88]–[90] . Assays of survival in the presence of 5-mM hydrogen peroxide or 10-mM 4-hydroxynonenal were modified from Ayyadevara et al . [91] . Wild-type ( N2DRM ) worms were assayed at day 3–4 of adulthood ( ∼6 d post-hatch ) . For RNAi experiments , day-1 adults were washed in S-buffer [92] and transferred to nutrient-agar plates seeded with dsRNA-expressing E . coli [56] . After 3 days at 20°C , 20 worms from each RNAi treatment were transferred to 24-well plates containing 300 µl of S Buffer plus 5 µg/ml cholesterol , supplemented , as indicated , either with 5-mM H2O2 ( freshly diluted from 30% H2O2 , Sigma ) or with 10-mM 4-HNE ( freshly obtained by acid hydrolysis of 4-HNE dimethylacetal which was synthesized according to [93] . Survival was scored as described [30] , [89] . Worms grown at 20°C were quickly frozen in liquid nitrogen to preserve endogenous kinase activity . Worms suspended in 50-mM Tris pH 7 . 5 , 80-mM β-mercaptoethanol , 2-mM EDTA , 1-mM PMSF , and Protease Inhibitor Cocktail I ( CalBiochem ) , were ground at −78°C and sonicated ( VIRTIS Virsonic 475 , setting 2 . 5 , 0°C ) in six 10-s bursts interspersed with 2-min cooling periods . Kinase activity toward endogenous substrates was assessed in cleared supernatants after centrifugation ( 10 min , 11 , 000 g ) , representing 20 µg protein in 100 µl of buffer containing 50-mM Tris pH 7 . 5 , 12 . 5-mM MgCl2 and ( for endogenous substrates ) 8–10 µCi γ-32P-ATP ( NEN ) . After 1 min at 30°C , quenched samples were electrophoresed on 10% SDS-polyacrylamide gels ( Invitrogen ) , which were stained with SYPRO Ruby ( Invitrogen ) , and dried under vacuum . 32P β-emissions of bands migrating slower than a 25-kDa protein marker ( Invitrogen ) , were imaged and quantified per lane after 6-h phosphor-screen exposure ( Storm , Molecular Dynamics ) . Peptide arrays were incubated as above , 60 min at 30°C , but with addition of phosphatase inhibitors and 1-mM cold ATP rather than 32P-ATP . Arrays were then stained with Pro-Q Diamond ( Invitrogen ) , and phosphorylation was quantified by fluorescence imaging ( excitation/emission at 550/580 nm ) with a ScanArray 5000 ( GSI Lumonics ) . Total protein ( 20 µg ) , extracted from each strain as above , was loaded onto NuPAGE 4–12% gradient gels ( Invitrogen ) and electrophoresed 1 hour at 200 V . Phosphoproteins were quantified by Pro-Q Diamond ( Invitrogen ) fluorescence , which depends linearly on protein concentration ( >1000-fold range ) . Protein load was assessed by Coomassie Blue ( BioRad ) staining . Phosphorylated ( 23 . 6 , 45 . 0 kDa ) and unphosphorylated ( 14 . 4 , 18 . 0 , 62 . 6 , 116 . 2 kDa ) protein standards ( BioRad ) furnished positive and negative controls . Expression of selected genes was assessed by real-time polymerase chain reaction after an initial round of reverse transcription . Total RNA was purified from each strain ( RNeasy , Qiagen ) , and cDNAs reverse-transcribed ( SuperScript III , Invitrogen ) , followed by RT-PCR ( Opticon2 , MJ Research , using SYBR Green , Roche ) .
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Insulin/IGF-1 signaling ( IIS ) impacts development , metabolism , and longevity in Caenorhabditis elegans . It has been viewed as a cascade of kinase reactions , chiefly phosphorylation of other kinases , leading to inactivation of the DAF-16/FOXO transcription factor . PI3K , a phosphatidylinositol kinase at the center of this pathway , converts PIP2 to PIP3 , instrumental to kinase docking and activation . Here we show that PI3K deficiency elicits transcriptional inhibition of many kinases , including those of IIS itself . This creates a positive-feedback loop , wherein DAF-16/FOXO silences expression of the very kinases that would have inactivated it . In the resulting “flip-flop” genetic switch , either kinase signaling or transcriptional silencing may predominate . We discovered the transcriptional arm of this switch in infertile age-1 ( mg44 ) mutants , defective for PI3K activity . The absence of PIP3 and PIP3-dependent kinase activity gives free rein to gene silencing by DAF-16/FOXO . This two-tiered response could scarcely have evolved for the benefit of a sterile mutant; some components presumably serve regulatory functions in normal animals , reinforcing a switch responsive to environmental and internal signals . In age-1 ( mg44 ) mutants , complete inactivation of PI3K “fuses” the switch , locking worms into longevity mode . With signaling profoundly silenced , they cannot resume reproduction , but instead acquire a remarkable capacity for individual survival .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"and",
"genomics/gene",
"expression",
"cell",
"biology/cell",
"signaling",
"molecular",
"biology/molecular",
"evolution",
"developmental",
"biology/aging",
"biochemistry/cell",
"signaling",
"and",
"trafficking",
"structures",
"cell",
"biology/gene",
"expression"
] |
2009
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Positive Feedback between Transcriptional and Kinase Suppression in Nematodes with Extraordinary Longevity and Stress Resistance
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Orientia tsutsugamushi is the causative agent of scrub typhus , a disease transmitted by Leptotrombidium mites which is responsible for a severe and under-reported public health burden throughout Southeast Asia . Here we use multilocus sequence typing ( MLST ) to characterize 74 clinical isolates from three geographic locations in the Lao PDR ( Laos ) , and compare them with isolates described from Udon Thani , northeast Thailand . The data confirm high levels of diversity and recombination within the natural O . tsutsugamushi population , and a rate of mixed infection of ~8% . We compared the relationships and geographical structuring of the strains and populations using allele based approaches ( eBURST ) , phylogenetic approaches , and by calculating F-statistics ( FST ) . These analyses all point towards low levels of population differentiation between isolates from Vientiane and Udon Thani , cities which straddle the Mekong River which defines the Lao/Thai border , but with a very distinct population in Salavan , southern Laos . These data highlight how land use , as well as the movement of hosts and vectors , may impact on the epidemiology of zoonotic infections .
Scrub typhus , caused by the Gram negative obligate intracellular coccobacillus Orientia tsutsugamushi , is an important cause of acute febrile illness in Asia responsible for up to 23% of cases of undifferentiated fever [1] . The infection represents a major disease burden throughout a region ranging from northern Japan to Pakistan , to Russia in the north and northern Australia in the south . Over 55% of the world’s population lives in this densely populated endemic area [2] . It can affect patients of all ages , with at least one billion people living in rural areas at risk , and perhaps approximately a million patients needing medical attention every year [3] . Scrub typhus is transmitted to humans through the bite of infected larval trombiculid mites [4] . The clinical manifestations range from fever , headache , muscle pain , cough , and gastrointestinal symptoms , to coma , multi-organ failure and death [5] . In this study , we present data on the strain diversity and population structure of O . tsutsugamushi in Lao PDR ( Laos ) , a country where the incidence of scrub typhus is almost certainly under-reported . Two recent studies found that up to 15% of adult patients with undifferentiated fever had scrub typhus [6 , 7] . Molecular typing studies , aimed at understanding and monitoring the distribution of this disease , have been most commonly based on the highly polymorphic 56 kDa-outer membrane protein . This approach has indicated that the genotypes causing infection in Vientiane are similar to those circulating elsewhere in Laos and in Taiwan [8] . However , the use of a single surface protein gene marker can result in low resolution , or may provide misleading evidence concerning strain relatedness due to the confounding effects of recombination or immune selection . To address these shortcomings , we use multilocus sequence typing ( MLST ) , which utilises sequences of multiple housekeeping genes . These are under less diversifying selection than surface protein genes , and are better able to both determine the relationships between closely related genotypes and reveal the genetic structure and mode of evolution of the bacterial population ( clonal vs panmictic ) . Two alternative MLST schemes have been developed for O . tsutsugamushi; The first scheme characterised isolates from 84 Thai patients with scrub typhus , and revealed a highly diverse O . tsutsugamushi population with a very high rate of recombination [9] . Moreover , the rate of mixed infection , as indicated by ambiguous sequence at 1 or more loci , was as high as 25% . This high rate of mixed infection was not found by the authors who developed the second MLST scheme , although their scheme was applied to a relatively small number of cultured Cambodian strains rather than directly to patient blood [10] . Here we report the results of a 4 year prospective study aimed at determining the temporal dynamics and geographical structure of O . tsutsugamushi from patients from three different regions of Laos . We used the original MLST scheme ( 9 ) to characterise 74 isolates from these three different regions . The data confirm a highly diverse , recombining population , and reveal evidence for geographical structuring and local clonal expansion within Laos .
A prospective study of patients presenting with acute fever to three hospitals in Laos from August 2008 to December 2012 was carried out . The hospitals , chosen to be in central , north and south Laos , were Mahosot Hospital in the capital Vientiane ( 17° 57ʹ N 102° 36ʹ E ) [6] , Luang Namtha Provincial Hospital in the northwest ( 21° 00ʹ N 101° 24ʹ E ) , and Salavan Provincial Hospital in the south ( 15° 43ʹ N 106° 25ʹ E ) [7] ( Fig 1 ) . At Mahosot Hospital rickettsial blood culture was performed on all patients with suspected typhus . These were positive by point of care diagnostic test for either anti-O . tsutsugamushi IgM ( CareStart assay; AccessBio , USA or Scrub Typhus IgM ICT , PanBio Inc . , Australia ) [11] or anti-R . typhi IgM ( murine typhus Dip-Sticks IgM IBT , Panbio Inc . , Australia ) [12] . At Luang Namtha and Salavan patients with fever for ≤ 8 days , an admission tympanic temperature of ≥38°C , no obvious causes of fever ( e . g . abscess , severe diarrhea , pneumonia ) , and negative malaria rapid diagnostic test had rickettsial culture performed . This study was approved by the ethical review committee from the Lao National Ethics Committee for Health Research , Ministry of Health of Laos ( No 25/NECHR ) , the Oxford Tropical Ethics Committee , UK and the Ethical Committee of Faculty of Tropical Medicine , Mahidol University , Thailand ( Approval no . MUTM 2014-029-01 ) . All patients subject in this study have provided written informed consent , and parents or legal guardians of any children participant provided written informed consent on their behalf . O . tsutsugamushi was isolated from EDTA blood by in vitro isolation as previously described [13] . Briefly , 5 ml of blood was drawn from the patient and centrifuged at 3 , 000 rpm for 10 min . 200 μl of the buffy coat was collected and mixed with 1ml of RPMI 1640 medium containing 10 mM HEPES ( PAA , Austria ) supplemented with 10% ( v/v ) fetal calf serum and transferred to L929 ( mouse fibroblast ) cell culture . The mixture was incubated in the presence of 5% CO2 at 35°C for 2 hours , the supernatant was removed and 5 ml new culture media were added and for further incubation . Cell culture media was changed three times per week by removing 2 . 5 ml media and replacing this with an equal volume of fresh media . Rickettsia infected samples were identified using indirect immunofluorescence assays as previously described [13] . Briefly , the bacterial culture was coated onto microscope glass slides and monoclonal antibodies for scrub typhus ( STG-100 ) , typhus group monoclonal antibody ( TG-100 ) and spotted fever group monoclonal antibody ( SFG-100 ) ( Australian Rickettsial Reference Laboratory , Geelong , Australia ) were added , followed by secondary goat anti-human IgA/M/G labelled with FITC ( Invitrogen , USA ) . Fluorescence microscopy was used to identify cells infected with Orientia /Rickettsia . To confirm the presence of O . tsutsugamushi or Rickettsia spp . , quantitative real-time PCR assays based on the 47 kDa outer membrane protein gene for identification of O . tsutsugamushi , 17 kDa surface protein gene for genus Rickettsia and ompB gene for R . typhi were performed as previously described [14–16] . Genomic DNA of O . tsutsugamushi from the in vitro cell cultures was extracted using QIAamp DNA Mini kit 250 ( QIAGEN , USA ) and characterized using multilocus sequence typing ( MLST ) as previously described [9] . The housekeeping genes gpsA , mdh , nrdF , nuoF , ppdK , sucB , sucD were amplified by PCR and sequenced in both directions using nested primer pairs ( Table 1 ) . The sequence data were edited and analyzed using SeqMan from LaserGene software ( DNASTAR Inc . , Wisconsin , USA ) and allele numbers assigned by reference to previous data [9] . The MLST scheme for O . tsutsugamushi is hosted on the PubMLST website ( http://pubmlst . org/otsutsugamushi/ ) [17] . The relationships between the STs were visualized using two implementations of the BURST algorithm [18]; e-BURST v . 3 and goeBURST [19] . The dN/dS of the 7 housekeeping gene partial sequences were calculated using START2-Sequence Type Analysis and Recombinational Tests , ( http://pubmlst . org/software/analysis/start2/ ) [20] . A neighbour-joining tree of the isolates was constructed based on the 2 , 700 bp concatenated sequence of all loci ( gpsA-mdh-nrdF-nuoF-ppdK–sucB-sucD ) using MEGA version 5 [21] . The data in the current study was supplemented with existing data from Thailand [9] . The amount of genetic differentiation between populations from different geographical locations was estimated using F-statistics ( FST ) , which reflect the rates of migration , mutation and drift [22] . The estimation of the recombination per mutation ratio ( r/m ratio ) was calculated by comparing the sequences of non-identical alleles in all single locus MLST variants with their clonal founders . Multiple nucleotide changes ( >1 ) were assumed to be caused by recombination while single nucleotide differences not found elsewhere in the database were assumed to be due to de novo mutation [23] .
A total of 2 , 844 patients presenting with acute fevers were recruited from the three hospitals: 1 , 401 from Luang Namtha , 893 from Mahosot hospital and 550 from Salavan . A total of 195 ( 6 . 8% ) of these patients were culture positive for O . tsutsugamushi , 58 from Luang Namtha ( 4 . 1% of all patients from this hospital ) , 118 from Vientiane ( 13 . 2% of all patients from this hospital ) , and 19 from Salavan ( 3 . 4% of all patients from this hospital ) . The relatively high percentage of patients from Vientiane confirmed as scrub typhus positive may reflect difficulties incurred during the transportation of samples from the other two areas . A total of 215 isolates were confirmed by both IFA and PCR , of which 195 ( 90 . 7% ) were scrub typhus and 20 ( 9 . 3% ) were R . typhi ( Table 2 ) . The first 81 out of 195 ( 41 . 5% ) O . tsutsugamushi isolates were selected for MLST; 74 ( 91 . 3% ) were successfully amplified and sequenced , while the remaining 7 isolates produced poor quality data , most likely as a result of mixed infection . Of the final 74 isolates , 51 originated from Vientiane , 11 from Luang Namtha and 12 from Salavan . These 74 isolates corresponded to 50 different sequence types ( STs ) , 43 of which were novel to this study ( STs 50 through ST 92 ) . Simpson’s index of diversity was calculated as 0 . 98 ( 95% CI 0 . 97–0 . 99 ) confirming a highly diverse population [24] . The seven STs that were not novel had been previously reported by Sonthayanon et al . in a study of O . tsutsugamushi from patients presenting to a hospital in Udon Thani , Northeast Thailand [9] . In the current study , the isolates corresponding to these seven previously recorded STs all originated in Vientiane , which is on the Laos/Thai border . These shared STs largely correspond to the clonal complexes previously described in the Thai study; ST29 and ST30 correspond to CC29 , ST37 and ST25 correspond to CC37 , ST9 corresponds to CC10 and ST4 corresponds to CC13 . The remaining ST common to both studies was ST1 which is a single locus variant ( SLV ) of ST2 , the second most common ST noted in the Thai study [9] . This is consistent with the view that these clusters are commonly encountered in both Thailand and Vientiane , although they appear not to have made significant incursions to other regions of Laos . Of the novel STs , 34 originated from Vientiane , 7 from North-Laos ( Luang Namtha ) and 9 from South-Laos ( Salavan ) . The proportions of novel STs are therefore very similar in Vientiane ( 66% ) and Luang Namtha ( 63% ) , but slightly higher in Salavan ( 75% ) . These novel STs did not simply reflect different combinations of previously described alleles , as might be expected in this highly recombining species , but also new allele sequences . 18 new alleles were noted for gpsA , 6 for mdh , 13 for nrdF , 16 for nuoF , 17 for ppdK , 8 for sucB and 14 for sucD . This again points to considerable population diversity , both in terms of the overall number of STs , but also in terms of the number of alleles per locus . The most common sequence type was ST86 , which was represented by 7 isolates , all from Vientiane ( Table 3 ) . ST37 , ST58 , and ST71 were each represented by 3 isolates , and were also recovered from a single origin ( the three ST37 isolates were all from Vientiane , the three ST58 isolates from Luang Namtha and the three ST71 isolates from Salavan ) . Twelve STs represented by two isolates each were noted , nine of which originated exclusively from Vientiane ( STs 1 , 4 , 9 , 30 , 51 , 59 , 67 , 78 ) , with one pair from Luang Namtha ( ST65 ) and one pair from Salavan ( ST75 ) . There was a single occurrence of an ST being recovered from more than one region; ST69 corresponded to one isolate from Luang Namtha , and one from Vientiane . In summary , whilst the majority of the STs ( 34/50; 68% ) are only represented by a single isolate , in those cases where a single ST is represented by multiple isolates those isolates exhibiting the same ST also originate from the same region ( with the exception of a single isolate pair ) . Given that a pair of isolates drawn at random from the data would be expected to originate from the same region only 51 . 6% of the time ( calculated by summing the probabilities that a random pair of isolates both correspond to one of the three regions ) , this observation is therefore strongly indicative of geographical clustering and the local clonal expansion of specific STs . The MLST data for the 74 isolates from Laos were visualized using eBURST ( Fig 2A ) and goeBURST ( Fig 3 ) . The major difference between these two implementations of the BURST algorithm is that goeBURST provides the option to depict links between STs that differ at more than two loci , whilst eBURST will only show single locus variant ( SLV ) and double locus variant ( DLV ) links . Three clonal complexes ( CCs ) are resolved by eBURST . ST86 , which is the most common ST , defines 4 single-locus variants ( SLVs ) ( STs 58 , 85 , 87 , 88 ) and 1 double locus variant ( DLV ) ( ST84 ) . ST29 is represented by two isolates and also defines two SLVs ( ST30 , ST55 ) . ST25 , which is represented by a single isolate , defines 2 SLVs ( ST37 , ST83 ) . Three SLV pairs are noted ( ST52 and ST53 , ST56 and ST57 , ST64 and ST65 ) . Relaxing the linkage criteria to double locus variants reveals that the pair ST56 and ST57 are connected to CC86 , ST54 is connected to CC25 , ST62 and ST63 are connected to the ST64/65 pair , and ST66 and ST77 are joined by a DLV link . Twenty-seven of the 50 STs were not linked to any other STs on the basis of single or double locus variation , which further illustrates the high level of allelic diversity in this population . Analysis using goeBURST also pointed to ST86 as a likely founder ( Fig 3 ) , and shows several additional putative links of descent from this genotype by relaxing the criteria for joining STs . Our data were then compared with previously published data using comparative eBURST ( Fig 2B ) . Besides the seven STs that were noted previously in Thailand and in Vientiane ( but not other regions in Laos ) , there is almost no overlap between the two countries , and only a single SLV link was noted between STs from Thailand ( ST43 ) and Laos ( ST59 ) . Although there has been some O . tsutsugamushi migration between Thailand and Vientiane , as indicated by the 7 shared STs , Vientiane lies across the Mekong river from Udon Thani in Thailand and it is not surprising that STs present in Thailand are also present in patients in this city . However , there is no evidence from this analysis for overlap between the Thai isolates and isolates from elsewhere in Laos . In order to examine further the phylogeny and geographical structuring of the O . tsutsugamushi isolates , we combined the data for the 74 isolates from Laos with data for 83 strains from Thailand and 6 reference strains ( Karp , Kato , Gilliam , Sido , Boryong and Ikeda ) , giving a total of 163 strains . For each strain , we concatenated the individual allele data , resulting in fragments of 2 , 700 bp length . This alignment was then used to construct a neighbour-joining tree as implemented in MEGA version 5 ( Fig 4 ) . The clusters resolved by eBURST from both the current and previous Thai study are annotated on the phylogenetic tree . The largest clusters of Thai isolates are CC29 and ST1/ST2 , and the tree shows the identical , or very closely related isolates , from Vientiane that correspond to these clusters . The most common clonal complex in the current study , CC86 , is confirmed to be composed of a mixture of isolates from Vientiane and Luang Namtha . A second cluster of five isolates from Luang Namtha ( including ST65 ) and three from Vientiane is also noted . In contrast eight of the isolates from Salavan correspond to a single diverse cluster ( incorporating ST71 and ST75 ) , which also incorporates a single isolate from Thailand . The other four Salavan isolates are found elsewhere in the tree , but do not correspond to any of the major clusters . The relatively high level of diversity in the major Salavan cluster points to a local population of bacteria circulating in relative isolation in this region over a protracted period of time . In contrast , the more closely related clusters ( those of common STs and close relatives that can be identified by eBURST , such as CC29 ) represent more recent introductions in to a region followed by rapid clonal expansion . The phylogenetic analysis paints the following general picture regarding geographical structure and spread . Isolates from Vientiane overlap with isolates from Udon Thani and from Luang Namtha , pointing to a key role of the capital both as a focus for movement of isolates between Thailand and Laos and also potentially as a reservoir for spread to and from other parts of Laos . However , there is no evidence for migration between Udon Thani and Luang Namtha . In contrast , the isolates from Salavan appear distinct from all other regions and are less clustered . This indicates that the strains in this region have been diversifying in relative isolation . In order to explore this picture further we computed pairwise FST values for each of the four populations corresponding to Vientiane , Luang Namtha , Salavan and the previously published strains from Udon Thani . These values are given in Fig 5 along with a dendrogram illustrating the level of differentiation between the four populations . Of the 6 pairwise comparisons , two show low levels of differentiation , two moderate and two high . Low levels of genetic differentiation ( ~0 . 05 ) are apparent between the Vientiane and the Thai populations , and between the Vientiane and Luang Namtha populations , consistent with the phylogenetic analysis . A moderate level of differentiation is noted between the Thai and Luang Namtha populations and the Vientiane and Salavan populations ( 0 . 17 and 0 . 18 respectively ) . Finally , a high level of differentiation is seen between the Salavan population and both the Thai and Luang Namtha populations ( 0 . 24 and 0 . 27 respectively ) . In summary , this analysis is consistent with the interpretation of the phylogenetic tree in confirming the relative isolation of the Salavan population , and pointing to the Vientiane population as being most “central” ( i . e . showing the lowest average differentiation to all other populations ) . The ratios of dN/dS of the 7 loci corresponded to a range of 0 . 002–0 . 310 ( Table 4 ) , confirming that all genes are evolving predominantly by purifying ( stabilizing ) selection . This also indicated that synonymous substitutions were more common than non-synonymous substitutions for all the genes tested for these bacteria . We note that the dN/dS ratio of sucD and nrdF is approximately an order of magnitude lower than the other genes . This was also apparent in the previous data in Thailand [9] and suggests particularly strong selective constraint on these two genes in the O . tsutsugamushi genome . In order to understand how O . tsutsugamushi was diversified , an estimation of the ratio of recent recombination to mutation events ( r/m ) in clonal complexes was performed by comparing the sequences of mismatched alleles in clonal founders and single locus variants [23] . The estimated ratio of recombination to mutation of these two populations in Laos ( n = 74 ) and Thailand ( n = 89 ) was high at both the nucleotide level ( 95:1 ) and at allele level ( 17:1 ) , suggesting that the diversification of O . tsutsugamushi is predominantly characterized by recombination rather than mutation at both nucleotide level and allele level .
This study represents the first investigation into the diversity and phylogeography of O . tsutsugamushi in Laos . As the isolates were characterized using the same MLST scheme , it was possible to combine these data with those from a previous study focusing on strains from Udon Thani in Northeast Thailand . Our results reveal a highly diverse and recombining population in Laos , as evidenced by the high diversity index ( 0 . 98 ) with high number of STs per isolate ( 50 STs in 74 isolates , 0 . 68 STs per isolate ) . This is consistent with the previous Thai study ( 0 . 95 STs per isolate ) [9] , although the diversity in the current Lao sample set might be expected to be slightly higher , as it represents three distinct geographic sources . The ecological implications of the very high rate of recombination are unclear , but this may reflect co-colonisation of either the mites or the rodents . It is possible that high rates of recombination might also reflect a mechanism for diversification and host adaptation in O . tsutsugamushi [25] . The O . tsutsugamushi genome displays a massive proliferation of mobile elements and repeat sequences [26] which are thought to facilitate horizontal gene transfer . Approximately 8 . 6% ( 7/81 ) of the sequenced isolates appeared to represent mixed infections in patients . This is a lower frequency than in Thailand , where 25% of cultures from patients’ blood were noted to be probable mixed infections . It is possible that the relatively low frequency of mixed infection in the Laos data is an artifact resulting from the in vitro culture which may have acted to amplify single predominant strains at the expense of more rare variants over several passages . It is also possible that the predominant isolate was more highly adapted to the culture conditions . It is not clear whether mixed infection primarily results from multiple mite bites , or from co-colonisation of multiple strains within individual mites . The latter possibility is supported by the detection of multiple antigenic strains of O . tsutsugamushi in both naturally infected and laboratory-reared chigger mites ( Leptotrombidium spp . ) [27 , 28] . As expected , the MLST genes show low dN/dS ratios , which is indicative of stabilizing selection . This is particularly true for sucD and nrdF which may be under unusual levels of selective constraint . The sucD gene produces succinyl-CoA synthase which uses succinyl CoA as a substrate to produce succinate and generate GTP in the citrate pathway ( TCA cycle ) [29 , 30] . Unlike other rickettsia O . tsutsugamushi has no active pyruvate dehydrogenase enzyme to convert pyruvate to acetyl-CoA ( 30 ) and has only a partial TCA cycle starting with α-ketoglutarate and ending with oxaloacetate . This ‘minimal’ citric acid cycle requires succinyl-CoA synthase and may explain why sucD is relatively conserved in Orientia . The ribonucleoside-diphosphate reductase beta subunit gene ( nrdF ) is involved in purine and pyrimidine biosynthesis in O . tsutsugmushi . The genetic and metabolic diversity in Rickettsia has been reported previously [30] . While the proteins unique to Rickettsia spp . represent a broad spectrum of functional categories ( carbohydrate , lipid transport ) , more than 60% of the proteins unique to O . tsutsugamushi belong to the replication , recombination and repair process categories . The nrdF gene product is strongly associated with these 3 processes , perhaps explaining why it is relatively conserved in O . tsutsugamushi . Limitations of the study include the fact that not all O . tsutsugamushi isolates underwent MLST and that the patient inclusion criteria for patients recruited in the north and south of the country differed from those recruited in the centre . Our MLST data reveals a mixed picture concerning geographic structure and migration . First , there is clearly migration and overlap between the strains from Vientiane and from Udon Thani . This is evidenced by shared STs , the intermingling of the isolates on the neighbour-joining tree , and by the FST analysis . This is perhaps not surprising as these locations straddle the Lao/Thai border . It is possible that disease transmission occurs via the trading activities of villagers in the border area , commuting , or tourism . This may be due to both human movement and movement of mites via animals . There is no evidence of overlap between the Thai isolates and the Lao isolates from the north ( Luang Namtha ) or the south ( Salavan ) . There is , however , evidence of transmission between Vientiane and Luang Namtha , particularly with respect to the most common cluster observed in our study , CC86 . In contrast , most of the strains from Salavan appear to form a loose cluster which is not closely related to isolates from any of the other regions . Salavan and Luang Namtha have remained relatively undisturbed rural hinterlands with environments which may be particularly suited to the maintenance of large populations of chigger mites . In contrast , Vientiane ( the capital of Laos ) is rapidly expanding into surrounding paddy fields and the rural hinterland [31] . This anthropogenic disturbance has likely had a major impact on the life cycle , ecology and behaviour of O . tsutsugamushi bacteria , their mite vectors , and their rodent and human hosts to limit the spread of the disease . A study on spatial distribution of scrub typhus in Vientiane demonstrated that the prevalence of scrub typhus IgG antibodies among patients from rural villages is significantly higher than that in patients from urban settings . Moreover , many urban patients are positive for O . tsutsugamushi IgG suggesting prior exposure to scrub typhus , possible in rural settings [31] .
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Scrub typhus , caused by the pathogen Orientia tsutsugamushi , is endemic in Southeast Asia , including Laos , accounting for up to 15% of cases of undifferentiated fever in adult patients . Despite its public health importance , little is known about the genetics of the O . tsutsugamushi population in Laos—this information is important for optimizing diagnostics and epidemiological surveillance . We conducted a 4 year prospective study to examine the genetic diversity of O . tsutsugamushi causing scrub typhus in Lao patients and highlight the geographical differentiation that can occur even within a small country .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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The Diversity and Geographical Structure of Orientia tsutsugamushi Strains from Scrub Typhus Patients in Laos
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